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vision | computer vision examples this project contains code examples created in visual studio code for computer vision using c opencv point cloud library pcl these examples are created for the computer vision subject of robotics software engineering degree at urjc opencv installation from source probably opencv is installed but it s a good practice to install it as follows open an ubuntu terminal and follow the next steps 1 install dependencies sudo apt install build essential cmake git pkg config libgtk 3 dev libavcodec dev libavformat dev libswscale dev libv4l dev libxvidcore dev libx264 dev libjpeg dev libpng dev libtiff dev gfortran openexr libatlas base dev python3 dev python3 numpy libtbb2 libtbb dev libdc1394 dev 2 clone opencv and contrib repositories mkdir opencv build cd opencv build git clone https github com opencv opencv git git clone https github com opencv opencv contrib git 3 create temporary build directory cd opencv build opencv mkdir build cd build 4 setup opencv without cuda cmake d cmake build type release d cmake install prefix usr local d install c examples on d install python examples on d opencv generate pkgconfig on d opencv extra modules path opencv build opencv contrib modules d build examples on d opencv enable nonfree on with cuda cmake d cmake build type release d cmake install prefix usr local d install c examples on d install python examples on d opencv generate pkgconfig on d opencv extra modules path opencv build opencv contrib modules d build examples on d opencv enable nonfree on d with cuda on d opencv dnn cuda on d with cudnn on d enable fast math 1 d cuda fast math 1 d cuda arch bin 8 6 d with cublas 1 cuda arch bin can be found here https developer nvidia com cuda gpus 5 compilation process make j expr nproc 2 6 installation process sudo make install 7 import opencv package pkg config opencv4 cflags libs 8 add in bashrc echo export ld library path ld library path usr local lib bashrc 9 load the libraries into the current shell source bashrc pcl installation from source the best way to be updated is to install pcl compiling from source https pcl readthedocs io projects tutorials en latest compiling pcl posix html it fixs some problems when you try to use ubuntu 22 04 vtk 9 1 and pcl 1 12 1 1 clone pcl repository mkdir pcl build cd pcl build git clone recursive https github com pointcloudlibrary pcl git 2 create temporary build directory cd pcl build pcl mkdir build cd build 3 run the cmake build system using the default options cmake please note that cmake might default to a debug build if you want to compile a release build of pcl with enhanced compiler optimizations you can change the build target to release with dcmake build type release cmake dcmake build type release 4 compilation process if it fails rerun the command make j2 5 installation process sudo make j2 install compiling examples and creating executables opencv examples use a makefile use make command to compile and create the executable cd folder example make executable pcl examples use a cmakelist txt so you should create the makefile using cmake and create the executable using make is a good practice to create it in a build folder cd folder example mkdir build cd build cmake make executable about this is a project made by jos miguel guerrero associate professor at universidad rey juan carlos copyright copy 2021 twitter https img shields io badge follow jm guerrero green svg https twitter com jm guerrero license shield cc by sa 4 0 cc by sa shield cc by sa this work is licensed under a creative commons attribution sharealike 4 0 international license cc by sa cc by sa 4 0 cc by sa image cc by sa cc by sa http creativecommons org licenses by sa 4 0 cc by sa image https licensebuttons net l by sa 4 0 88x31 png cc by sa shield https img shields io badge license cc 20by sa 204 0 lightgrey svg universidad rey juan carlos https www urjc es jos miguel guerrero https sites google com view jmguerrero | opencv urjc robotics computer-vision pcl-library cpp | ai |
sw_machine_learning | machine learning https github com yunshuipiao cheatsheets ai code blob master md img md maching learning https github com yunshuipiao cheatsheets ai code blob master md machine learning md personal blog python https github com yunshuipiao swblog blob master maching 20learning e6 9c ba e5 99 a8 e5 ad a6 e4 b9 a0 e4 b9 8b e7 ba bf e6 80 a7 e5 9b 9e e5 bd 92 e7 ba afpython e5 ae 9e e7 8e b0 md python https github com yunshuipiao swblog blob master maching 20learning e6 9c ba e5 99 a8 e5 ad a6 e4 b9 a0 e4 b9 8b e9 80 bb e8 be 91 e5 9b 9e e5 bd 92 e7 ba afpython e5 ae 9e e7 8e b0 md python https github com yunshuipiao swblog blob master maching 20learning e6 9c ba e5 99 a8 e5 ad a6 e4 b9 a0 e4 b9 8b e8 b4 9d e5 8f b6 e6 96 af e5 88 86 e7 b1 bb python e5 ae 9e e7 8e b0 md knn python https github com yunshuipiao swblog blob master maching 20learning e6 9c ba e5 99 a8 e5 ad a6 e4 b9 a0 e4 b9 8bknn e7 ae 97 e6 b3 95 e7 ba afpython e5 ae 9e e7 8e b0 md k means python https github com yunshuipiao swblog blob master maching learning e6 9c ba e5 99 a8 e5 ad a6 e4 b9 a0 e4 b9 8bk means e8 81 9a e7 b1 bb e7 ae 97 e6 b3 95 python e5 ae 9e e7 8e b0 md id3 python https github com yunshuipiao swblog blob master maching learning e6 9c ba e5 99 a8 e5 ad a6 e4 b9 a0 e4 b9 8b e5 86 b3 e7 ad 96 e6 a0 91id3 python e5 ae 9e e7 8e b0 md https github com yunshuipiao swblog blob master maching learning e6 9c ba e5 99 a8 e5 ad a6 e4 b9 a0 e4 b9 8b e9 9a 8f e6 9c ba e6 a3 ae e6 9e 97 e7 ae 80 e5 8d 95 e7 90 86 e8 a7 a3 md svm https github com yunshuipiao swblog blob master maching learning e6 9c ba e5 99 a8 e5 ad a6 e4 b9 a0 e4 b9 8bsvm e7 ae 80 e5 8d 95 e7 90 86 e8 a7 a3 md python cart https github com yunshuipiao swblog blob master maching learning e6 9c ba e5 99 a8 e5 ad a6 e4 b9 a0 e4 b9 8b e5 88 86 e7 b1 bb e5 9b 9e e5 bd 92 e6 a0 91 python e5 ae 9e e7 8e b0cart md gbdt https github com yunshuipiao swblog blob master maching learning e6 9c ba e5 99 a8 e5 ad a6 e4 b9 a0 e4 b9 8bgbdt e7 ae 80 e5 8d 95 e7 90 86 e8 a7 a3 md neural networks and deep learning http neuralnetworksanddeeplearning com index html python numpy ann colah github io http colah github io cnn rnn cs229 linear and logistic regression http cs229 stanford edu notes cs229 notes1 pdf sigmoid softmax regression pattern recognition and machine learning https book douban com subject 2061116 svm https blog csdn net v july v article details 7624837 svm kernel svm interview it http www allitebooks com http www allitebooks com | python ai machine-learning machine-learning-algorithms | ai |
PiOS | pios rtos designed for automatics control tasks development in an alpha stage development of the main part of the kernel is mainly finished but it has not been tested in real application there are many improvements to do see issues please feel free to contribute if you want and feel that it s worth it motivation kernel was created in order to improve quality of control tasks main responsibilities of kernel are task cheduling and dynamic memory allocation kernel is meant to be extra small and light it s a must in a small embedded devices also it is assumed that kernel itself will use newest possible technologies at the time of implementation it should not influence applications especially it will not enforce compiler used etc because kernel is provided as a precompiled library supported hardware adding next supported hardware is as simple as adding new directory in sources pios hardware after this new entry in cmake gui appears drop down list pios platform type | operating-system | os |
MAD-Project | mad project mobile application development project language java android development group project oop concepts really interested in android development | front_end |
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Datasets | machine learning datasets this repository contains a copy of machine learning datasets used in tutorials on machinelearningmastery com this repository was created to ensure that the datasets used in tutorials remain available and are not dependent upon unreliable third parties all regression and classification problem csv files have no header line no whitespace between columns the target is the last column and missing values are marked with a question mark character in many cases tutorials will link directly to the raw dataset url therefore dataset filenames should not be changed once added to the repository datasets this section provides a summary of the datasets in this repository binary classification datasets breast cancer wisconsin breast cancer wisconsin csv breast cancer yugoslavia breast cancer csv breast cancer haberman s haberman csv bank note authentication banknote authentication csv horse colic horse colic csv ionosphere ionosphere csv pima indians diabetes pima indians diabetes csv sonar returns sonar csv german credit german csv credit card fraud creditcard csv zip adult income adult all csv mammography mammography csv oil spill oil spill csv phoneme phoneme csv multiclass classification datasets glass identification glass csv iris flower species iris csv wheat seeds wheat seeds csv wine wine csv ecoli ecoli csv thyroid gland new thyroid csv regression datasets boston housing housing csv auto insurance total claims auto insurance csv auto imports prices auto imports csv abalone age abalone csv wine quality red winequality red csv wine quality white winequality white csv univariate time series datasets daily minimum temperatures in melbourne daily min temperatures csv daily maximum temperatures in melbourne daily max temperatures csv daily female births in california daily total female births csv monthly international airline passengers monthly airline passengers csv monthly armed robberies in boston monthly robberies csv monthly sunspots monthly sunspots csv monthly champagne sales monthly champagne sales csv monthly shampoo sales monthly shampoo sales csv monthly car sales monthly car sales csv monthly mean temperatures in nottingham castle monthly mean temp csv monthly specialty writing paper sales monthly writing paper sales csv yearly water usage in baltimore yearly water usage csv multivariate time series datasets hourly pollution levels in beijing pollution csv minutely individual household electric power consumption household power consumption zip human activity recognition using smartphones har smartphones zip indoor movement prediction indoormovement zip yearly longley economic employment longley csv natural language processing flickr 8k photo caption dataset flickr8k dataset zip flickr8k text zip movie review polarity review polarity tar gz german to english translation deu eng txt the republic by plato republic txt arff datasets weka uci datasets weka datasets zip weka numeric datasets weka datasets numeric zip | machine-learning datasets | ai |
mobilebbbook.github.com | mobilebbbook github com mobile web development with backbone js web site summary mobile and desktop web application patterns written in coffeescript and test driven with jasmine js jekyll jekyll pygments no lsi safe | front_end |
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Bdd | div align center img width 100 src https i imgur com xpxmvv9 png alt bdd div instructions the practices are organized as follows the p folders represent each of the practices with their corresponding number also in each practice you will find a pdf document with the statements of the exercises within these folders are a series of subfolders denoted as e that represent each of the exercises of the practices the practices are made with sqldeveloper to see them simply import the corresponding file | practices exercises university | server |
ExoVisix | e x o v i s i x p align center img src logo png alt logo style width 220px div p exovisix is a smart computer vision application with various functionalities i have tried to put as many machine learning tools as possible into one single application for greater productivity key features auto attendance system using real time face recognition face trainer motion detection ocr optical character reader gesture control controlling mouse pointer using finger or red colored object rectangle shape detection trained faces image gallery view eye detection persistent storage for trained faces image using database technology used core java javacv wrapper of opencv javafx mysql maven tesseract ocr framework user interface img src src applayout png alt exovisix ui style width 700px installation guide video guide image alt text src sc png https www youtube com embed wzwc4rujs1y video title ide bash i have developed this project using eclipse neon so i highly recommend you to use this particular ide maven dependencies xml dependency groupid org bytedeco groupid artifactid javacv platform artifactid version 1 3 2 version dependency dependency groupid mysql groupid artifactid mysql connector java artifactid version 5 1 14 version dependency dependency groupid org bytedeco javacpp presets groupid artifactid tesseract platform artifactid version 3 04 01 1 3 version dependency required software to properly run this application on your system at first you need to download and install the following software an implementation of java se 7 or newer jdk http www oracle com technetwork java javase downloads index html an implementation of javafx follow the installation instruction javafx https docs oracle com javafx 2 installation jfxpub installation htm an implementation of javacv follow the installation instruction javacv https github com bytedeco javacv an implementation of mysql database xampp https www apachefriends org download html to connect mysql with java you will need a connector follow the installation instruction mysql connector java https dev mysql com downloads connector j 5 1 html an implementation of javafx scene builder follow the installation instruction javafx scene builder https docs oracle com javafx scenebuilder 1 installation 1 0 jsbpub installation 1 0 htm finally please make sure everything has the same bitness 32 bit and 64 bit modules do not mix under any circumstances configuration settings exovision may not work properly without these settings before executing the app you have to make some change to below mentioned files database settings open mysql on xampp then create a new database name it ghosteye now import attached face bio sql to the ghosteye database or create a new schema table sql create table if not exists face bio id int 11 not null code int 10 not null first name varchar 30 not null last name varchar 20 not null reg int 10 not null age int 10 not null section varchar 20 not null engine innodb auto increment 1 default charset latin1 alter table face bio add primary key id alter table face bio modify id int 11 not null auto increment auto increment 1 now open src application database java and provide your mysql db credintials java package application import java sql import java util arraylist import java util list class database public int code public string fname public string lname public int reg public int age public string sec public final string database name your database public final string database user your database user name public final string database pass your database password ocr settings to use tesseract api at first you have to install tesseract with desired language training data on your system after that you have to mention the installation folder java now goto src application ocr java in line 36 provide your tesseract installation directory name tips when you going to train a new face try to capture at least 10 pictures of a single person in different angle keep it in mind that the more number of training image in different angle and posture the more accurate will be face recognition after everything done kindly empty the faces folder there is a test face image you have to delete it please note please keep it in mind sometimes the face recognition algorithm provides wrong output if a person is not trained or unknown to the system the reason behind this is that the face recognition algorithm guess the face with the nearest match when it does not find any match the system pick any face with a nearest match this is why it sometimes provides wrong output video tutorial visit https www youtube com watch v 6unbzfvy8he t 3s licence licence mit license copyright c 2017 anup kumar sarkar permission is hereby granted free of charge to any person obtaining a copy of this software and associated documentation files the software to deal in the software without restriction including without limitation the rights to use copy modify merge publish distribute sublicense and or sell copies of the software and to permit persons to whom the software is furnished to do so subject to the following conditions the above copyright notice and this permission notice shall be included in all copies or substantial portions of the software the software is provided as is without warranty of any kind express or implied including but not limited to the warranties of merchantability fitness for a particular purpose and noninfringement in no event shall the authors or copyright holders be liable for any claim damages or other liability whether in an action of contract tort or otherwise arising from out of or in connection with the software or the use or other dealings in the software | javacv opencv computer-vision motion-detection gesture-detection face-recognition mechine-learing javafx ocr-recognition mysql-database eye-detection haar-training bio-metric-attendance-system | ai |
system-design-with-code | system design with code computer system design not just on whiteboard but with code build status https api travis ci org npathai system design with code svg branch master https travis ci org npathai system design with code why this repository this repository represents an effort to learn system design by experimenting failing fast learning from that experince and providing all the fellow developers a wealth of knowledge in terms of source code system design always seemed quiet far from reach because the knowledge available online either is too shallow or basic or quiet high level being a developer i wanted to learn by looking at code and experimenting facing challenges head on and building robust systems if you feel the same then this repository is perfect for you goals try to re create system design case studies not just on prototype scale but full scale i intend to deploy sytems on cloud and load test them at scale all systems built in this repository should be microservices driven or even serverless lightweight highly scalable fault tolerant kill machines randomly and system shouldn t cave in no single point of failure high performance observable and traceable projects url shortening service chatter slack inspired from mattermost discourse qna bookmyshow technology stack 1 micronaut framework 2 zookeeper 3 consul service discovery 4 mysql 5 redis cache 6 test containers 7 react frontend 8 docker 9 zipkin 10 hystrix resilience4j 11 micrometer 12 prometheus 13 grafana 14 gatling | microservice system-design interview-preparation architecture architectural-patterns software-architecture software-design | os |
EmbeddeDAM | dam damn pnu cse 2020 fall semester embedded system design experiment term project 3 1 stm32 board dam 01 https user images githubusercontent com 49744580 102891798 2b7dfd80 44a2 11eb 8284 9549e3ae11d3 jpg tft lcd smart phone sensor bluetooth connection 02 https user images githubusercontent com 49744580 102892140 cbd42200 44a2 11eb 8ec0 3bb40f4aa7f4 jpg dam 03 https user images githubusercontent com 49744580 102892143 cd9de580 44a2 11eb 9cc0 3cf0a13a8e5e jpg | dam embedded stm32 | os |
hypetrigger | hypetrigger github https github com nathanbabcock hypetrigger crates io https crates io crates hypetrigger docs rs https docs rs hypetrigger npm https www npmjs com package hypetrigger website https hypetrigger io discord https discord gg vcadvczwm9 perform efficient per frame operations on streaming video getting started rust sh cargo add hypetrigger install native dependencies w vcpkg cargo install cargo vcpkg cargo vcpkg build what does it do streaming video input with ffmpeg sidecar https github com nathanbabcock ffmpeg sidecar image processing with photon https github com silvia odwyer photon text recognition with tesseract https github com tesseract ocr tesseract image recognition with tensorflow https github com tensorflow tensorflow wasm output with wasm bindgen https github com rustwasm wasm bindgen if you re just looking for a minimal wrapper around ffmpeg without the extra bindings for image processing and computer vision you should use the ffmpeg sidecar https github com nathanbabcock ffmpeg sidecar crate directly architecture diagram simple version txt video ffmpeg tensorflow tesseract custom callback annotated version txt metadata progress errors stderr tesseract callback input video ffmpeg stdout tensorflow callback video files static images http urls stdin custom trigger callback live streams desktop capture webcam video pause stop commands media source video decoding computer vision callback simple example rust rs use hypetrigger hypetrigger simpletrigger fn main hypetrigger new test input add trigger simpletrigger new frame println received frame x frame frame num frame image width frame image height now do whatever you want with it run in depth example rust this is slightly simplified sample code it won t immediately compile and work without the right input source and parameters but it illustrates how to use the api to solve a real world problem problem statement detect when a goal is scored in live video of a world cup match cargo toml toml dependencies hypetrigger version 0 2 0 features photon tesseract enable the tesseract feature and its photon dependency for image processing see the native dependencies section in readme md if you have trouble building main rs rs use hypetrigger hypetrigger simpletrigger use hypetrigger photon crop thresholdfilter use hypetrigger tesseract tesseracttrigger init tesseract fn main first init a tesseract instance with default params let tesseract init tesseract none none initialize some state use an rc or arc mutex if needed let mut last score option u32 none create a trigger that will be used to detect the scoreboard let trigger tesseracttrigger tesseract pass in the tesseract instance identify the rectangle of the video that contains the scoreboard probably the bottom middle of the screen crop some crop left percent 25 0 top percent 25 0 width percent 10 0 height percent 10 0 filter the image to black and white based on text color this preprocessing improves tesseract s ability to recognize text you could replace it with your own custom preprocessing like edge detection sharpening or anything else threshold filter some thresholdfilter r 255 g 255 b 255 threshold 42 attach the callback which will run on every frame with the recognized text callback result let parsed score u32 result text parse if parsed score is err return ok no score detected continue to next frame check for different score than last frame if last score unwrap parsed score unwrap println a goal was scored do something todo celebrate todo tell your friends todo record a clip todo send a tweet todo cut to commercial break update state last score parsed score using this option will pause after every frame so you can see the effect of your crop filter settings enable debug breakpoints false create a pipeline using the input video and your customized trigger hypetrigger new input https example com world cup broadcast m3u8 add trigger trigger run run will block the main thread until the job completes but the callback will be invoked in realtime as frames are processed getting started typescript browser and node are supported through a wasm compilation of the image preprocessing code with the excellent photon js https github com silvia odwyer photon image processing library after that tesseract js https github com naptha tesseract js is used for the text recognition console npm add hypetrigger ts const videoelem document getelementbyid video const pipeline new hypetrigger videoelem addtrigger frame console log frame do whatever you want with the frame autorun limitations the ts version is not a fully featured port of the rust library rather it is more of a parallel toolkit with a subset of the full functionality there are no tensorflow js https github com tensorflow tfjs bindings yet and frames are pulled directly from media sources eliminating the useage of ffmpeg completely for more information see this page in the docs using with other languages docs src other languages native dependencies visual studio build tools must install visual studio build tools 2017 current version 15 9 50 must also install visual studio community 2019 with the following components of desktop development with c workload msvc v142 vs 2019 c x65 x86 build tools c cmake tools for windows c atl for latest v142 build tools build tools are required by cargo vs 2019 is used to compile link native dependencies tensorflow should be installed automatically by cargo tesseract install with cargo vcpkg sh cargo install cargo vcpkg cargo vcpkg build or install manually with vcpkg github https github com microsoft vcpkg quick start windows sh git clone https github com microsoft vcpkg cd vcpkg bootstrap vcpkg bat vcpkg integrate install vcpkg install leptonica x64 windows static md vcpkg install tesseract x64 windows static md also install libclang included in the latest llvm release https github com llvm llvm project releases current version https github com llvm llvm project releases download llvmorg 14 0 6 llvm 14 0 6 win64 exe useful links https github com charlesw tesseract wiki compiling tesseract and libleptonica using vcpkg https sunnysab cn translate goog 2020 10 06 use tesseract to identify captchas in rust x tr sl zh cn x tr tl en x tr hl en x tr pto sc wasm pack sh cargo install wasm pack if you get openssl perl errors like this this perl implementation doesn t produce windows like paths try running once from windows cmd exe instead of vscode integrated terminal and or git bash contribution pull requests bug reports and feature requests are welcome on the github page | ai |
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blockchain-id-deprecated | blockchain id docs deprecated view the blockstack documentation https blockstack org docs | blockchain |
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blockchain-book | learn blockchain by building one this is the full source code for my book learn blockchain by building one https www amazon com learn blockchain building understanding cryptocurrencies dp 1484251709 ref sr 1 3 crid 1tb6lkk9insjc dchild 1 keywords learn blockchain by building one qid 1613493701 sprefix learn blockchain 2caps 2c144 sr 8 3 apress amazon please submit any issues found in the code here https github com dvf blockchain book issues and if i haven t responded to them please get my attention at hi dvf nyc and i ll do my best to help you out the code the finalized blockchain is located in chapters chapter 7 please ensure all dependencies are installed bash cd chapters chapter 7 poetry install creating virtualenv chapter 7 uy9ygse2 py3 8 in home dan3x cache pypoetry virtualenvs installing dependencies from lock file package operations 50 installs 0 updates 0 removals installing pyparsing 2 4 7 installing six 1 15 0 installing attrs 20 2 0 installing colorama 0 4 3 installing idna 2 10 installing iniconfig 1 0 1 then you can run the node poetry shell chapter 7 py3 8 python node py 2021 02 16 11 37 35 creating genesis block 2021 02 16 11 37 35 server listening on 0 0 0 0 8888 2021 02 16 11 37 35 found external ip xxx xxx xxx xxx | blockchain |
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sby | symbiyosys sby is a front end driver program for yosys https yosyshq net yosys based formal hardware verification flows see https yosyshq readthedocs io projects sby https yosyshq readthedocs io projects sby for documentation on how to use symbiyosys symbiyosys sby itself is licensed under the isc license note that the solvers and other components used by symbiyosys come with their own license terms there is some more details in the selecting the right engine section of the documentation https yosyshq readthedocs io projects sby en latest quickstart html selecting the right engine symbiyosys sby is part of the tabby cad suite https www yosyshq com tabby cad datasheet and the oss cad suite https github com yosyshq oss cad suite build the easiest way to use sby is to install the binary software suite which contains all required dependencies including all supported solvers contact yosyshq https www yosyshq com contact for a tabby cad suite https www yosyshq com tabby cad datasheet evaluation license and download link or go to https github com yosyshq oss cad suite build releases to download the free oss cad suite follow the install instructions on github https github com yosyshq oss cad suite build installation make sure to get a tabby cad suite evaluation license for extensive systemverilog assertion sva support as well as industry grade systemverilog and vhdl parsers for more information about the difference between tabby cad suite and the oss cad suite please visit https www yosyshq com tabby cad datasheet | front_end |
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spotify-web-player | spotify web player clone a front end clone project of the spotify web player the project was created using react this is my first big react js project preview link spotify web player clone https spotify clone oguz3 web app tech framework used react css | reatctjs css html javascript spotify | front_end |
iHealth_app | ihealth ihealth demo mui webapp mui http www dcloud io mui html arttemplate https aui github io art template docs syntax html js hbuilder http www dcloud io index html socket io https socket io docs 1 hbuilder http www dcloud io index html 2 hbuilder 3 hbuilder hbuilder app 02 helloworld http blog csdn net uikoo9 article details 46734079 todo x x x x js arttemplate x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x h3 strong x x x x x x md5 bug br bug bug a href js onclick id init mui plusready mui http ask dcloud net cn article 786 mui http dev dcloud net cn mui ui arttemplate https aui github io art template docs syntax html mui http blog csdn net hbcui1984 article details 42156409 app mui https ke qq com course 203400 hello mui http ask dcloud net cn article 12575 html5 http ask dcloud net cn article 25 git http www cnblogs com lout p 6111739 html hbuilder mui webview http blog csdn net zhuyu19911016520 article details 70270731 hbuilder mui 2 tab http blog csdn net anjingshen article details 74138717 tab nativeobj tab https github com dcloudio mui tree master examples nativetab http dev dcloud net cn mui pullup 7 mui vue js http blog csdn net u012453773 article details 52292816 mui http blog csdn net sbt0198 article details 52215614 scroll scrollto 0 0 100 mui scrolltobottom http blog csdn net sbt0198 article details 51755843 evaljs ios http ask dcloud net cn question 11022 mui http dev dcloud net cn mui ui scroll mui scroll http luckylearn iteye com blog 2366710 mui mui scroll onclick mui onclick http ask dcloud net cn question 21432 mui scroll onclick http ask dcloud net cn question 19170 demo mui a http ask dcloud net cn question 6444 bug ios div webview mui mui scroll wrapper scroll pullrefresh ios https ask dcloud net cn article 12681 bug mui fire srcolltop http ask dcloud net cn question 3186 css http blog csdn net plutohusky article details 6043366 mui im web im sdk https segmentfault com a 1190000005729743 articleheader11 web http www 52im net thread 338 1 1 html web comet websocket sse http www 52im net thread 336 1 1 html socket io websocket web http www 52im net forum php mod viewthread tid 190 ctid 15 ios header http ask dcloud net cn question 10629 hbuilder mui http www bcty365 com content 146 3158 1 html mui http ask dcloud net cn article 788 mui app http blog csdn net well2049 article details 69499644 mui index webview id http www bcty365 com content 146 5242 1 html webview id http ask dcloud net cn question 3903 js class http www cnblogs com dealblog p 6885437 html html5 14 http blog csdn net u013267266 article details 51398333 mui table view li li http ask dcloud net cn question 5411 mui datepicker http www hcoder net tutorials info 86 html | mui webapp socket-io | front_end |
cog-mpt-7b-storywriter-65k | cog mpt 7b storywriter 65k replicate https replicate com replicate mpt 7b storywriter badge https replicate com replicate mpt 7b storywriter a cog implementation of mosaicml s mpt 7b storywriter 65k large language model this is a guide to running mpt 7b storywriter 65k in the cloud using replicate you ll use the cog https github com replicate cog command line tool to package the model and push it to replicate as a web interface and api mpt 7b storywriter 65k is a language model that specializes in generating fictional stories with lengthy context lengths the model was created by finetuning mpt 7b with a context length of 65k tokens on a filtered fiction subset of the books3 dataset thanks to alibi the model can extrapolate beyond 65k tokens at inference time allowing for longer story generations the mosaicml team demonstrated the ability to generate stories as long as 84k tokens on a single node of 8 a100 80gb gpus in their blog post https www mosaicml com blog mpt 7b prerequisites gpu machine you ll need a linux machine with an nvidia gpu attached and the nvidia container toolkit https docs nvidia com datacenter cloud native container toolkit install guide html docker installed if you don t already have access to a machine with a gpu check out our guide to getting a gpu machine https replicate com docs guides get a gpu machine docker you ll be using the cog https github com replicate cog command line tool to build and push a model cog uses docker to create containers for models step 0 install cog first install cog https github com replicate cog install sudo curl o usr local bin cog l https github com replicate cog releases latest download cog uname s uname m sudo chmod x usr local bin cog step 1 set up weights you can use the following script to pull the model weights from the hugging face hub we also recommend using tensorizer to tensorize your weights which will dramatically reduce the time it takes to load your model chmod x scripts download and prepare model py cog run python scripts download and prepare model py model name mosaicml mpt 7b storywriter model path model tensorize tensorizer path model mpt 7b storywriter 65 tensors step 2 run the model you can run the model locally to test it cog predict i prompt on a dark and stormy night step 3 push your model weights to cloud storage if you want to deploy your own cog version of this model we recommend pushing the tensorized weights to a public bucket you can then configure the setup method in predict py to pull the tensorized weights currently we provide boiler plate code for pulling weights from gcp to use the current configuration simply set tensorizer weights path to the public google cloud storage bucket path of your tensorized model weights at setup time they ll be downloaded and loaded into memory alternatively you can implement your own solution using your cloud storage provider of choice to see if the remote weights configuration works you can run the model locally step 4 create a model on replicate go to replicate com create https replicate com create to create a replicate model make sure to specify private to keep the model private step 5 configure the model to run on a100 gpus replicate supports running models on a variety of gpus the default gpu type is a t4 but for best performance you ll want to configure your model to run on an a100 click on the settings tab on your model page scroll down to gpu hardware and select a100 then click save step 6 push the model to replicate log in to replicate cog login push the contents of your current directory to replicate using the model name you specified in step 3 cog push r8 im username modelname learn more about pushing models to replicate https replicate com docs guides push a model | ai |
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traffic_flow_counter | traffic flow counter vertical traffic light introduction hello everyone the following code will be a current work in progress app for traffic flow counting my hope is to make this something of value for my city to be used for traffic flow management this uses the yolo v3 computer vision model to vehicles setup to run the app locally install the necessary python packages by python pip install r requirements txt for better reproducibility make sure to open up a python environment using virtualenv or any of your favorite python environment packages the app contains a custom slider to use it make sure you have npm installed and then run the following commands bash cd components custom slider frontend npm install afterwards run npm run build this should recreate the build package for the custom slider pull the necessary models and data by running make dependencies run the app streamlit run app streamlit app py future developments here are some of my ideas that would be neat additions to the api speed measurement vehicle distribution measurement traffic density | ai |
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2018_Group_14 | 2018 group 14 158 383 information technology project description openstreetmap osm is a collaborative project to create a free editable map of the world rather than the map itself the data generated by the project is considered its primary output the creation and growth of osm has been motivated by restrictions on use or availability of map information across much of the world and the advent of inexpensive portable satellite navigation devices osm is considered a prominent example of volunteered geographic information assignment 1 task one usage system required aws instance net core 2 1 with ubuntu server 18 04 version 1 0 storage 30gb our system does not require net support so although this system has prebuilt net core it still can be seen as a blank instance we just need ubuntu server 18 04 sercurity groups http tcp 80 0 0 0 0 0 postgresql tcp 5432 0 0 0 0 0 ssh tcp 22 0 0 0 0 0 http tcp 443 0 0 0 0 0 to install openstreetmap by default settings run curl https raw githubusercontent com damming mapdata master set up openstreetmap sh bash to install openstreetmap with your own password run bash curl s https raw githubusercontent com damming mapdata master set up openstreetmap with password sh your password for example if your password is 12345678 then run bash curl s https raw githubusercontent com damming mapdata master set up openstreetmap with password sh 12345678 the installation process might be stuck by very a little warnings or some steps need times those are all normal test openstreetmap server is ready when you see these lines the numbers may different renderd 12266 starting stats thread renderd 12266 using web mercator projection settings renderd 12266 using web mercator projection settings renderd 12266 using web mercator projection settings renderd 12266 using web mercator projection settings then open http actual ip osm tiles 0 0 0 png to see if tiles can be rendered you can change the values of 0 0 0 png they are scale x y respectivly or http autual ip ol html to see the relinked online map if you want to see if the password is correctly set press control c to interupt the server process then enter cd to go back to the user root directory then enter vi pgpass then you will see your password after the last colon assignment 1 task two discussion use of management and staging environments in task one we successfully set up a working openstreetmap server that will act as our management server for task two we will use our management server to create duplicate osm servers these duplicate copies of osm can be used as staging environments with the same hardware and software settings for testing and evaluating changes privately by having staging environments that are identical or as close as possible to our production environment we can minimise differences which may cause or hide issues in the deployment of changes as developers we want to minimise the risk of errors being transitioned to our live environments and ensure minimal downtime staging environments allow us to ensure there are no conflicts before making changes live new duplicates of our original production environment can be made quickly should there be issues caused by changes in another staging environment usage install ansible if you are going to rerun the playbook please delete the created keypair in aws console run prepared localhost sh this shell script will install ansible and boto in the current system then a ansible playbook used to create a new aws keypair will be created the new keypair is ssh keypairforansible yem parameters are aws access key id aws secret access key region please have a look at the important below first bash curl s https raw githubusercontent com damming mapdata master prepared localhost sh aws access key id aws secret access key region for example your aws access key id is aaaa and your aws secret access key is bbbb and you want to create the new instance in us west 2 then run bash curl s https raw githubusercontent com damming mapdata master prepared localhost sh aaaa bbbb us west 2 run playbook important if you did not create instance in us west 2 then you need to change the value of image line 33 and reigon line 35 before run the script a feasible way is to edit the file directly in github page and then click raw use the address replace the address below wget c https raw githubusercontent com damming mapdata master prepared new instance yml ansible playbook prepared new instance yml test http autual ip ol html assignment 2 task one decrisption in this task six aws instances are required they are 1 assistant server 1 database server 3 openstreetmap program servers including 1 backup and 1 nginx server only assistant server needs to be setup manually the other servers can be setup by ansible playbook running on the assistant server assistant server can also be used to update program server system required ubuntu server 18 04 lts hvm assistant server needs 8g storage the other servers storage will be set by the playbook sercurity groups assistant server http tcp 80 0 0 0 0 0 postgresql tcp 5432 0 0 0 0 0 ssh tcp 22 0 0 0 0 0 http tcp 443 0 0 0 0 0 the other server will be set by the playbook usage please have a look at the usage of assignment 1 task 2 first setup system setup an assistant server then run bash curl s https raw githubusercontent com damming mapdata master ansible sh aws access key id aws secret access key region the shell script you just ran has installed ansible into assistant server next step is setup all the other servers run wget c https raw githubusercontent com damming mapdata master q2 playbook yml ansible playbook q2 playbook yml this playbook will run quiet a while the system will be ready for using after the playbook is running completely update if you want to update all the program servers in one time run wget c https raw githubusercontent com damming mapdata master update yml ansible playbook update yml if you want to update servers one at a time and see the changes download the update playbook by wget c https raw githubusercontent com damming mapdata master update yml then comment the 26th line and decomment the 27th line the 0 in the 27th line is used to control which server is going to be updated the valid options are 0 1 2 run the following command to execute the playbook ansible playbook update yml test http autual ip of nginx server ol html if you only updated one program server the old version and the new version will appear alternately the log of nginx can be found in var log nginx assignment 2 task two decrisption backup and restore the database usage setup a blank backup server then run bash curl s https raw githubusercontent com damming mapdata master backup sh actual database ip now the backup server will backup the database every 15 minutes you can modify the last line of etc crontab to change the backup rate then delete the database server instance and run the following command on backup server bash curl s https raw githubusercontent com damming mapdata master restore sh retore database ip we highly recommand you just use localhost as the place to restore the database otherwise you need to set up a blank database server first which is a bit complex last reconfigure the map program servers download configure playbook wget c https raw githubusercontent com damming mapdata master change database yml modify database ip in line 35 then run ansible playbook change database yml test http autual ip of nginx server ol html | server |
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trainjs | node on train welcome to node on train npm https nodei co npm trainjs png https nodei co npm trainjs install node on train shell sudo npm install g trainjs update node on train shell sudo npm update g trainjs running tests before you run tests you may need to first install mocha module and jspec module shell sudo npm install g mocha to run the tests shell npm test tutorial step by step guide for getting started http nodeontrain xyz tuts home report an issue please create an issue https github com nodeontrain trainjs issues new or contact us at trainjs https twitter com trainjs license copyright c by ng duy thanh the node on train is license under the terms of the gnu general public license v3 | front_end |
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wine-o.ai | wine o ai computer vision assisted wine recommendations by michelle l gill ph d this is the home of wine o ai http wine o ai a computer vision based wine label search and recommendation application wine o ai uses computer vision natural language processing collaborative filtering and d3 for visualization note under development 07 10 2017 http www sharonkgilbert com wp content uploads 2015 12 under construction 1 150x150 png to do add website code fix bug with responsive design add recommender notebook clean data more hook up aws instance to website re evaluate accuracy as a function of cluster number and augmented data presentation a video http wineoai michellelynngill com presentation wine o ai mlgill m4v and pdf http wineoai michellelynngill com presentation wine o ai mlgill pdf of the presentation slides is available application the web application is under development but you can sign up on the website http wine o ai to receive a notification when the website launches coming soon figures wine o ai sidebyside mlgill png repo contents environment yml list of conda python libraries that were used during analysis figures images used in the presentation notebooks jupyter notebooks used for analysis presentation pdf http wineoai michellelynngill com presentation wine o ai mlgill pdf and video http wineoai michellelynngill com presentation wine o ai mlgill m4v versions of the presentation | ai |
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FreeRTOS-STM32F407-examples | template lib stm32f407 v1 4 0 freertos v9 0 0 template noos keil5 15 stm32f407 template treertos keil5 15 stm32f407 freertos 001 freertos ledtask led examples commonlib 001 freertos ledtask led freertos https github com xxpcb freertos stm32f407 examples blob master pic freertosv9 png | os |
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Hands-On-RTOS-with-Microcontrollers | hands on rtos with microcontrollers hands on rtos with microcontrollers published by packt download a free pdf i if you have already purchased a print or kindle version of this book you can get a drm free pdf version at no cost br simply click on the link to claim your free pdf i p align center a href https packt link free ebook 9781838826734 https packt link free ebook 9781838826734 a p | os |
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plasma-web-ide | plasmadlt quickstart web ide for decentralized applications plasmadlt latest https img shields io badge plasmadlt latest blue svg software license https img shields io badge license mit lightgrey svg license plasmadlt quickstart web ide lets developers start building full stack plasmadlt applications in a matter of minutes powered by gitpod io and docker it provides developers with a personal single node plasmadlt blockchain for development and testing purposes without a need of going through advanced local environment setup it also includes an example application with a smart contract and web frontend connected to the blockchain developers can also use plasmadlt tools like sol and ion cdt straight out of the box this project requires zero installation on the user s machine all code is stored and managed on the developer s personal github account with the changes saved automatically we built this project with ease of use and simplicity in mind it can be used by new developers trying out or learning plasmadlt as well as advanced developers and teams it is especially useful in the environments where users don t have full control over the systems they work on universities banks government organizations etc or when they have lower than required computer specs to run plasmadlt locally we hope you will find this project useful and welcome feedback on future improvements setup 1 fork this repo to your personal github account so that you can save your work into your personal github account 2 point your browser to the following url https gitpod io https github com your github account plasma web ide to start the ide you will be automatically prompted to create a gitpod account all types of gitpod accounts including free will work you can also choose to provide multiple developers push access to your personal github fork of this repo to collaborate with them one developer working on the smart contract c while the other working on the front end decentralized application plasmajs etc each such developer sharing access to the forked repo will get their own copy of the plasmadlt blockchain components to enable independent development you can test drive the system by accessing the ide at https gitpod io https github com plasmadlt plasma web ide however you will not be able to save your work into the plasmadlt plasma web ide github repository instructions the following instructions assume that the web ide was started successfully see setup setup opening a terminal to open a terminal use the terminal drop down menu in the ide user interface building sample contract the source code for the sample smart contract is at contracts talk talk cpp within the ide to compile the contract run this in a terminal cd contracts talk ion cpp talk cpp this will produce talk abi and talk wasm installing the contract run this in a terminal generate contract s account on behalf of ion account ion s account key is already in the wallet sol create account ion talk plasma5sj5yg8h4szwn5sdcnuc8dv7jratwyufrrnumugf9ojseylggr you can ensure that the key is in the wallet with the following command sol wallet keys deploy contract into the just created account sol set contract talk creating local users and using the contract run this in a terminal sol create account ion bob plasma5sj5yg8h4szwn5sdcnuc8dv7jratwyufrrnumugf9ojseylggr sol create account ion jane plasma5sj5yg8h4szwn5sdcnuc8dv7jratwyufrrnumugf9ojseylggr sol push action talk post 1000 0 bob this is a new post p bob sol push action talk post 2000 0 jane this is my first post p jane sol push action talk post 1001 2000 bob replying to your post p bob listing the messages run this in a terminal sol get table talk message viewing the front end decentralized web app plasmajs the source code for the react webapp is at webapp src index tsx within the ide to preview the webapp run this in a terminal gp preview gp url 8000 resetting the chain to remove the existing chain and create another switch to the terminal running ionode press ctrl c to stop it run the following rm rf data ionode config config ini genesis json genesis json data dir data deploying production activate the production account in official wallet plasmapay on the dashboard https app plasmapay com dashboard and decrypt your private keys key icon on the wallet attention you can create only one account in plasmapay and the account s name will be your contract name choice producer from the network from http plasmadlt com monitor setup dapp https app plasmapay com dashboard and get auoth for front end import wallet production sol url http comeric liberty plasmadlt com wallet url http 0 0 0 0 9999 wallet import private key 5jf deploy smart contract sol url http comeric liberty plasmadlt com set contract accountname host share helllloworld p accountname active note if the web app is currently open then it will cause errors like the following you may ignore them fc exception encountered while processing chain get table rows license mit license important see license license for copyright and license terms all repositories and other materials are provided subject to the terms of this important important md notice and you must familiarize yourself with its terms the notice contains important information limitations and restrictions relating to our software publications trademarks third party resources and forward looking statements by accessing any of our repositories and other materials you accept and agree to the terms of the notice | blockchain ide smart-contracts stablecoin payments plasma plasmadlt dapp dapps dapp-example dapps-development dapp-developers smartcontract smartcontract-dapp blockchain-plasmadlt | front_end |
polaris_view_components | polaris viewcomponents polaris viewcomponents is an implementation of the polaris design system using viewcomponent https github com github view component polaris viewcomponents github assets preview png preview https polarisviewcomponents org usage render polaris viewcomponents erb polaris card title title do p card example p end dependencies stimulus https stimulus hotwired dev installation add polaris view components to your gemfile bash bundle add polaris view components run installer bash bin rails polaris view components install development to get started 1 run bundle install 1 run yarn install 1 run bin dev it will open demo app with component previews on localhost 4000 you can change components and they will be updated on page reload component previews located in demo test components previews to run tests bash rake releases the library follows semantic versioning https semver org to draft a new release you need to run script release with a new version number bash bin release version where the version is the version number you want to release this script will update the version in the gem and push it to github and rubygems automatically to release a new version of npm package update the package json file with the new version number and run bash npm run release after that make sure to commit changes in package json license the gem is available as open source under the terms of the mit license https opensource org licenses mit | shopify polaris ruby rails | os |
SwiftSafari | swiftsafari swiftsafari is a projectc that aims to provide an introduction to data science concepts and the swift programming language through building various tools from scratch these tools include neural networks genetic algorithms and more the project is designed to be a follow along project meaning that you can work through the code examples and exercises alongside the accompanying blog posts and videos to get a deeper understanding of the concepts being covered you can find my full tutorials and explanations on my medium blog oceanexplains medium com what is swift safari swift is such a spectacular language easy to learn highly functional open sourced but people too often associate it with ios development and fail to see its potential beyond ios app development to be fair the language most comparable to swift python has such an extensive collection of features and packages that it s hard not to want to dive into all of that with swift you don t get as diverse an ecosystem yet but you do get so much an impossibly accessible user interface package manager and more there are tons of free resources too for learning swift check those out here scroll down i want to help make this language more accessible for data science machine learning and artificial intelligence projects and so i m putting together a project i m calling swift safari where we will be building up all the tools from scratch so that we can gain an intuitive understanding of them if this sounds interesting to you hop on board and get ready to build a virtual world filled with organisms that learn and evolve and watch an ecosystem of your design take you on a developer journey like you d never imagined you can start at the beginning here in this project we will start by building a simple neural network evolutionary algorithm graphic ecosystem and a user interface to wrap it all up this is just the beginning because you will be able to take it even further with your own modifications getting started to get started with swiftsafari you can either follow along with oen of the project tutorials at oceanexplains medium com or you can clone the project you ll need to have either xcode or swift playgrounds installed on your machine xcode is apple s integrated development environment ide for building apps for macos ios and other apple platforms you can download xcode and swift playgrounds for free from the mac app store once you have xcode installed you can clone the swiftsafari repository to your local machine or download the project as a zip file and then unzip it i have included playground projects that correspond to the individual tutorials these are like checkpoints along the road and can be run independently to see what a given implementation looks like the xcode project is where i do my active development and i am still learning version control with github so please be patient thanks contributing contributions to swiftsafari are welcome and encouraged if you notice a bug have an idea for a new feature or want to improve the documentation feel free to open an issue or submit a pull request i really just want to ghelp grease the gears and get swift chugging along the data science train license swiftsafari is licensed under the chicken dance license license is included in the project folder entitled license in short engage your inner chicken because it s time to dance dance instructions are located in the license folder in file entitled dance | data-science swift swift-tutorials follow-along-projects swift-data-science | os |
design-system | salesforce lightning design system build status https travis ci org salesforce ux design system svg branch master https travis ci org salesforce ux design system dependabot status https api dependabot com badges status host github repo salesforce ux design system internal identifier 41938205 https dependabot com welcome to the source code repository for salesforce lightning design system http getslds com brought to you by salesforce ux https twitter com salesforceux slds is tailored for building salesforce apps using the lightning design system markup and css framework results in uis that reflect the salesforce lightning look and feel continuously updated as long as you re using the latest version of the lightning design system your pages are always up to date with salesforce ui changes getting started this project utilizes storybook for component development if you would like to know more about storybook or how it works check out their website https storybook js org project installation setup 1 clone the repository down locally 2 cd into the project and run npm install to install all project dependencies running the development environment the storybook development environment can be started by running npm start whenever you add remove or alter a component s css annotation metadata you ll need to restart storybook to see those changes configuring node and nvm node v14 is recommended for use with the design system repository and nvm http nvm sh is the recommended choice for managing multiple versions of node on your computer a nvmrc file is included in this project to aid in local development to utilize it for setting your project s node version run nvm use in the root of the directory additionally you can set up a deeper shell integration for automatically invoking the nvmrc file when you change into the project directory by following these instructions https github com nvm sh nvm deeper shell integration developing in storybook once the development server is started with npm start you can load it at http localhost 9002 http localhost 9002 annotations see the annotations guide guidelines annotations md tasks npm start starts the storybook server for local development npm run gulp lint lint the code base for syntax and stylistic errors lint indentation sass javascript files npm run gulp lint lint languages independently npm run gulp lint sass npm run gulp lint javascript npm run gulp lint javascript test npm run gulp lint spaces npm run gulp lint html html5 validation npm run gulp lint vnu html5 validation on comma separated blueprint names npm run gulp lint vnu components button path trees a11y validation npm run gulp lint a11y a11y validation on comma separated blueprint names npm run gulp lint a11y components button path trees lint examples using vnu axe slds validation and html5 validation npm run gulp lint examples pull request checks to run all the checks a pull request will run in travis use the following command to run every check against all blueprints npm run pr checks to run every check but target certain blueprints for slow checks like axe and vnu npm run pr checks components button path trees compilation npm run build dist generate the lightning design system into the dist directory npm run gulp styles compile sass to css into assets styles npm run gulp clean delete temporary build and local files stats npm run gulp styles stats useful stats about the project s deliverables tests npm test run all tests except axe a11y tests npm run test a11y run axe tests for accessibility violations results are saved into tests a11y results release npm release site build and release the framework and site requires heroku access to build and release the site troubleshooting see the troubleshooting guide guidelines troubleshooting md contributing back to slds see the contributing guide contributing md licenses source code is licensed under bsd 3 clause https git io sfdc license all icons and images are licensed under creative commons attribution noderivatives 4 0 https github com salesforce ux licenses blob master license icons images txt got feedback please open a new github issue https github com salesforce ux design system issues | css salesforce-lightning design-systems html | os |
TWAIN-SDK | twain protocol introduction twain full name technology without an interesting name is an applications programming interface api and communications protocol that regulates communication between software and digital imaging devices such as image scanners and digital cameras twain is not a hardware level protocol it requires a driver called data source for each device provide multiple platform support maintain and distribute a no charge developer s toolkit ensure ease of implementation encourage widespread adoption open source data source manager multiple images format support twain is not a hardware level protocol it requires a driver mysteriously called a data source or ds for each imaging device when a device is advertised as twain compatible this simply means the device has a twain ds driver available for it twain is available at this time march 2007 on all 32 bit intel versions of microsoft windows and on apple os x note that dosadi does not support apple products or os x development the twain manager or dsm is provided for free by the twain working group it acts as liason and coordinator between twain applications and data sources the dsm has minimal user interface just the select source dialog all user interaction outside of the application is handled by the data source each data source is basically a high level device driver provided by the device manufacturer the twain working group does not enforce compliance with the twain standard twain compliance and compliance testing are voluntary and left up to application and ds developers the twain manager and the data source are dlls so they load into the application s memory space and run essentially as subroutines of the application the dsm uses interprocess communication to coordinate with other instances of itself when more than one application uses twain much simplified the steps of an application using twain are 1 open a device and have a conversation with the device actually the ds about the capabilities and settings of the device there is a huge list of capabilities every device implements a different set but for example most devices can list the resolutions they support and most will allow an application to select a resolution for subsequent images 2 enable a device which in twain terms means give the device permission to deliver images most scanners when enabled display their user interface and allow the user to adjust scan settings eventually hitting a scan button to actually start the scan the application can request that a ds not display a user interface but some devices ignore the request and show their dialog anyway this is a common cause of surprise and frustration for twain application developers 3 once a device is enabled the application waits for a notification from the ds that an image is ready while it waits the application must somehow ensure that any messages posted to it are routed through twain unless this is done correctly the application will never receive the image ready notification and the device s user interface may not work correctly 4 the application accepts the image from the ds twain defines three modes of image transfer native on windows this is a dib device independent bitmap in memory note that windows has two kinds of bitmaps memory strips or blocks of pixels in a series of memory buffers file the ds writes the image out directly to a file a ds is not required to support this mode 5 if appropriate the application may transfer multiple images until it chooses to stop or until the ds signals that no more images are available 6 the application normally then disables the ds and closes it in symmetry with the open enable steps we started with eztwain eztwain sits between the application and the twain dsm hiding the complexity of the twain api from the rest of the application with eztwain twain is still needed all the twain parts play their usual roles to the application eztwain presents a simplified version of the twain api plus additional features that are useful to scanning applications such as image file loading and saving eztwain relieves the application of the chore of routing all windows messages through twain as needed and of waiting for and reacting to the image ready notification https zh wikipedia org wiki twain https zh wikipedia org wiki twain https zh wikipedia org wiki twain twain stucture layout https github com mrlitong twain sdk blob master source twain layout jpg application todo source manager in this figure we can see that source manager plays a very important role as a bridge between application and source through the unified entry function dsm entry we can transfer messages between application and source to achieve the purpose of communication the communication between the source manager and the source is done through ds entry the developer doesn t have to worry about how this function is called source manager can automatically detect the installed image device on the user s computer and can load the device as needed source twain core module a dll file provided by the device manufacturer this dll and twain interface remain unified but different manufacturers are not exactly the same developers need to perform logical judgments and other verifications at the application layer this component is dedicated to solving this problem twain sdk twain sdk provides a unified developer interface for applications that supports the following scanner models canon cr 1xx series 3xx series 6xx series d12xx series fs27xx series fb63xx series panasonic kv s50xx series kv s20xx series kodak i30xx series i26xx series fujitsu unislan epson developers do not need to care about hardware differences or interface differences between different scanners guide 1 get twain pointer based on os c dsmentryproc lpdsm entry dsm entry pointer hmodule hdsmdll twain 32 dll handle if hdsmdll loadlibrary twain 32 dll null if lpdsm entry dsmentryproc getprocaddress hdsmdll makeintresource 1 null all below operation based on this pointer 2 open source manager c int ctwain opensourcemanager void tw uint16 rc hpwnd is the handler of the parent s windows of source rc lpdsm entry appid null dg control dat parent msg opendsm tw memref hpwnd switch rc check if source manager is prepared case twrc success done case twrc cancel 3 open source c int ctwain opensource void tw uint16 rc rc lpdsm entry appid null dg control dat identity msg opends tw memref sourceid switch rc case twrc success done 4 handle event of source c int ctwain dealsourcemsg msg pmsg tw uint16 rc twrc notdsevent tw event twevent twevent pevent tw memref pmsg rc lpdsm entry appid sourceid dg control dat event msg processevent tw memref twevent switch twevent twmessage case msg xferready istatus 6 istatus 6 getbmpinfo donativetransfer case msg closedsreq close case msg closedsok case msg null 5 data transport c int ctwain donativetransfer void tw uint32 hbitmap null pointing to address of image data tw uint16 rc handle hbm acq null rc lpdsm entry appid sourceid dg image dat imagenativexfer msg get tw memref hbitmap switch rc case twrc xferdone hbm acq hbitmap hbitmap sendmessage hpwnd pm xferdone wparam hbm acq 0 istatus 7 break case twrc cancel case twrc failure 6 handle image data c lresult ctwainappview windowproc uint message wparam wparam lparam lparam if message pm xferdone recieve pm xferdone message hbitmap hbmp fixup handle wparam image transform handling bitmap pbm 0 gdi object pbmp pbm fromhbitmap hbmp hdibpal invalidate return cview windowproc message wparam lparam | twain sdk cross-platform | front_end |
INFO-F-410_project | info f 410 project light and temperature control system with a web server on a wemos d1 using platformio for building and pushing on the board push the code to the wemos platformio run target upload connect to the webserver connect to the wifi hello iot with password 12345678 the interface is accessible at the address http 192 168 4 1 | os |
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o1heap | o1heap o1heap is a highly deterministic constant complexity memory allocator designed for hard real time high integrity embedded systems the name stands for o 1 heap this rust implementation is closely based on pavel kirienko s original c implementation https github com pavel kirienko o1heap i only translated it into rust please see the readme there for details about how this allocator works license mit license see license txt the original c implementation is also mit licensed copyright c 2020 pavel kirienko permission is hereby granted free of charge to any person obtaining a copy of this software and associated documentation files the software to deal in the software without restriction including without limitation the rights to use copy modify merge publish distribute sublicense and or sell copies of the software and to permit persons to whom the software is furnished to do so subject to the following conditions the above copyright notice and this permission notice shall be included in all copies or substantial portions of the software | os |
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how-to-build-your-own-blockchain | how to build your own blockchain in this repository you ll find the source code and material of our first how to build your own blockchain https www facebook com events 541216486228386 event you can find the slides of the talk here how to build your own blockchain slides https www slideshare net leonidbeder how to build your own blockchain how to build your own blockchain images event png blockchain academy blockchain academy the community for technologists looking to learn more about crypto and blockchain technology so you re interested in blockchain if you came to this page it probably means that despite the hundreds of events groups and pages you have yet to find one entity that caters to your blockchain needs if crypto trading advice and strategy is what you re into or if high level sessions that will provide you with buzzwords but not much else please continue your search however if you re a blockchain professional that is interested in an active and productive discussion with other blockchain professionals or if you re a top notch backend cloud cyber fintech professional that is actively looking to get a running start into a new and exciting technological field this is the place for you blockchain academy was founded by top tier professionals that have been actively working with and in blockchain technology for years in order to provide those who use it in practice a home and a framework to help each other grow and help applicable newcomers learn the basics and a lot more in this case only those who can and do will teach license mit license | blockchain |
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NDK_Engine | ndk engine synopsis this project is a simple android mobile oriented 3d opengl es 2 0 based game engine developed inside of the android native development kit written primarily in c this engine was written specifically for a game this is why no general 3d physics engine is included and why other common game engine features are missing i e a particle system lighting shadow rendering graphical features skeletal 3d animations parenting objects to skeletal animation bones i e parenting the camera to a head bone for first person animations custom glsl shader material support skybox rendering support sound features supports 3d stereo r l volume panning i e sounds playing from a source nearby on the camera s left hand side will be played through the left speaker supports 3d audio falloff i e sounds playing further away are quieter than nearby sounds mobile specific features includes jni java native interface support this allows you to create java code snippets and execute them from within the c game code meant for implementing in app purchases mobile banner ad support achieved through jni this allows a banner ad to be overlayed on top of the opengl game view banner ad can be made visible hidden from within the engine c code technical details utilizes opengl es 2 utilizes opensl for sound engine custom skeletal animation format skaf custom skeleton structure format sksf custom skeletal model format skmf allows each vertex to have up to 3 bone weight influences 1 set of uv coordinates vertex normals tangents and binormals custom static model format stmf allows each vertex to have 2 sets of uv coordinates one meant for a diffuse texture the other meant for a lightmap texture atlas vertex normals tangents and binormals utilizes etc1 compressed texture format pkm this allows me to simply pass along the image data directly to the gpu without the need for modification the tradeoff is that this format only supports rgb channels and has some slight compression artifacts utilizes raw headerless sound format raw 16 bit depth stereo files at 44100 hz | front_end |
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SMQ | smq c client library the smq c client library for microcontrollers and computers includes porting layers for many rtos environments and bare metal smq based on the publish subscribe pattern provides features similar to other pub sub protocols such as mqtt however smq extends the pub sub pattern with additional features such as one to one messaging and sender s address which are typically required in device management smq iot protocol https makoserver net gz images smq iot broker svg see the following for details smq home page https realtimelogic com products simplemq smq documentation https realtimelogic com ba doc url smq html smq c client api https realtimelogic com ba doc en c reference html group smqclient html this repository includes the standard smq c client library and introductory examples recommended for anyone new to the smq protocol smq c c examples the following examples are listed in the recommended study order 1 the two introductory 1 introductory smq examples examples publish cpp and subscribe cpp are recommended for any c or c developer new to the smq protocol 2 the light bulb example 2 light bulb example is the companion example for an online tutorial 3 the iot example led smq c 3 smq iot example is the companion example for an online tutorial 1 introductory smq examples the two introductory examples publish cpp examples publish cpp and subscribe cpp examples subscribe cpp use the c api which is slightly easier to use than the c api a recommendation is to initially read the introduction to the c and c api concept https realtimelogic com ba doc url introduction html oo c the examples require the json library the following shows how to fetch the two repositories and how to compile all examples on linux shell sudo apt install g gcc make git git clone https github com realtimelogic json git git clone https github com realtimelogic smq git cd smq make windows users compile and run the examples using the project files in vcmake the publish and subscribe examples require an smq broker running on the same computer run the broker as follows download the pre compiled mako server https makoserver net download overview for your platform and unpack the archive copy the two files mako exe and mako zip to this directory start the broker as follows linux shell sudo mako u whoami l broker windows shell mako l broker the file broker preload broker preload will now be loaded by the mako server and you will see several lines being printed including the following shell server listening on ipv6 port 80 server listening on ipv4 port 80 loading certificate makoserver sharkssl server listening on ipv6 port 443 sharkssl server listening on ipv4 port 443 creating broker registering topic example struct a with tid 2 registering topic example struct b with tid 3 registering topic example jstruct a with tid 4 registering topic example json array with tid 5 for your c program define example struct a 2 define example struct b 3 define example jstruct a 4 define example json array 5 as shown above the server is listening on port 80 if the server is not listening on port 80 open the two examples publish cpp and subscribe cpp in an editor change the port number macro closer to the top of the two files to the port number used by the mako server and recompile the examples start the publisher and subscriber examples in separate terminal windows the publisher publishes data and the subscriber consumes data see the following short video for details on running the example bundle https youtu be yqjbwq2pzvm simplified c c design the two c examples highlight several features that simplify designing c c applications using the smq protocol the smq protocol registers topics by name https realtimelogic com ba doc url smq html topicnames but translates the names to topic ids tids in this example setup the smq broker initialization in the script broker preload broker preload pre registers all topics used and forces the smq broker to use static tids instead of dynamic tids this construction simplifies the c code which would otherwise have to keep track of dynamically registered tids the smq payload can be anything from binary data to json the two examples show how one can send c structures as binary data between two c programs this construction works as long as the two c programs are compiled for the same architecture and alignment json simplifies sending structured messages between different architectures and computer languages most json libraries operate on complete messages which can be problematic in an embedded system if the json payload is large the two examples show how to send and receive complete messages but also how to send json messages in chunks and how to parse the received json messages in chunks the mako server printouts shown above include define directives these are already included in the two example programs the macro names correspond to the topic name string and the numbers are the topic id tid enforced by the broker preload broker preload lua script topic example struct a tid 2 payload is examplestructa see examples examplestruct h examples examplestruct h topic example struct b tid 3 payload is examplestructb see examplestruct h topic example jstruct a tid 4 payload is json which is sent and received as one chunk the payload is a json representation of examplestructa topic example json array tid 5 payload is json which is sent and received as multiple chunks the payload is an array of json object representations of examplestructa json library the json library https github com realtimelogic json used by the examples is fairly unique in that it provides some interesting features for encoding and decoding json in resource constrained embedded devices a recommendation is to read the json tutorial https realtimelogic com ba doc en c reference html md en c md json html prior to looking at the source code using json with real time iot communication https realtimelogic com gz images json iot svg 2 light bulb example the light bulb example is the companion example for the tutorial modern approach to embedding a web server in a device https realtimelogic com articles modern approach to embedding a web server in a device two identical examples are provided bulb c examples bulb c and bulb cpp examples bulb cpp you can compare the two examples which makes it easy to see the difference between the c and c api the light bulb connects to our public smq test broker https simplemq com you also need the companion javascript code https github com realtimelogic lsp examples tree master smq examples lightswitch and lightbulb app when testing this example start the light bulb example as follows shell bulb the following screenshot shows how to compile and run the example how to compile and run the iot light bulb example https realtimelogic com blogmedia modernapproachembeddedwebserver bulb c code png when you have initially tested the c code and the javascript code with the public test broker change the url in all code to your own private broker the broker you set up in example 1 1 introductory smq examples 3 smq iot example the iot example shows how one can use the smq protocol to design a complete iot solution the following video shows how to use the iot example smq iot example https img youtube com vi r8sjfdyspsm mqdefault jpg https youtu be r8sjfdyspsm the iot example led smq c is a copy of the smq example from sharkssl https github com realtimelogic sharkssl the example can use the secure sharkmq library or the standard smq library the example is using a tls connection when compiled with sharkmq and a standard tcp ip connection when compiled with smq smq api documentation https realtimelogic com ba doc en c reference html group smqclient html sharkmq api documentation https realtimelogic com ba doc en c shark structsharkmq html the standard smq stack includes a compatibility api that enables programs using the sharkmq api to be compiled with the standard smq stack how to run the iot example linux see the above linux build instructions start led smq in a terminal window windows compile and run the example using the project files in vcmake embedded systems see instructions below build instructions for embedded systems the example code led smq c requires porting to your embedded board s led s see the tutorial interfacing led demo programs to hardware https realtimelogic com ba doc en c shark md md examples html leddemo for details see the src arch src arch directory for smq porting layer details ready to run embedded examples the sharkssl esp32 ide https realtimelogic com downloads sharkssl esp32 includes ready to use led interface code for the esp32 you can also download the iot example for arduino https realtimelogic com downloads smq smq arduino zip tl dr iot solution quickstart set up your own iot solution as follows 1 download and compile the example code as is the example when run connects to the online test broker https simplemq com m2m led 2 familiarize yourself with how the example works 3 follow the setting up an environmentally friendly iot solution https makoserver net articles setting up a low cost smq iot broker tutorial for how to set up your own iot solution 4 modify the example code examples led smq c and change the domain url smq domain the url should be set to your own iot server smq license the source code in this repository is released under the eclipse public license v 2 0 https www eclipse org legal epl v20 html https www eclipse org legal epl v20 html you may compile a program licensed under the epl without modification and commercially license the result in accordance with the terms of the epl https www eclipse org legal epl 2 0 faq php this source code may also be made available under the following secondary licenses when the conditions for such availability set forth in the eclipse public license v 2 0 are satisfied gnu general public license version 2 | os |
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fastcgipp | fastcgi author eddie carle version 3 1alpha news october 12 2018 postgresql functionality is now complete and i m really hoping to get people testing and giving feedback as soon as possible i m pretty proud of this particular iteration at integrating database functionality into fastcgi so go easy on me check out the example 15 unit test 16 and reference documentation 17 for further details april 5 2018 it s been long enough 3 0 is now official and marked stable may 28 2016 some good examples are now done and in the documentation i ve got said documentation hosted online now so check it out 13 may 18 2016 the re write is now effectively complete what i mean by this is that the library now builds and passes some basic benchmarking tests i m really hoping to get as much feedback as possible so please test away the docs are not web hosted anywhere yet so you ll have to build them yourself as described below note that the only example tutorial that works so far is the helloworld one april 10 2016 fastcgi is going through a dramatic rewrite now and the master branch does not work at all if you re here hoping for a functional version scroll down to the releases section if you d like to read a bit more about the rewrite and fastcgi in general check out ten years of fastcgi 1 1 https eddie isatec ca 2016 04 10 ten years of fastcgi html 15 https fastcgipp isatec ca sql html 16 https github com eddic fastcgipp blob master tests sql cpp 17 https fastcgipp isatec ca namespacefastcgipp 1 1sql html about this library is intended as a high efficiency c 20 api for web development it allows your applications to communicate with web servers through the fastcgi protocol tabulates all your environment data manages character encoding and allows requests to effectively share cpu time if you want any further information check the doxygen documentation associated with the respective release or build it yourself be sure to read through the examples releases your best bet for releases and documentation is to clone the git repository checkout the tag you want and see the building section of either this file or the doxygen documentation if you re too lazy for that however you can take the risk and try the following links fastcgipp 3 0 tar gz 12 documentation 13 tree 14 fastcgi 2 1 tar bz2 2 documentation 3 tree 10 fastcgi 2 0 tar bz2 4 documentation 5 tree 11 fastcgi 1 2 tar bz2 6 documentation 7 fastcgi 1 1 tar bz2 8 fastcgi 1 0 tar bz2 9 2 http download savannah nongnu org releases fastcgipp fastcgi 2 1 tar bz2 3 http www nongnu org fastcgipp doc 2 1 4 http download savannah nongnu org releases fastcgipp fastcgi 2 0 tar bz2 5 http www nongnu org fastcgipp doc 2 0 6 http download savannah nongnu org releases fastcgipp fastcgi 1 2 tar bz2 7 http www nongnu org fastcgipp doc 1 2 8 http download savannah nongnu org releases fastcgipp fastcgi 1 1 tar bz2 9 http download savannah nongnu org releases fastcgipp fastcgi 1 0 tar bz2 10 https github com eddic fastcgipp tree 2 1 11 https github com eddic fastcgipp tree 2 0 12 https github com eddic fastcgipp archive 3 0 tar gz 13 https fastcgipp isatec ca 14 https github com eddic fastcgipp tree 3 0 building this should provide you with all the basic stuff you need to do to get fastcgi built and installed the build system is cmake and the following instructions assume you are in bash first we need to clone git clone https github com eddic fastcgipp git fastcgi then we make a build directory mkdir fastcgi build cd fastcgi build now we need run cmake note that the install prefix is being explicitly set to usr because most server spawned fastcgi applications lack the usr local library directories in the search path cmake dcmake install prefix path usr dcmake build type release fastcgi and if we want to build the postgresql stuff we need to actually make it do so cmake dcmake install prefix path usr dcmake build type release dsql true fastcgi note that that was to do a release build that means heavily optimized and not good for debugging if you want to do some debugging to either fastcgi or an application you are developing that uses fastcgi do a debug build cmake dcmake install prefix path usr dcmake build type debug fastcgi or if you want some really hardcore debug and diagnostics info cmake dcmake install prefix path usr dcmake build type debug d log level int 4 fastcgi now let s build the library itself make then we can build the documentation if we so desire make doc now let s install it all doc included if it was built sudo make install maybe we should build the unit tests make tests and of course we should run them as well make test and hey let s build the examples too make examples | fastcgi api web | front_end |
WeBall_Statistics | weball statistics h4 the weball statistics application is a league statistics application for basketball which was created as part of the course apps development for mobile devices university of macedonia applied informatics academic year 2021 2022 6th semester h4 h4 part of the course was to get organized into groups of 10 people our team team 2 consists of the following students alphabetically h4 ul li b i ampatzidou elisavet i b li li b i charakopoulos minas theodoros i b li li b i dasyra evmorfia elpida i b li li b i iordanou sofia i b li li b i lougaris dionisis i b li li b i lousta aravella i b li li b i machairas panagiotis i b li li b i ouzounidis kyriakos i b li li b i pepa leonard i b li li b i stefou george john i b li ul h4 video presentation of the app on youtube a href https www youtube com watch v ouzmwkucq s list ll index 12 b i presentation video i b a h4 h4 visit the other repository with the back end of our application a href https github com uom android team2 weball statistics backend b i back end i b a h4 h2 r1 nbsp nbsp display matches admin login guest starting page h2 div float left img src screenshots r1 start page png height 450 img src screenshots r1 admin login png height 450 img src screenshots r1 upcoming matches admin view before start png height 450 div br p b i requirement 1 i b is handled by the administrator admin and it concerns the match selection and manage the card of the selected match this includes the appearance of players and the corresponding ones logos first the administrator must enter the username and password in the form is requested after choosing the button login as admin the admin account can created by the backend website through it register it then goes to the matches screen where there are three columns with the corresponding matches previous matches live matches upcoming matches from there the administrator can choose a match and edit the tab of more specifically by pressing it arrow a popup appears menu which includes the players of the groups with the edit button is transferred to the welcome admin screen where it is match management see r2 br note the edit option concerns only the live and upcoming matches not the completed p h2 r2 nbsp nbsp match management by admin h2 div float left img src screenshots r2 admin live match panel png height 450 img src screenshots r2 live match admin png height 450 img src screenshots r2 pop add points png height 450 div br p b i requirement 2 i b constitutes the next possibility of the administrator admin which includes all functions related to managing a match shoot with type and result rebound or assist or block steal turnover and foul necessary condition for starting the game but also to activate the buttons it is to click the button start after it s click the same button turns into end through which the match could be terminated in addition the administrator can stop the timer and start it from where you stopped it via the pause button the which turns into continue when pressed and vice versa still for registering any action it is necessary the administrator to follow a series of steps initially the administrator during his navigation on this screen sees the home team selected by default to if he can change team he uses the banner of which located at the top as an image once he selects any from the 2 teams the key players of the selected team appear at the bottom of the screen in the same way that the team is selected a player can also be selected that is by clicking on his image br note the match does not end when done is pressed only will paused and the admin will moved back to all matches p h2 r3 nbsp nbsp recording statistics h2 p this particular requirement deals with calculating stats for players and the groups when the administrator performs a corresponding action these actions include the basic events that occur in a match basketball skills such as free throws and attempts two pointers three pointers in addition assists rebounds steals cuts fouls are also recorded and mistakes the specific statistics are recorded in the database at the moment which the administrator presses a similar button from its graphical interface which is fragment admins view statistics recording can begin the moment a match is live for something like this to happen it is necessary o administrator to press the start button from its graphical interface on the contrary if the administrator seeks to increase statistics for a player team respectively buttons will be disabled beyond the simple recording of statistics n application modifies the above data into a more logical form for the user specifically in the frontend a percentage calculation is also carried out through a condition to if the application succeeds in the specific process it stores its data in classes statistics for players and teams from the database p h2 r4 nbsp nbsp watch the progress of the live match h2 div float left img src screenshots r4 live progress 1 png height 450 img src screenshots r4 live progress 2 png height 450 img src screenshots r4 live comments 1 png height 450 div br p the purpose of implementing b i requirement 4 i b is that users as well as match administrators admins can watch the progression of a live match in real time through verbal descriptions and comments for more details in order to watch the progress of a live match one must first choose one from the list of live matches live matches by clicking anywhere on its layout thus it will be transferred to a new screen where the 2 teams the current score the match week as well as the current minutes of the match are shown above below is a menu available where gives the opportunity to watch the match through brief descriptions by selecting the progress tab as well as through comments and more detailed descriptions by pressing the comments tab he can also see the statistics of the teams and the respective players by going to the statistics tab r5 br br about the b i progress i b tab short descriptions are displayed for actions registered by the admin and performed in the match such as the following p ul li start complete pause and resume of the match li li successful freethrow 2 point and 3 point li li rebound li li steal li li the name of the player who made the assist in parentheses only for 2 points or 3 points li li block li li foul li li turnover li li player substitution li ul p about the b i comments i b tab all actions previously mentioned in the progress tab are described in the form of comments with the extra addition of the display of missed free throws 2 points and 3 points p p left aligned descriptions refer to the home team right aligned to the away team and in the center there are descriptions generally related to the flow of the match without specifically addressing any team p p b note b b i all descriptions are realtime and no refresh is required to display the newest events each new action will appear on top first at the beginning also the score and the time shown in the header of the match are realtime and directly obey the actions of the admin i b p h4 for the implementation of the real time data the possibility of the real time database offered by the a href https firebase google com firebase a platform was utilized h4 h2 r5 nbsp nbsp watch the statistics of the live match both for teams and players h2 div float left img src screenshots r5 live team statistics png height 450 img src screenshots r5 live players statistics 1 png height 450 img src screenshots r5 live players statistics 2 png height 450 div br p b i requirement 5 i b will give the opportunity to the user to watch live stats of a match as it is live the user having selected a live match has the possibility to see the relevant statistics of the teams from the last column of the live game screen here again the elements on the left side of the screen represent the home team while the elements on the right represent the away team in addition the bars visually show the statistics of the teams by category i successful effort total effort successful freethrow total freethrow successful twopointer total twopointer successful threepointer total threepointer steal assist block rebound foul turnover i while the number above each bar indicates the total number of attempts successful shots etc the view players live statistics button at the bottom of the screen refers the user to the individual player statistics by category again the team s overall data e g total effort is displayed on the right and the number representing each player on the left the bar again indicates the corresponding percentage additionally the user can select the player from the bottom of the screen or change team from the pop up menu on the top left of the screen p p b note b b i firebase was used to record and store the data so that the comments of each match are always updated without the need for further action by the user e g refreshing the page i b p h2 r6 nbsp nbsp statistics of completed matches h2 div float left img src screenshots r6 completed match statistics 1 png height 450 img src screenshots r6 completed match statistics 2 png height 450 img src screenshots r6 completed match statistics 3 png height 450 div br p b i requirement 6 i b will offer the user the option to view the stats of a completed match from the user s home match screen and the previous matches column the user can select a completed match to view its statistics in more detail after selecting one the individual statistics of the five most efficient players of each team are displayed and below a list of the leading players in the specific statistics for the selected match the following are the total statistics of the two teams per category i team efficiency 3 pointers made 2 pointers made total freethrows team assists total fouls 10 i the left side is for the home team while the right side is for the away team p h2 r7 nbsp nbsp league scoreboard h2 div float left img src screenshots r7 score board png height 450 div br p in b i requirement 7 i b the scores of all the teams will be presented after they have completed the match in which they are participating more specifically the user goes to the scoreboard screen from the championship leaderboard button located on the home screen this screen shows the teams sorted according to their score pts to the left of the columns is the position number of each team followed by the team name total games played so far gm wins w and losses l respectively and finally the points scored have collected pts points are calculated as the sum of wins times 2 and losses additionally there are two buttons on this screen the statistics button which leads to team and player statistics and the top 5 button which leads to the best 5 players regardless of team p h2 r8 nbsp nbsp overall team stats h2 div float left img src screenshots r8 team stats all time png height 450 div br p in b i requirement 8 i b the total statistics of the teams will be displayed the user from the statistics button of requirement 7 goes to the championship statistics screen which has two tabs the second tab team stats related to r8 contains four tables per category in each table the five teams with the highest percentages per category i points per game assists per game rebounds per game blocks per game up to the given moment in the league i are shown for example in points per game the user can see the top five teams that collected the most points per game p h2 r9 nbsp nbsp personal player stats h2 div float left img src screenshots r9 top players all time png height 450 div br p in b i requirement 9 i b the personal statistics of the players throughout the league are displayed the statistics button of requirement 7 navigates the user to the championship statistics screen which has two tabs the first tab on the left players stats corresponds to requirement 9 and concerns the statistics of the players by category i points per game assists per game rebounds per game blocks per game fouls per game i i e how many points rebounds assists etc collected by the respective player per game up to the given moment in the league in each category the 5 players who collected the highest percentages per category in the matches they have participated in so far are displayed these statistics are updated as the match progresses p h2 r10 nbsp nbsp top 5 players for each week h2 div float left img src screenshots r10 top5 per week png height 450 div br p in b i requirement 10 i b the best 5 of the competition are calculated based on the evaluation system efficiency meter by pressing the button top 5 the user enters the page and displays the 5 best players of the matchday last matchday current week according to the position in which they play for the selection of the top five the statistics of all players who participated in the completed matches of the current week are gathered the efficiency index of each player is calculated and then these indices are compared between players of the same position the player with the greatest efficiency emerges as the best of the week for the position he plays in addition the data of the 5 best players is displayed in a frame with a background color that dominates the team they play p prerequisites ul li android studio li li xampp control panel li li an emulator installed e g nexus 5 api 30 pixel 3 xl api 29 li li internet connection li ul local installation h4 for the correct use of the application the following actions are required h4 run at first the back end git clone https github com uom android team2 weball statistics backend git or download the zip from github and extract it store or move the root folder weball statistics backend master in path xampp htdocs folder open xampp control panel and start apache and mysql servers visit from your browser http localhost weball statistics backend index then register or login and follow the manual now for the mobile application git clone https github com uom android team2 weball statistics git or download the zip from github and extract it store or move the root folder weball statistics main in path androidstudioprojects open android studio and the app root folder config the app public static final string ip your ip java uom team2 weball statistics configuration config java domain includesubdomains true your ip domain res xml network security config xml start any emulator and then you are ready to launch the app h4 note maybe you will see already data for live matches because of the real time cloud service was used firebase real time database h4 | 6th-semester android android-app android-development android-studio basketball-stats firebase-realtime-database java mysql-database postman realtime-database statistics xampp applied-informatics uom | front_end |
PyPagekite | pagekite py this is pagekite py a fast and reliable tool to make localhost servers visible to the public internet for stable releases and quick start instructions please see https pagekite net downloads the full manual is in the docs folder or visible on line here https github com pagekite pypagekite tree main doc note this program is under active development and the contents of this repository may at times be somewhat unstable stable source releases are archived here https pagekite net pk src | front_end |
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Chem_LLM_Hackathon | welcome to the 2023 chemistry digifab hackathon challenge 1 retrosynthesis prediction in this challenge you will be given a set of molecules and their corresponding retrosynthesis your task is to build a model that can predict the retrosynthesis of new molecules in this challenge the goal is to compare the performance of more tailored language models the molecular transformer https github com pschwllr moleculartransformer and more general language models gpt 3 for the specific task of retrosyntyhesis prediciton the starting point for this task is in the task 1 folder challenge 2 large language models for general science in this afternoon task the goal is to evaluate the performance of large language models llms at answering specific exam questions the starting point is the knowledge extraction notebook https github com stevenkbennett chem llm hackathon blob main task 2 knowledge extraction notebook ipynb in the task 2 folder using the automated scoring your progress on the challenges will be monitored using the automated scoring system the general idea is to submit a pull request containing your best predictions the scores will be calculated automatically and uploaded as a comment on your pull request you can submit multiple predictions and track the progress of your scores over time the detailed instructions for using the scoring system are as follows 1 navigate to the hackathon github page https github com stevenkbennett chem llm hackathon 2 please speak to one of the demonstrators who will add you to the repository you will need to do this before submitting files 3 click add file then upload files 4 select create a new branch and click propose changes 5 click create pull request your automated scores will become available after a few minutes 6 to submit new test files just upload them again using the add file button with the same branch name and the scores will be recalculated tracking progress each task is worth 45 points each and a further 10 points will be allocated by the judges at the end of the hackathon each of the scores can be seen in the pull requests and on the leaderboard that will be on the screen during the day | ai |
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debugging-practice | introduction to debugging introduction this repository contains the starter files for the introduction to debugging exercise as part of this exercise you will debug a simple browser based card matching game the html css and javascript code that makes up the game has been provided however it s a bit buggy rules the game is intended to work as follows the user is presented with a selection of 3 pairs of cards for a total of 6 cards each pair of cards features a matching symbol all of the cards are displayed face down meaning that the symbols are not visible the user will select two cards one at a time when a card is selected it will be flipped face up meaning that the symbol will be displayed if the symbols match the cards will remain face up if the symbols do not match the cards will be flipped face down this continues until the user has matched all 6 cards when all 6 cards have been matched a message is displayed and the game ends bonus features users are able to change the colour of the cards by adding any one of the following values to the end of the url green red orange defects our users have reported the following problems i am able to select more than 2 cards cards do not seem to be compared matched correctly the cards are never flipped face down regardless of whether or not they match the game does not end even after all the cards have been matched additionally adding the green red or orange values to the url and then refreshing the page does not update the colour of the cards approach debug and fix each defect in order if possible introduce each fix as a separate commit focus on debugging the rules part 1 before moving on to the bonus features part 2 please review the accompanying class materials for additional details attribution card background by gordon johnson https pixabay com users gdj 1086657 provided by pixabay https pixabay com | humber | front_end |
udemyNode | udemynode udemy course for backend development i node de cero a experto i br br link https www udemy com course node de cero a experto topics covered in course node fundamentals js promises node foundations interactive console app todo list interactive console app weather api webserver http express hbs rest server rest server scope user authentication jwt google signin frontend backend sockets foundations node typescript mysql projects in this repo 4 interactive console application todo list br run the todo list app by opening console and typing node app 5 console weather app consume weather apis run the weather app by opening console and typing node app or npm start | nodejs | server |
TNKernel_v3 | tnkernel v3 tnkernel v3 is a small high performance rtos with ports for the arm cortex m0 3 4 7 and msp430x mpus tnkernel v3 supports static and dynamic os objects creation tasks semaphores mutexes queues mailboxes evenflags fixed sized memory pools malloc timers the tnkernel v3 code is misra c 2012 compliant according to iar c stat the directory tests contains a comprehensive set of the tests for the all tnkernel v3 objects and ports | os |
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learning-path-system-design | learning path system design curated path for learning system design based on published videos in techprimers each link points to a separate youtube video the code samples and relevant links videos are available in the description of each video system design 1 basics basics 2 deep dive deep dive 1 basics apis vs events when to choose one over other https youtu be 3t7pmx35reg rest vs graphql when to choose one over other https youtu be 4aksaaeyjqs rabbitmq vs kafka trade offs to choose one over other https youtu be gmmrtsfq5z0 when to use kafka and rest https youtu be 13p483nnwho cap theorem trade offs to choose a database https youtu be r fxz14tr2m api gateway swiggy architecture https youtu be wa q8c6qo68 load balancing https youtu be 7lmaavwze2c client side load balancing https youtu be pbnwgddmcm server side load balancing https youtu be z90dcid2py4 proxy server vs reverse proxy server https www youtube com watch v 4nanxfx5gbg how to design highly available systems https youtu be dhvgnqbx7zm the scale cube rules of scalability https youtu be 8zw3rl4lety centralized log management https youtu be 4x0wlg05asw golden signals of monitoring https youtu be yvk1fovinwq serverless architectural use cases https www youtube com watch v 43phzc3wd8s 2 deep dive zomato system design https youtu be a8rm2xcm9ry stock exchange system design event sourcing cqrs https youtu be e 7tbzxmkxe food store system design https youtu be bhelfhgsn2c batch processing stream processing system design https youtu be a3mvy8wmk04 caching architectures https youtu be 0x zv vp73k rapids rivers ponds event driven system design https youtu be st89bxuxnei iot platform system design https youtu be bdcdkdfdf7o zerodha cloud native system design https www youtube com watch v 1twrah3avhy transaction outbox pattern resilient transactional design https www youtube com watch v m fhb8lzhpo p s all the content in this readme are based on the videos published in techprimers https www youtube com techprimers disclaimer policy the content views opinions posted here are solely mine and the code samples created by me are open sourced you are free to use the code samples in github after forking and you can modify it for your own use all the videos posted in youtube are copyrighted you cannot re distribute videos on this channel in other platforms contact social media get the latest videos about latest technology trends aws kubernetes microservices etc youtube https www youtube com techprimers twitter https twitter com techprimers facebook https www facebook com techprimers github https github com techprimers instagram https instagram com techprimers reddit https reddit com r techprimers mail us mailto info techprimers com | os |
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orbit-swiftui | div align center a href https orbit kiwi target blank img alt orbit components src https images kiwi com common orbit logo full png srcset https images kiwi com common orbit logo full 2x png 2x a div br div align center kiwi com library https img shields io badge kiwi com library 00a991 https code kiwi com swiftui version https img shields io badge swiftui 1 0 blue https developer apple com documentation swiftui swift version https img shields io badge swift 5 5 orange https github com apple swift swift package manager https img shields io badge swift package manager compatible green https github com apple swift package manager build https github com kiwicom orbit swiftui actions workflows ci yml badge svg https github com kiwicom orbit swiftui actions workflows ci yml strong orbit is a swiftui component library which provides developers the easiest possible way of building kiwi com s products strong div orbit mission orbit https orbit kiwi aims to bring order and consistency to all of our products and processes we elevate user experience and increase the speed and efficiency of how we design and build products orbit is an open source design system created for specific needs of kiwi com and together with that for needs of travel projects this library allows you to integrate the orbit design system into your ios swiftui project requirements ios 13 xcode 15 swift package manager installation add orbit package to your project by adding the package dependency swift package name orbit url https github com kiwicom orbit swiftui git uptonextmajor from 0 8 0 documentation docc documentation docc png https kiwicom github io orbit swiftui documentation orbit br docc documentation https kiwicom github io orbit swiftui documentation orbit the online documentation contains instructions on how to get started with the library once you integrate it into your project as well as examples and pages for individual components you can also build this documentation locally in xcode product build documentation app store the app can also be downloaded from the app store a href https apps apple com us app orbit storybook id1622225639 itsct apps box badge amp itscg 30200 style display inline block overflow hidden border radius 13px width 150px height 50px img src https tools applemediaservices com api badges download on the app store black en us size 150x50 amp releasedate 1651708800 h 19b81a69aa959af2af398c51dc84737a alt download on the app store style border radius 13px width 150px height 50px a contributing feel free to create bug reports and feature requests via the issues tab if you want to directly contribute by fixing a bug or implementing a feature or enhancement you are welcome to do so pull request review has following priorities to check 1 api consistency with other components similar components should have similar api 2 component variants matching design variants components should have same properties as design 3 visual match to designs 4 internal code structure consistency button like components should use consistent mechanism haptics etc 5 previews storybook consistency a new component needs to be added to the storybook feedback we want to provide high quality and easy to use components we can t do that without your feedback if you have any suggestions about what we can do to improve please report it directly as an issue or write to us at orbit components on slack | swiftui ui-components | os |
decentralized_AI | decentralized ai final project for siraj s school of ai authors benoit courty matthew mcateer alexandre moreau and jeddi mees for more background info read our whitepaper https github com trancept decentralized ai blob master whitepaper whitepaper md this is our try at building a decentralized ai well it is just a semantic segmentation task that run in a decentralized fashion the task is done on a machine in the internet like in a proprietary cloud but on a decentralized cloud you do not have to create an account with the computer owner all is handle by iexec the semantic segmentation is done by the mask rcnn https github com matterport mask rcnn project trained on the coco dataset http cocodataset org submit an image frontui https raw githubusercontent com trancept decentralized ai master img front ai2 jpg get the result in the work tab frontuiwork https raw githubusercontent com trancept decentralized ai master img front work jpg and you are done sampleresult https raw githubusercontent com trancept decentralized ai master img iexec team mrcnn png other sample mask r cnn https github com trancept decentralized ai blob master img 20180604 143926 png the docker image was based on the modern deep learning container from waleed abdulla https hub docker com r waleedka modern deep learning with the mask rcnn added into it along with a modified version of the demo packaged for iexec iexec is a whole ecosystem with a market place for dapps oracle mechanism scheduler workers https cdn images 1 medium com max 1200 1 iierfys1iqvvxncxfrghfa jpeg dedicated to off chain computing in a fully decentralized way the v2 is just out speaking from 1st of june 2018 iexec sdk https github com iexecblockchaincomputing iexec sdk is a nodejs application who allow to easily create and manage your application the result is that you can call it quite like an api to get your resulting image how to run iexec front side you could use it on the browser http nrxubuntu eastus2 cloudapp azure com get eth and rlc for kovan connect to metamask and switch to kovan ethereum test network ask for free eth on kovan faucet https gitter im kovan testnet and for free rlc on iexec marketplace https market iex ec then transfert rlc from your wallet to your account on top left of iexec marketplace https market iex ec build it from source cd frontend npm install npm run dev your browser will automatically go to localhost 8081 so you can access the frontend choose an image from your harddisk or copy past an url choose a worker in the list on the right click on iexec button openmined side in openmined https github com trancept decentralized ai tree master openmined folder you will find a demo of how to use open mined to train a model using decentralized grid computing capabilities how we make it building the docker image docker build docker keras cpu t trancept keras mrcnn v0 docker run v pwd iexec trancept keras mrcnn v0 http fr ubergizmo com wp content uploads 2017 11 nouvel algorithme correction panoramas google street view jpg docker push trancept keras mrcnn v0 iexec project init project get money iexec wallet getrlc for eth on kovan you have to go to ask for it on kovan faucet https gitter im kovan testnet check your wallet iexec wallet show you need to have eth and rlc send money to the iexec account marketplace to use it iexec account deposit 100 check money iexec account show deploy adding docker image to iexec edit iexec js run iexec app deploy iexec app show prepare order iexec order init buy important you have to edit iexec json at these step to edit the params string to match the parameters you want to send to the job how to execute iexec dapp easiest way the easiest way is to go to https market iex ec and place a buy order with an available sell order id dapp address 0xc790d024ec41a7649e7a0590e4ae05891fa61ef8 work params cmdline https storage canalblog com 78 32 802934 60160490 jpg command line way clone the repository change the image url in iexec json run you have to initiate an order to buy computing ressource then find one available then buy it show available computing ressource iexec orderbook show category 3 check a ressource iexec order show 170 buy the ressource iexec order fill 170 check the status iexec work show 0xfda65e0d09bf434ea1e52f4ec044a07d6e7d592d watch download | ai |
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front-end-handbook-2019 | front end developer handbook 2019 written by cody lindley http codylindley com sponsored by frontend masters https frontendmasters com advancing your skills with in depth modern front end engineering courses this is a guide that anyone could use to learn about the practice of front end development it broadly outlines and discusses the practice of front end engineering how to learn it and what tools are used when practicing it in 2019 it is specifically written with the intention of being a professional resource for potential and currently practicing front end developers to equip themselves with learning materials and development tools secondarily it can be used by managers ctos instructors and head hunters to gain insights into the practice of front end development the content of the handbook favors web technologies html css dom and javascript and those solutions that are directly built on top of these open technologies the materials referenced and discussed in the book are either best in class or the current offering to a problem the book should not be considered a comprehensive outline of all resources available to a front end developer the value of the book is tied up in a terse focused and timely curation of just enough categorical information so as not to overwhelm anyone on any one particular subject matter the intention is to release an update to the content yearly read online https frontendmasters com books front end handbook 2019 https frontendmasters com books front end handbook 2019 download pdf https github com frontendmasters front end handbook 2019 raw master exports front end 20developer 20handbook 202019 pdf epub https github com frontendmasters front end handbook 2019 raw master exports front end 20developer 20handbook 202019 epub a rel license href http creativecommons org licenses by nc nd 3 0 img alt creative commons license style border width 0 src https i creativecommons org l by nc nd 3 0 88x31 png a br this work is licensed under a a rel license href http creativecommons org licenses by nc nd 3 0 creative commons attribution noncommercial noderivs 3 0 unported license a | javascript frontend front-end-development front-end css book handbook | front_end |
machine.js | machine for typescript javascript machine is a natural language processing library it is specifically focused on providing tools and techniques that are useful for processing languages that are very resource poor the library is also useful as a foundation for building more advanced language processing techniques the library currently only provides a basic set of algorithms but the goal is to include many more in the future features tokenization machine provides a set of word and segment tokenizers translation machine provides interfaces and classes for supporting interactive machine translation in a browser the calling application must provide an implementation of the interactive translation engine the translation engine returns all possible translations for a source segment in a word graph the application can efficiently search the graph for best translation suffix based on a provided prefix using the interactive translator class installation sh npm install sillsdev machine | ai |
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ChatKBQA | chatkbqa chatkbqa a generate then retrieve framework for knowledge base question answering with fine tuned large language models paper https arxiv org abs 2310 08975 overview figs f1 drawio png figs f2 drawio png general setup environment setup conda create n chatkbqa python 3 8 conda activate chatkbqa pip install torch 1 13 1 cu117 torchvision 0 14 1 cu117 torchaudio 0 13 1 extra index url https download pytorch org whl cu117 pip install r requirement txt freebase kg setup below steps are according to freebase virtuoso setup https github com dki lab freebase setup how to install virtuoso backend for freebase kg 1 clone from dki lab freebase setup cd freebase setup 2 processed freebase https developers google com freebase virtuoso db file can be downloaded from here https www dropbox com s q38g0fwx1a3lz8q virtuoso db zip or via wget warning 53g disk space is needed tar zxvf virtuoso db zip 3 managing the virtuoso service to start service python3 virtuoso py start 3001 d virtuoso db and to stop a currently running service at the same port python3 virtuoso py stop 3001 a server with at least 100 gb ram is recommended download facc1 mentions for entity retrieval download the mention information including processed facc1 mentions and all entity alias in freebase from facc1 https 1drv ms u s aujig47glqtznjl7vbnoesk6qpw2 e hdy2ye to data common data facc1 chatkbqa data common data facc1 entity list file freebase complete all mention surface map file freebase complete all mention dataset experiments are conducted on 2 kbqa benchmarks webqsp cwq webqsp download the webqsp dataset from here https www microsoft com en us research publication the value of semantic parse labeling for knowledge base question answering 2 and put them under data webqsp origin the dataset files should be named as webqsp test train json chatkbqa data webqsp origin webqsp train json webqsp test json cwq download the cwq dataset here https www dropbox com sh 7pkwkrfnwqhsnpo aacuu4v3ynkhirzboeeahyala and put them under data cwq origin the dataset files should be named as complexwebquestions test train dev json chatkbqa data cwq origin complexwebquestions train json complexwebquestions dev json complexwebquestions test json data processing 1 parse sparql queries to s expressions webqsp run python parse sparql webqsp py and the augmented dataset files are saved as data webqsp sexpr webqsp test train json cwq run python parse sparql cwq py and the augmented dataset files are saved as data cwq sexpr cwq test train json 2 prepare data for training and evaluation webqsp run python data process py action merge all dataset webqsp split test train the merged data file will be saved as data webqsp generation merged webqsp test train json run python data process py action get type label map dataset webqsp split train the merged data file will be saved as data webqsp generation label maps webqsp train type label map json cwq run python data process py action merge all dataset cwq split test train the merged data file will be saved as data cwq generation merged cwq test train json run python data process py action get type label map dataset cwq split train the merged data file will be saved as data cwq generation label maps cwq train type label map json 3 prepare data for llm model webqsp run python process nq py dataset type webqsp the merged data file will be saved as llms data webqsp freebase nq test train examples json cwq run python process nq py dataset type cwq the merged data file will be saved as llms data cwq freebase nq test train examples json fine tuning retrieval and evaluation the following is an example of llama2 7b readme md fine tuning and retrieval num beam 15 on webqsp and llama2 13b readme md fine tuning and retrieval num beam 8 on cwq respectively we also provide a variety of llms including llama2 7b scripts readme llama2 7b md llama2 13b scripts readme llama2 13b md chatglm2 6b scripts readme chatglm2 6b md baichuan2 7b scripts readme baichuan2 7b md baichuan2 13b scripts readme baichuan2 13b md fine tuning scripts num beam 8 1 train and test llm model for logical form generation webqsp train llms for logical form generation bash cuda visible devices 3 nohup python u llms llama src train bash py stage sft model name or path meta llama llama 2 7b hf do train dataset dir llms data dataset webqsp freebase nq train template llama2 finetuning type lora lora target q proj v proj output dir reading llama2 7b webqsp freebase nq lora epoch100 checkpoint overwrite cache per device train batch size 4 gradient accumulation steps 4 lr scheduler type cosine logging steps 10 save steps 1000 learning rate 5e 5 num train epochs 100 0 plot loss fp16 train llama2 7b webqsp freebase nq lora epoch100 txt 2 1 beam setting llms for logical form generation bash cuda visible devices 3 nohup python u llms llama src beam output eva py model name or path meta llama llama 2 7b hf dataset dir llms data dataset webqsp freebase nq test template llama2 finetuning type lora checkpoint dir reading llama2 7b webqsp freebase nq lora epoch100 checkpoint num beams 15 predbeam llama2 7b webqsp freebase nq lora epoch100 txt 2 1 bash python run generator final py data file name reading llama2 7b webqsp freebase nq lora epoch100 evaluation beam generated predictions jsonl cwq train llms for logical form generation bash cuda visible devices 2 nohup python u llms llama src train bash py stage sft model name or path meta llama llama 2 13b hf do train dataset dir llms data dataset cwq freebase nq train template default finetuning type lora lora target q proj v proj output dir reading llama2 13b cwq freebase nq lora epoch10 checkpoint overwrite cache per device train batch size 4 gradient accumulation steps 4 lr scheduler type cosine logging steps 10 save steps 1000 learning rate 5e 5 num train epochs 10 0 plot loss fp16 train llama2 13b cwq freebase nq lora epoch10 txt 2 1 beam setting llms for logical form generation bash cuda visible devices 3 nohup python u llms llama src beam output eva py model name or path meta llama llama 2 13b hf dataset dir llms data dataset cwq freebase nq test template default finetuning type lora checkpoint dir reading llama2 13b cwq freebase nq lora epoch10 checkpoint num beams 8 predbeam llama2 13b cwq freebase nq lora epoch10 txt 2 1 bash python run generator final py data file name reading llama2 13b cwq freebase nq lora epoch10 evaluation beam generated predictions jsonl 2 evaluate kbqa result with retrieval webqsp evaluate kbqa result with entity retrieval and relation retrieval bash cuda visible devices 1 nohup python u eval final py dataset webqsp pred file reading llama2 7b webqsp freebase nq lora epoch100 evaluation beam beam test top k predictions json predfinal llama2 7b webqsp freebase nq lora epoch100 txt 2 1 evaluate kbqa result with golden entities and relation retrieval bash cuda visible devices 4 nohup python u eval final py dataset webqsp pred file reading llama2 7b webqsp freebase nq lora epoch100 evaluation beam beam test top k predictions json golden ent predfinalgoldent llama2 7b webqsp freebase nq lora epoch100 txt 2 1 cwq evaluate kbqa result with entity retrieval and relation retrieval bash cuda visible devices 4 nohup python u eval final cwq py dataset cwq pred file reading llama2 13b cwq freebase nq lora epoch10 evaluation beam beam test top k predictions json predfinal llama2 13b cwq freebase nq lora epoch10 txt 2 1 evaluate kbqa result with golden entities and relation retrieval bash cuda visible devices 5 nohup python u eval final cwq py dataset cwq pred file reading llama2 13b cwq freebase nq lora epoch10 evaluation beam beam test top k predictions json golden ent predfinalgoldent llama2 13b cwq freebase nq lora epoch10 txt 2 1 bibtex if you find this work is helpful for your research please cite bibtex misc luo2023chatkbqa title chatkbqa a generate then retrieve framework for knowledge base question answering with fine tuned large language models author haoran luo and haihong e and zichen tang and shiyao peng and yikai guo and wentai zhang and chenghao ma and guanting dong and meina song and wei lin year 2023 eprint 2310 08975 archiveprefix arxiv primaryclass cs cl for further questions please contact luohaoran bupt edu cn or wechat lhr1846205978 acknowledgement this repo benefits from peft https github com huggingface peft llama efficient tuning https github com hiyouga llama efficient tuning simcse https github com princeton nlp simcse gmt kbqa https github com hxx97 gmt kbqa and decaf https github com awslabs decode answer logical form thanks for their wonderful works | knowledge-graph semantic-parsing sparql-query graph-database finetuning large-language-models | ai |
docker-compose-php | nginx mariadb mailhog php 7 4 8 0 8 1 8 2 fpm apache mod php 5 6 7 4 8 1 https github com rhamdeew docker compose php workflows docker 20image 20ci badge svg russian readme readme ru md first local run all you have to do is run these commands 1 edit your etc hosts sudo vim etc hosts and add 127 0 0 1 site test 2 run these commands cp mysql env example mysql env cp docker nginx config templates site test conf php 82 docker nginx config site test conf mkdir p projects site test echo php echo phpversion projects site test index php make up details summary another options summary cp mysql env example mysql env edit mysql env you can choose the template with specific php version cp templates docker compose php 81 yml docker compose yml and copy specific config for nginx php fpm cp docker nginx config templates site test conf php 81 docker nginx config site test conf or copy configs for nginx apache php cp templates docker compose apache php 74 yml docker compose yml cp docker nginx config templates site test conf apache php 74 docker nginx config site test conf cp docker apache php 74 config templates site test conf docker apache php 74 config sites enabled site test conf mkdir p projects site test echo php echo phpversion projects site test index php make up details 3 test running services http localhost 8025 mailhog super demo http localhost 8080 adminer super demo http site test test site management for ease of management all basic commands are included in the makefile to list the available commands run cat makefile run docker compose up d make up stop docker compose stop make stop view the status of running containers docker compose ps make ps viewing container logs docker compose logs tail 100 f php 82 db mailhog nginx make logs name php 82 database host db fine tuning change login password super demo open docker nginx htpasswd and replace its contents host user permissions in the terminal using the id command we get the digital identifier of our user and group then uncomment the line run usermod u 1050 www data groupmod g 1050 www data in docker php 82 build dockerfile and replace id 1050 with your identifiers there we start containers with a rebuild docker compose up d build make upb php ini settings open docker php 82 config php ini or edit the php fpm settings www conf switch php version uncomment the block with the container of the required php version in docker compose yml in nginx config for the site comment out the old upstream and uncomment the new one docker compose stop docker compose up d build make st upb in the case of apache in the nginx config you need to comment out the entire block for php fpm and uncomment the one below for apache also do not forget to tweak apache configs adding a new host just copy config docker nginx config templates site test conf and tweak it in the case of using the container with apache you must also fix the docker apache php 56 config sites enabled site test conf config there are examples of nginx config files in docker nginx config disabled connect to the database from the console make php mysql uroot hdb pmysql root password example with importing sql dump make php mysql uroot hdb pmysql root password create database test mysql uroot hdb pmysql root password test dump sql connect to the database from the console docker compose f docker compose mycli yml run rm mycli bin ash c mycli uroot hdb p mysql root password true make mycli run php scripts from the console docker compose exec name bin sh true make exec name php 82 route access to the database the password is registered in the mysql root password parameter in mysql env change of database access details changed in mysql env file an example of running cron background tasks usr local bin docker compose f srv www docker compose php docker compose yml exec php 82 srv projects site test yii api send acme sh docker compose f docker compose acme yml run rm acme acme sh issue d echo d sed s d g w acme challenge make ssl d site ru www site ru ssl certificates are saved in the docker nginx ssl directory to make it work you need to uncomment lines in the docker compose yml config docker nginx ssl etc nginx ssl ro also uncomment the line 443 443 crontab 00 3 usr local bin docker compose f srv www docker compose php docker compose acme yml run rm acme acme sh cron 02 3 usr local bin docker compose f srv www docker compose php docker compose yml exec t nginx nginx t q usr local bin docker compose f srv www docker compose php docker compose yml restart nginx if you need to run acme sh for some other purpose you can do this with this command make acme node js docker compose f docker compose node yml run rm node 10 bin ash true make node mysql tuner docker compose f docker compose mysqltuner yml run rm mysqltuner bin ash c opt mysqltuner user root host db pass mysql root password forcemem mem true make mysqltuner mem 4096 | php docker mailhog php-fpm mod-php mariadb acme | front_end |
aether-app | p align center a href https getaether net img src https getaether net images logo v3 light bg png width 240 a p p align center aether is a peer to peer network of independent self moderated communities p p align center a href https news ycombinator com item id 18370208 hacker news a p p align center a href http www theverge com 2013 11 27 5150758 aether aims to be a reddit for the privacy conscious the verge a p heads up the current version is a developer preview it collects usage metrics to help debugging this is a developer preview a pre alpha it is unstable and untested it is not production ready legalese this software is provided for free on an as is basis with no warranty and without any expressed or implied offer of support there is no warranty for the program to the extent permitted by applicable law except when otherwise stated in writing the copyright holders and or other parties provide the program as is without warranty of any kind either expressed or implied including but not limited to the implied warranties of merchantability and fitness for a particular purpose the entire risk as to the quality and performance of the program is with you should the program prove defective you assume the cost of all necessary servicing repair or correction full license text gnu affero general public license 3 0 license md only download download aether https getaether net aether is available for mac os windows and linux our community supports windows mac os and linux versions at meta geteather net https meta getaether net c support compiling aether is a relatively large app with an electron and go toolchain at 100 000 lines of code getting it to compile requires setting up a correct build runtime with the latest versions of go node for electron and c dependencies and development environments expect the initial set up to take a few hours be patient instructions compile instructions can be found here on this gist https gist github com nehbit 4a8c3d81d543e85c9df974f521732b1e and at getaether net docs developers https getaether net docs developers filing a bug please create a topic in the appropriate section of meta getaether net https meta getaether net this allows the non github using majority of aether users to help with your issue and point you in the right direction backers aether exists thanks to the generous fellows below funding aether comes with some perks such as registering your unique name before anyone else see here https getaether net supporterbenefits for full benefits a href https www patreon com nehbit img src https c5 patreon com external logo become a patron button 2x png width 160 a gold sponsors your name here https www patreon com bepatron u 11407204 sponsors peter wang generous backers alex alex tibbles andrew asher gottlieb bart grantham cerxi chip wasson daniel fischer duane bailey jackson solway james bekkema john alexander john moore john travise lewis liu mindricity pavel minaev ryan hill sebastian jug srdis steamy mcmemerton steve tom kapanka backers andreas basurto forest friendly grischa bo lar whitman schorn crypto supporters agalati hostfat | aether p2p desktop-app discussion-platform golang vue go mac-app windows-app linux-app snap | front_end |
SIM7000-LTE-Shield | overview this shield uses simcom s sim7000 series module a low power cellular module that supports lte cat m1 and nb iot technology and integrated multi gnss gps glonass and beidou compass galileo qzss standards for location tracking the shield can be used in different regions around the world by using the appropriate module version sim7000a america sim7000c china sim7000e europe or sim7000g global as detailed on the github wiki https github com botletics sim7000 lte shield wiki board versions the shield also includes a high accuracy i2c temperature sensor for iot monitoring applications to use the shield follow the step by step wiki https github com botletics sim7000 lte shield wiki to attach the headers plug the shield into an arduino insert a compatible sim card attach the dual lte gps antenna and you re ready to load the example code you can buy the shield on amazon com http a co d eq2l2tl check out the comprehensive wiki https github com botletics lte shield wiki or use this instructables https www instructables com id lte nb iot shield for arduino to get started if that works better for you all pcb design files and hardware are released under the creative commons attribution share alike 4 0 license https choosealicense com licenses cc by sa 4 0 all other software is released under the gnu general public license v3 0 https choosealicense com licenses gpl 3 0 arduino library support this library is based on the adafruit fona library https github com adafruit adafruit fona and supports a variety of simcom 2g 3g 4g lte cat m nb iot modules including the sim7000 lte cat m nb iot module please see the sim7000 shield library repo https github com botletics sim7000 shield library for source code more info on the botletics sim7000 shield hardware can be found here on botletics https www botletics com products sim7000 shield and here on amazon https a co d apoagud for a list of library functions please see this wiki page https github com botletics sim7000 lte shield wiki library functions to get help or share a project you ve done using this hardware or library please go to the botletics community forum https forum botletics com | arduino arduino-ide lte cellular iot low-power microcontroller gps gnss nb-iot | server |
curriculum | the project is in development now and is open for contributions design figma https www figma com file 5egt4txy4r69wkzq8jxw9f untitled node id 0 3a1 code editor images code editor svg how to run 1 yarn install 2 yarn dev contributing to curriculum from opening a bug report to creating a pull request every contribution is appreciated and welcomed if you re planning to implement a new feature or change the api please create an issue first this way we can ensure your work is not in vain where to add content and how it works there is a website readme https github com planet nullcast curriculum blob main how to add chapter md file which lists out how the curriculum is structured and which files need to be updated for adding content steps for contributing switch to development https github com planet nullcast curriculum tree development branch before start working as it has the latest code 1 create or pick an issue from the issues https github com planet nullcast curriculum issues 2 if adding a new feature create an issue with lots of details to support you can even start a discussion here https github com planet nullcast curriculum discussions to gain upvotes or ask for improvising the idea 3 for a member create a branch and send pr 4 the contributions guide is generally forking and pull request https github com firstcontributions first contributions for outside collaborators happy hacking commit mesage specify the type of commit feat the new feature you re adding to a particular application fix a bug fix style feature and updates related to styling refactor refactoring a specific section of the codebase test everything related to testing docs everything related to documentation chore regular code maintenance you can also use emojis to represent commit types separate the subject from the body with a blank line your commit message should not contain any whitespace errors remove unnecessary punctuation marks do not end the subject line with a period capitalize the subject line and each paragraph use the imperative mood in the subject line use the body to explain what changes you have made and why you made them do not assume the reviewer understands what the original problem was ensure you add it do not think your code is self explanatory type title why this is necessary how it is done fixes issue number for example feat create new post new post can be created using the button api post create is used the store integration is with react redux modal uses abcd package fixes issue 223 | curriculum web development course hacktoberfest | front_end |
CEDS-Data-Warehouse-Parquet | ceds data warehouse parquet logo res data warehouse parquet logo full png ceds data warehouse parquet ceds data warehouse parquet dw parquet welcome to the ceds open source community the common education data standards ceds data warehouse parquet dw parquet standard is designed for data engineering and data science needs in the cloud the dw parquet models mirror the sql based ceds data warehouse parquet files are designed for rapid and distributed reporting across multiple technology stacks data processing and bi tools and are cloud vendor agnostic this standard is ideal for stakeholders implementing reporting structures in a data lake environment submitting a use case use cases may be submitted through the issues https github com cedstandards ceds data warehouse parquet issues tab by clicking on new issue and then get started which is located next to ceds integrated data store and data warehouse use case contributing please read contributing md contributing md for details on the process for submitting pull requests versioning the ceds open source community uses a customized version of explicit versioning to keep the various ceds open source projects in alignment with the ceds elements the concept of disruptive releases has been replaced with alignment releases these releases ensure that the data models are in sync with the official ceds community approved list of ceds elements for the versions available see the tags on this repository here is an example of how explicit versioning will occur assuming an official release of ceds has just occurred data warehouse dw version 7 0 0 0 data warehouse parquet dw parquet version 7 0 0 0 integrated data store ids version 7 0 0 0 ceds elements 7 0 0 0 use case brand new elements are introduced to ceds because they are new they represent no breaking change to any of the other ceds elements ceds elements version 7 0 1 0 these new elements however result in a new understanding of how data is integrated in the ids resulting in a restructuring of the ids which is not backwards compatible ids version 7 1 0 0 these elements are added to the dw structure and result in backwards compatibility but a defect is identified in doing so that needs to be corrected dw version 7 0 1 1 these elements are also added to the dw parquet structure and result in backwards compatibility but a defect is identified in doing so that needs to be corrected the ceds dw and ceds dw parquet standards are updated simultaneously to maintain cross compatibility dw parquet version 7 0 1 1 throughout the remainder of the year many changes occur in each of the different repositories the changes prior to the annual release of ceds results in the following dw version 7 27 1 6 dw parquet version 7 27 1 6 ids version 7 3 2 0 ceds elements 7 2 18 2 the annual official ceds release occurs typically around january february of the calendar year all resources are brought into version alignment note no changes occurred to the resource the annual release simply restarts aligns the versioning dw version 8 0 0 0 dw parquet version 8 0 0 0 ids version 8 0 0 0 ceds elements version 8 0 0 0 note the ceds collaborative exchange contains resources contributed by stakeholders these resources should contain the compatible version they were created under the versions are not changed for a resource unless a stakeholder updates them to function under a newer version license this project is licensed under the apache 2 0 license license see the license file for details | data-warehouse data-standard data-standards data-warehouses parquet ceds | cloud |
awesome-reviews-kaist | license cc by sa 4 0 https img shields io badge license cc 20by sa 204 0 lightgrey svg https creativecommons org licenses by sa 4 0 awesome reviews by kaist ai 2021 ai604 https awesome davian gitbook io awesome reviews from the fall semester of 2021 the reviews written by kaist ai604 deep learning for computer vision class students will be available on the internet the articles will be mainly written in the korean language in order to contribute to the deep learning community of korea also we will focus on the up to date papers which are not reviewed or summarized in the korean language yet we prepared several types of articles for high quality content and these will cover a detailed explanation of the paper know how on research and implementation of algorithm modules with line by line descriptions to deliver accurate information all contents are peer reviewed by the students all articles are available at https awesome davian gitbook io awesome reviews course information ai604 the instructor and the teaching assistants of kaist ai604 deep learning for computer vision class are in charge of this project instructor jaegul choo associate professor kim jaechul graduate school of ai kaist webpage https sites google com site jaegulchoo teaching assistant youngwoo cho ph d student kim jaechul graduate school of ai kaist contact jeonghoon park ph d student kim jaechul graduate school of ai kaist contact sunghyun park ph d student kim jaechul graduate school of ai kaist contact sanghyeon lee ph d student kim jaechul graduate school of ai kaist contact chaehoon park ph d student kim jaechul graduate school of ai kaist contact license 4 0 see the license license md file for license rights and limitations cc by sa 4 0 | ai |
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laptop | laptop build status https circleci com gh 18f laptop svg https circleci com gh 18f laptop laptop is a script to set up an os x computer for web development and to keep it up to date it can be run multiple times on the same machine safely it installs upgrades or skips packages based on what is already installed on the machine requirements we support macos sierra 10 12 https www apple com osx os x el capitan 10 11 os x yosemite 10 10 os x mavericks 10 9 older versions may work but aren t regularly tested bug reports for older versions are welcome install begin by opening the terminal application on your mac the easiest way to open an application in os x is to search for it via spotlight the default keyboard shortcut for invoking spotlight is command space once spotlight is up just start typing the first few letters of the app you are looking for and once it appears press return to launch it in your terminal window copy and paste the command below then press return sh bash curl s https raw githubusercontent com 18f laptop master laptop the script https github com 18f laptop blob master mac itself is available in this repo for you to review if you want to see what it does and how it works note that the script will ask you to enter your os x password at various points this is the same password that you use to log in to your mac if you don t already have it installed github for mac will launch automatically at the end of the script so you can set up everything you ll need to push code to github once the script is done make sure to quit and relaunch terminal more detailed instructions with a video video are available in the wiki it is highly recommended to run the script regularly to keep your computer up to date once the script has been installed you ll be able to run it at your convenience by typing laptop and hitting return in your terminal spotlight https support apple com en us ht204014 video https github com 18f laptop wiki detailed installation instructions with video want to install just git seekret in your terminal window copy and paste the following line and press return sh curl s https raw githubusercontent com 18f laptop master seekrets install bash note that the script may ask you to enter your password this is the same password that you use to log in to your computer git seekret requires git 2 9 1 or higher some versions of ubuntu ship with an older version to update your git before installing git seekret sudo add apt repository ppa git core ppa sudo apt get update git seekret will install global git hooks into git support hooks to restore pre existing git hooks it is recommended to save pre existing hooks into a separate directory and to copy those hooks into git support hooks after git seekret is installed development git seekret this section covers contributing and developing new rulesets for git seekrets the rules installed by the seekret install script are located in the seekret rules directory at the root of this repository inside each rule file is a list of rules the rule file can be considered a tree with the rules as the leaves of the tree an example rule file is below yaml thing to match match r egx 2 p unmatch some prefix s r egx 2 p r egx 2 p s some suffix using the example above let s break down each stanza thing to match the name of the rule we d like to match unmatch this can be anything that makes sense for the rule file being created edited match a single regular expression which will be used to match any rules for the name above unmatch a list of regular expressions which will be used to unmatch anything that the match rule matches feel free to submit an issue create a pull request in order to submit a new ruleset or to apply a modifification to an existing ruleset testing git seekrets you can test secret rulesets using bats for automated testing and manually using the installation script let s talk about bats please read the local bats documentation test let s talk about local manual testing to install the rule files located in the repo just run the installation script locally this will update your local git support seekret rules directory with the changes in this repository shell seekrets install you should now be able to run the check within any repository on your machine shell git seekret check c 0 check for secrets within commit history shell git seekret check s check for secrets within staged files debugging your last laptop run will be saved to laptop log read through it to see if you can debug the issue yourself if not copy and paste the entire log into a new github issue https github com 18f laptop issues new for us git seekrets false positives sometimes the git seekrets rules may indicate a false positive and match things that aren t actually secrets this can happen if the regular expressions used to match and unmatch are too strict make sure you have the latest rulesets from this repository by running the git seekrets installation script want to install just git seekret if the ruleset is still triggering a false positive please open an issue or a pull request if you know how to fix the regular expression and include the text that is being treated as a false positive along with the rules installed on your computer please run this command to output your current rules then copy and paste them into the github issue shell cat git support seekret rules rule what it sets up chromedriver for headless website testing chruby for managing ruby versions cloud foundry cli for command line access to 18f s cloud foundry based application platform docker for all your containerization needs git seekret for preventing you from committing passwords and other sensitive information to a git repository github desktop for setting up your ssh keys automatically homebrew for managing operating system libraries homebrew cask for quickly installing mac apps from the command line homebrew services so you can easily stop start and restart services hub for interacting with the github api nvm for managing node js versions if you do not have node js already installed includes latest node js and npm for running apps and installing javascript packages pyenv for managing python versions if you do not have python already installed includes the latest 3 x python ruby install for installing different versions of ruby slack for communicating with your team the silver searcher for finding things in files virtualenv for creating isolated python environments via pyenv if it is installed virtualenvwrapper for extending virtualenv via pyenv if it is installed zsh as your shell bundler http bundler io chromedriver http chromedriver chromium org chruby https github com postmodern chruby cloud foundry cli https github com cloudfoundry cli docker https www docker com git seekret https github com 18f git seekret homebrew http brew sh homebrew cask https github com homebrew homebrew cask homebrew services https github com homebrew homebrew services hub https github com github hub n https github com tj n node js http nodejs org npm https www npmjs org python https www python org pyenv https github com yyuu pyenv ruby https www ruby lang org en ruby install https github com postmodern ruby install slack https slack com the silver searcher https github com ggreer the silver searcher virtualenv https virtualenv pypa io en latest virtualenvwrapper http virtualenvwrapper readthedocs org en latest zsh http www zsh org it should take less than 15 minutes to install depends on your machine and internet connection customize in laptop local and brewfile local your laptop local is run at the end of the mac script put your customizations there if you want to install additional tools or mac apps with homebrew add them to your brewfile local this repo already contains a laptop local and brewfile local you can use to get started sh go to your os x user s root directory cd download the sample files to your computer curl remote name https raw githubusercontent com 18f laptop master laptop local curl remote name https raw githubusercontent com 18f laptop master brewfile local it lets you install the following tools and apps vscode microsoft s open source text editor atom github s open source text editor sublime text 3 for coding all the things vim for those who prefer the command line exuberant ctags for indexing files for vim tab completion firefox for testing your website on a browser other than chrome iterm2 an awesome replacement for the os x terminal reattach to user namespace to allow copy and paste from tmux tmux for saving project state and switching between projects spectacle automatic window manipulation laptop local https github com 18f laptop blob master laptop local brewfile local https github com 18f laptop blob master brewfile local vscode https code visualstudio com atom https atom io sublime text 3 http www sublimetext com 3 exuberant ctags http ctags sourceforge net firefox https www mozilla org en us firefox new iterm2 http iterm2 com reattach to user namespace https github com chrisjohnsen tmux macosx pasteboard tmux https tmux github io vim http www vim org spectacle https www spectacleapp com write your customizations such that they can be run safely more than once see the mac script for examples laptop functions such as fancy echo and gem install or update can be used in your laptop local what about background services redis postgres mysql etc the script does not automatically install services like databases because you may not need any particular one or you may need specific versions not just the latest for services we recommend using docker for example you can use the docker run command to start a service in a container and make the container s port available to your local machine shell docker run p 5432 postgres 10 6 you can also use docker compose to define your app s containers and their relationships cutting out the need to manually setup each service docker compose https docs docker com compose docker run https docs docker com engine reference run expose incoming ports how to switch your shell back to bash from zsh or vice versa 1 find out which shell you re currently running echo shell 2 find out the location of the shell you want to switch to for example if you want to switch to bash run which bash 3 verify if the shell location is included in etc shells run cat etc shells to see the contents of the file 4 if the location of the shell is included run chsh s the location of the shell for example if which bash returned bin bash you would run chsh s bin bash if the location of the shell is not in etc shells add it then run the chsh command if you have sublime text you can open the file by running subl etc shells 5 quit and restart terminal or iterm2 or open a new tab for the new shell to take effect whether you re using bash or zsh we recommend installing the latest versions with homebrew because the versions that came with your mac are really old brew install bash or brew install zsh credits the 18f laptop script is based on and inspired by thoughtbot s laptop https github com thoughtbot laptop script public domain thoughtbot s original work remains covered under an mit license https github com thoughtbot laptop blob c997c4fb5a986b22d6c53214d8f219600a4561ee license 18f s work on this project is in the worldwide public domain license md as are contributions to our project as stated in contributing contributing md this project is in the public domain within the united states and copyright and related rights in the work worldwide are waived through the cc0 1 0 universal public domain dedication https creativecommons org publicdomain zero 1 0 all contributions to this project will be released under the cc0 dedication by submitting a pull request you are agreeing to comply with this waiver of copyright interest | front_end |
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FlyingFox | flying fox work has been moved to amoveo https github com zack bitcoin amoveo a security flaw was found in this software in this repository that is difficult to fix i am planning on starting over with a new github project the flaw is that if the coins are distributed too thinly amount too many people that it becomes cheap to bribe the validators to keep a fork alive lightning consensus is a bad idea combining the consensus mechanism with the channel mechanism is a bad idea it does increase the amount of voice we get in making consensus decisions but there are other more efficient ways to achieve this goal non technical explanation docs goal md innovations in flying fox docs innovations md glossary to define words used in cryptoeconomics docs glossary md explains how chanels work useful for other projects that want to clone this channel mechanism docs channels md this explains 3 types of attacks that can be done to proof of stake blockchkains and compares flying fox to other pos mechanisms docs failure modes md this calculates the portion of money that needs to be colluding with the attacks for the attack to be successful docs security py this folder is for calculating how stable coins will be made from synthetic assets docs stablecoin code of conduct development guidelines submit pull requests if i like your code and it passes tests i will accept it feel free to ask me questions or make github issues installing for ubuntu compile md | blockchain |
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PPLM | privacy protection language models overview large language models llms exhibit advanced linguistic comprehension but face challenges in specialized industries including hallucination and the inability to update with the latest domain knowledge while open source llms like llama and rwkv offer fine tuning solutions using domain specific knowledge there remain significant concerns about privacy especially with the potential exposure of sensitive data this work introduces methodologies for fine tuning llms to ensure both domain knowledge incorporation and robust privacy protection the work explored strategies such as corpus curation penalty based unlikelihood in training loss and instruction based tuning with the goal of developing models that can effectively balance knowledge acquisition with privacy protection environment setup to set up the required environment bash pip install r requirements txt note if you intend to use fsdp peft install pytorch nightlies please ensure the correct version of pytorch has been installed dataset datasets provided there are five dataset classes provided in pt dataset py ft datasets pt dataset py originaldataset offers raw training data with basic templated prompts for experiments vanilla tuning penalty classifier share this dataset class qadataset is structured for question answer setups the inputs are prepended with question n while the outputs are prepended with responses n for experiments qa and dpo share this dataset class removedataset cleanses the output by eliminating pii tokens for experiments removal uses this dataset class maskdataset is similar to removedataset the pii tokens are replaced by their corresponding categories e g name organization for experiments substitution uses this dataset class instructdataset creates its prompts and outputs based on specific instruction strategies the dataset provides different choices of templates in template py ft datasets template py for experiments it pn np share this dataset class adding custom datasets to introduce custom datasets create a dataset configuration in configs datasets py configs datasets py add a preprocessing routine in the ft datasets ft datasets folder register the dataset name and preprocessing function in utils dataset utils py utils dataset utils py update the dataset field in the training config or use the dataset option of the training script model the backbone models used for the experiments are the llama2 7b and 13b models please ensure the path to your model is specified using the model name flag in the training script further configurations including peft methods and quantization can be set in configs training py configs training py training hardware and software gpu cards nvidia a100 sxm4 80gb 4 cards each node 3 nodes driver version 530 30 02 cuda version 12 1 memory capacity 80gb operating system ubuntu 22 04 2 lts python 3 10 12 pytorch 2 0 1 configuration main training configurations are available in configs training py configs training py this file allows you to specify various settings from the model s path to batch size and learning rates besides the use of peft methods with the huggingface peft https github com huggingface peft library and bitsandbytes https github com timdettmers bitsandbytes int8 quantization can alleviate the burden on gpu and enable training of llama2 7b on gpu cards with as less as 24gb of memory scripts we provide the scripts to train llama2 on pii protection tasks in run sh run sh bash subset wikidoc stgy instruct task instruct loca stgy subset size ml bs echo loca mkdir p ckpt loca train llama2 with peft torchrun nnodes 1 nproc per node 4 llama finetuning py enable fsdp use peft peft method lora model name models hf size pure bf16 output dir ckpt loca num epochs ep batch size training bs micro batch size bs num workers dataloader 64 use fast kernels dataset task dataset subset subset maxlen ml inst strategy stgy 2 1 tee a ckpt loca train log merge the lora weights python inference hf text generation inference merge lora weights py base model models hf 7b peft model ckpt loca output dir ckpt merge loca evaluation genrarte evaluation samples run ft datasets example sampler py script pass subset parameter to generator to initialize then pass task argument to generate function to generate dataset datafileds filling into templeates ready for feeding into model for inference and save as json file example generator generator subset medical flashcards generator generate task original inference pipeline please utilize the inference pl py inference pl py script for the inference pipeline usage bash python pl py h dataset dataset template template scale scale max length max length train batch size train batch size generate batch size generate batch size max new tokens max new tokens use tqdm device device model evaluation evaluate models using the inference eval py inference eval py script this script calculates rouge and bert scores for label prediction pairs usage bash python inference eval py subset medical flashcards wikidoc wikidoc patient information strategy original remove loss instruct etc scale 7b 13b | ai |
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carbon-components-svelte | carbon components svelte npm npm npm url github https img shields io github license carbon design system carbon components svelte color 262626 style for the badge npm downloads to date https img shields io npm dt carbon components svelte color 262626 style for the badge a href https discord gg j7jeuektrx img src https img shields io discord 689212587170201628 color 5865f2 style for the badge alt chat with us on discord a carbon components svelte is a svelte https github com sveltejs svelte component library that implements the carbon design system https github com carbon design system an open source design system by ibm design systems facilitate design and development through reuse consistency and extensibility the carbon svelte portfolio also includes carbon icons svelte https github com carbon design system carbon icons svelte 2 000 carbon icons as svelte components carbon pictograms svelte https github com carbon design system carbon pictograms svelte 1 000 carbon pictograms as svelte components carbon charts svelte https github com carbon design system carbon charts tree master packages svelte 20 charts powered by d3 carbon preprocess svelte https github com carbon design system carbon preprocess svelte collection of svelte preprocessors for carbon documentation https carbon components svelte onrender com other forms of documentation are auto generated typescript definitions types component typescript definitions component index component index md component api in markdown format component api docs src component api json component api in json format installation install carbon components svelte as a development dependency sh yarn yarn add d carbon components svelte npm npm i d carbon components svelte pnpm pnpm i d carbon components svelte usage styling before importing components you will need to first apply carbon component styles the carbon design system supports five themes 2 light 3 dark white css default carbon theme light g10 css gray 10 theme light g80 css gray 80 theme dark g90 css gray 90 theme dark g100 css gray 100 theme dark all css all themes white gray 10 gray 90 gray 100 using css variables https developer mozilla org en us docs web css using css custom properties each stylesheet is generated scripts build css js from the flagship carbon components https github com carbon design system carbon tree main packages carbon components library the compiled css is generated from the following scss files css white scss css white scss css g10 scss css g10 scss css g80 scss css g80 scss css g90 scss css g90 scss css g100 scss css g100 scss css all scss css all scss css stylesheet js white theme import carbon components svelte css white css gray 10 theme import carbon components svelte css g10 css gray 80 theme import carbon components svelte css g80 css gray 90 theme import carbon components svelte css g90 css gray 100 theme import carbon components svelte css g100 css all themes import carbon components svelte css all css cdn an alternative to loading styles is to link an external stylesheet from a content delivery network cdn like unpkg com https unpkg com this is best suited for rapid prototyping html html doctype html html head link rel stylesheet href https unpkg com carbon components svelte css white css head html svelte head html svelte head link rel stylesheet href https unpkg com carbon components svelte css white css svelte head scss the most performant method to load styles is to import scss directly from carbon components although it requires more set up you can reduce the size of the bundle css by importing individual component styles instead of a pre compiled css stylesheet refer to the official carbon guide on sass https github com carbon design system carbon blob v10 docs guides sass md for documentation dynamic theming use the all css stylesheet for dynamic client side theming js import carbon components svelte css all css update the theme by setting the theme attribute on the html element the default theme is white html doctype html html lang en theme g10 body body html programmatically switch between each of the five carbon themes by setting the theme attribute on the html element html script let theme white white g10 g80 g90 g100 document documentelement setattribute theme theme script importing components import components from carbon components svelte in the script tag of your svelte file visit the documentation site https carbon components svelte onrender com for examples html app svelte script import accordion accordionitem from carbon components svelte script accordion accordionitem title section 1 open content 1 accordionitem accordionitem title section 2 content 2 accordionitem accordionitem title section 3 content 3 accordionitem accordion refer to component index md component index md for component api documentation preprocessors carbon preprocess svelte https github com carbon design system carbon preprocess svelte is a collection of svelte preprocessors for carbon sh yarn yarn add d carbon preprocess svelte npm npm i d carbon preprocess svelte pnpm pnpm i d carbon preprocess svelte optimizeimports optimizeimports is a script preprocessor that rewrites base imports from carbon components icons pictograms packages to their source svelte code paths this can greatly speed up compile times during development while preserving typeahead and autocompletion hinting offered by integrated development environments ide like vscode the preprocessor optimizes imports from the following packages carbon components svelte https github com carbon design system carbon components svelte carbon icons svelte https github com carbon design system carbon icons svelte carbon pictograms svelte https github com carbon design system carbon pictograms svelte before after diff import button from carbon components svelte import add16 from carbon icons svelte import airplane from carbon pictograms svelte import button from carbon components svelte src button button svelte import add16 from carbon icons svelte lib add16 svelte import airplane from carbon pictograms svelte lib airplane svelte usage js svelte config js import optimizeimports from carbon preprocess svelte export default preprocess optimizeimports svelte preprocess should be invoked before any preprocessor from carbon preprocess svelte diff svelte config js import sveltepreprocess from svelte preprocess import optimizeimports from carbon preprocess svelte export default preprocess sveltepreprocess optimizeimports examples examples rollup examples rollup examples sveltekit examples sveltekit examples vite examples vite examples webpack examples webpack typescript support typescript definitions types are generated by sveld https github com carbon design system sveld contributing refer to the contributing guidelines contributing md changelog changelog md license apache 2 0 license npm https img shields io npm v carbon components svelte svg color 262626 style for the badge npm url https npmjs com package carbon components svelte | carbon-design-system svelte design-system carbon svelte-components component-library typescript ui-library typescript-definitions ui-components | os |
polaris | div align center a href https polaris shopify com img src https github com shopify polaris blob main documentation readme png raw true alt a div polaris build contribute evolve shape the merchant experience for shopify s core product the admin storybook https shields io badge storybook white logo storybook style flat https storybook polaris shopify com npm version https img shields io npm v shopify polaris svg label shopify polaris https www npmjs com package shopify polaris ci https github com shopify polaris workflows ci badge svg https github com shopify polaris actions query branch 3amain prs welcome https img shields io badge prs welcome brightgreen svg https github com shopify polaris blob main github contributing md your first pull request status owner help active shopify polaris new issue https github com shopify polaris issues new about this repo the shopify polaris repository is an intergalactic https www youtube com watch v qoryo0atb6g monorepo made up of npm packages vscode extensions and websites sh polaris documentation documentation for working in the monorepo polaris for vscode vs code extension for polaris polaris icons icons for polaris polaris react components for shopify polaris package polaris tokens design tokens for polaris polaris shopify com documentation website stylelint polaris rules for custom property usage and mainline coverage commands install dependencies and build workspaces sh yarn yarn build run a command one workspace run commands from a selected workspace using turbo run command filter workspace https turborepo org docs core concepts filtering flag command runs yarn turbo run dev filter shopify polaris open the react component storybook yarn turbo run dev filter polaris shopify com open polaris shopify com nextjs site all workspaces run commands across all workspaces this uses turbo run command https turborepo org docs reference command line reference turbo run task command runs yarn changeset adds a new changelog entry https github com shopify polaris blob main github contributing md adding a changeset yarn lint lints all workspaces yarn test tests all workspaces yarn type check build types and check for type errors yarn clean remove generated files yarn format format files with prettier contribute to this repo pull requests are welcome see the contribution guidelines https github com shopify polaris blob main github contributing md for more information licenses source code is under a custom license https github com shopify polaris blob main license md based on mit the license restricts polaris usage to applications that integrate or interoperate with shopify software or services with additional restrictions for external stand alone applications all icons and images are licensed under the polaris design guidelines license agreement https polaris shopify com legal license | shopify-polaris react typescript design-system component-library design-systems design-tokens figma-plugin icons vscode-extension | os |
SI-507-Final-Project | si 507 final project fall 2018 si 507 final project p u msu engineering staff database u p p b data extraction method b crawling and scraping p p b data source b https www egr msu edu people directory all p p b external credit b base html template with bootstrap navbar code used from template provided in si664 creator instructor anthony whyte p b cached data b cache json br b formatted scraping data b staff json br b sql database b staff db excluded from repo but will be generated when project is run p b program purpose b 1 crawl and scrape msu s engineering staff directory a href https www egr msu edu people directory all data source a 2 insert scraping data into sql database 3 generate a flask website with sql database query results populating the website s content b how to run b 1 clone this repository or duplicate the files and directories contained within it ensure that you also have the contents of templates and static 2 launch a virtual machine in your terminal 3 install requirements txt 4 decide how quickly you d like the flask website to deploy based on how much data this program is processing slow 18 minutes with new crawling and scraping requests delete cache json and staff json from the project directory medium 2 minutes with retrieving crawling and scraping data from cache delete staff json fast 5 seconds with immediately generating the database from json and deploying flask app with query info fed to routes keep both cache json and staff json 5 launch si507 final proj py 6 navigate to http 127 0 0 1 5000 in your browser when prompted b test cases b 1 ensure that steps 1 3 in how to run have been completed 2 launch si507 final proj test py comments explaining tests are contained in the py file there are no other file dependencies for the test file except for the si507 final proj py file b due to tests that pull data from cache or even make new requests if no cache exists tests take 2 minutes to run b b detailed workflow b more granular comments in si507 final proj py and si507 final proj test py 1 check for cache and open it for future processing if it exists create a new dictionary that will hold contents for a cache of a request get from the data source 2 try to set up a sql database based on a parsed json file generated from a previous request if that json file doesn t exist causing the database setup to fail then the program will call a function that is meant to 3 get the contents of the engineering directory website if a page has already been cached retrieve the page contents from the cache parse the page contents with beautiful soup to get data points tied to a staff member first name last name title email address etc store these data points as class attributes for staff members and return a list of these class instances to the program body 4 format each class instance for a staff member for writing to a json file this json file is a consolidated record of all of the data points we were looking for about a staff member 5 set up a sql database based on the formatted json file produced earlier data is normalized with if elif statements due to inconsistent manual entry from the data source the database is split into 3 tables staff buildings and departments the staff table has foreign key relationships with building s and department s primary keys 6 based on the information loaded into the sql database deploy a flask app locally to http 127 0 0 1 5000 b final product overview b the flask website i have created contains the following routes 1 index a simple homepage with a basic description of the website 2 staff an exhaustive list of all engineering staff members with their departments next to their name the number of staff members is shown at the top header 3 profile contains a staff member s detailed information name phone email etc 4 building this is a list of buildings where engineering staff members have offices a plotly bar chart shows how many staff members are in each building a number of buildings is shown above the list 5 building staff this is a list of staff members in a building it features a plotly map with the location of the building noted b the mapbox access token exposed in the template is a read only privileged public facing token b 6 dept this is a list of all departments that engineering staff members are employed under a plotly bar chart shows the distribution of staff members to departments the number of departments is also displayed 7 dept staff this is a list of all of the staff members aligned to a specific department the name of the department featured is also displayed | server |
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refinitiv-ui | element framework ef test https github com refinitiv refinitiv ui actions workflows test coverage yml badge svg https github com refinitiv refinitiv ui actions workflows test coverage yml nightly test https github com refinitiv refinitiv ui actions workflows test nightly yml badge svg event schedule https github com refinitiv refinitiv ui actions workflows test nightly yml production release https github com refinitiv refinitiv ui actions workflows prod release yml badge svg branch v7 https github com refinitiv refinitiv ui actions workflows prod release yml element framework is lseg workspace s design system components that provides components and tooling to help product teams work faster and more efficiently documentation getting started and usage guide are available from this documentation https ui refinitiv com packages package version change log refinitiv ui configurations https github com refinitiv refinitiv ui tree v7 packages configurations npm version https badgen net npm v refinitiv ui configurations https www npmjs com package refinitiv ui configurations change log https badgen net badge icon changelog grey icon git label https github com refinitiv refinitiv ui blob v7 packages configurations changelog md refinitiv ui core https github com refinitiv refinitiv ui tree v7 packages core npm version https badgen net npm v refinitiv ui core https www npmjs com package refinitiv ui core change log https badgen net badge icon changelog grey icon git label https github com refinitiv refinitiv ui blob v7 packages core changelog md refinitiv ui demo block https github com refinitiv refinitiv ui tree v7 packages demo block npm version https badgen net npm v refinitiv ui demo block https www npmjs com package refinitiv ui demo block change log https badgen net badge icon changelog grey icon git label https github com refinitiv refinitiv ui blob v7 packages demo block changelog md refinitiv ui elemental theme https github com refinitiv refinitiv ui 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https badgen net badge icon changelog grey icon git label https github com refinitiv refinitiv ui blob v7 packages translate changelog md refinitiv ui utils https github com refinitiv refinitiv ui tree v7 packages utils npm version https badgen net npm v refinitiv ui utils https www npmjs com package refinitiv ui utils change log https badgen net badge icon changelog grey icon git label https github com refinitiv refinitiv ui blob v7 packages utils changelog md create efx https github com refinitiv refinitiv ui tree v7 packages create efx npm version https badgen net npm v create efx https www npmjs com package create efx change log https badgen net badge icon changelog grey icon git label https github com refinitiv refinitiv ui blob v7 packages create efx changelog md license information see license license md support for questions or issues please refer to documentation see documentation section above and q a https community developers refinitiv com index html forum on developer community which supported by an active developer community contributing see contributing contributing md sponsoring services picture source media prefers color scheme dark srcset documents resources images browserstack darkmode svg source media prefers color scheme light srcset documents resources images browserstack lightmode svg img alt browserstack logo src documents resources images browserstack lightmode svg width 200 height 85 picture browserstack https www browserstack com thank you for a great service let us test on real browsers | accessibility design-system lit typescript ui webcomponents monorepo | os |
MCW-IoT-and-the-Smart-City | iot and the smart city this workshop is archived and is no longer being maintained content is read only fabrikam city council has conducted a six month study of new and emerging technologies that can improve the lives of its citizens being the largest city in the us the challenges most cities face are compounded by scale many of these challenges revolve around city traffic and public transportation at the conclusion of their study the city council realized that the internet of things iot is widely available and is becoming more integrated into our daily lives fabrikam city can capitalize on the wide availability and affordability of iot devices this means physical things like traffic lights and vehicles will be able to collect and share data by connecting to the internet through analytics cities can turn this data into intelligent information that will change the way the world works june 2020 target audience application developer data engineer abstracts workshop in this workshop you will use the unique benefits of the internet of things iot to build a smart city solution to help improve traffic and public transportation in fabrikam city use a combination of the power of the cloud along with iot edge devices to provide anomaly detection from city buses including engine anomaly alerts and aggressive driving detection as well as location broadcasting to update bus route status traffic lights will also receive new iot devices that can help detect maintenance and performance issues such as voltage irregularities easily view all of this information through a centralized reporting dashboard provided by the azure remote monitoring accelerator web application use the iot remote monitoring accelerator to manage and simulate iot devices set alerts and view data on a map by the end of this workshop you will learn to use iot hub to manage iot devices configure and run the iot remote monitoring accelerator to provision manage and simulate telemetry for iot devices use azure iot edge to collect vehicle telemetry data detect anomalies and send the summarized data to azure iot hub as needed in addition you ll route critical alerts to a service bus queue create an azure function that extracts critical alerts from the service bus queue and stores them in cosmos db as well as use azure time series insights to store visualize and query the large amounts of time series data generated by various iot devices whiteboard design session this whiteboard design session is designed to help you gain a better understanding of implementing architectures that use iot data in new and innovative ways you will design an iot workflow that begins with a local iot edge device that collects and analyzes data from various sensors that are connected to it and intelligently aggregates and sends that data to the cloud when anomalies are detected other non critical data is uploaded to cloud storage when a viable internet connection is available once the data is uploaded it is sent to a time series database for rapid analysis alongside other classes of iot data to spot and act on correlated information in real time you will also configure alerts when certain thresholds are exceeded and configure a remote monitoring solution that manages and sends control messages to iot devices located within the city limits at the end of this whiteboard design session you will be better able to design an end to end iot solution that processes and analyzes data both in the field and in the cloud hands on lab we have removed the iot and the smart city lab documents due to technical issues please look for an update in the upcoming months azure services and related products azure iot hub azure iot edge azure stream analytics azure time series insights azure storage azure event hub azure service bus visual studio visual studio code azure solutions internet of things related references mcw https microsoftcloudworkshop com help support we welcome feedback and comments from microsoft smes learning partners who deliver mcws having trouble first verify you have followed all written lab instructions including the before the hands on lab document next submit an issue with a detailed description of the problem do not submit pull requests our content authors will make all changes and submit pull requests for approval if you are planning to present a workshop review and test the materials early we recommend at least two weeks prior please allow 5 10 business days for review and resolution of issues | server |
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python-ml-course | curso completo de machine learning data science en python https www udemy com course machinelearningpython requisitos se necesitan conocimientos de matem ticas de bachillerato o conocimientos b sicos de estad stica se recomienda saber programar un poco para enfocarse en aprender las t cnicas de an lisis en python aunque no es totalmente necesario descripci n te suenan las palabras machine learning o data scientist te pica la curiosidad de para qu sirven estas t cnicas o por qu empresas de todo el mundo pagan un sueldo de 120 000 hasta 200 000 al a o a un cient fico de datos pues este curso est pensado y dise ado por todo un profesional del mundo del data science como es juan gabriel gomila de modo que os va a compartir todo su conocimiento y ayudaros a entender la teor a tan compleja sobre las matem ticas que tiene detr s los algoritmos y librer as de programaci n con python para convertiros en todo unos expertos a pesar de que no teng is experiencia previa veremos paso a paso como empezar a trabajar con conceptos y algoritmos del mundo del machine learning con cada nueva clase y secci n que completes tendr s unas nuevas habilidades que te ayudar n a entender este mundo tan completo y lucrativo que puede ser esta rama del data science tambi n decirte que este curso es muy divertido en la l nea de juan gabriel gomila y que aprender s y te divertir s mientras vas aprendiendo acerca de t cnicas de machine learning con python en particular los temas que trabajaremos ser n los siguientes parte 1 instalaci n de python y paquetes necesarios para data science machine learning y visualizaci n de los datos parte 2 evoluci n hist rica del an lisis predictivo y el machine learning parte 3 pre procesado y limpieza de los datos parte 4 manejo de datos y data wrangling operaciones con datasets y distribuciones de probabilidad m s famosas parte 5 repaso de estad stica b sica intervalos de confianza contrastes de hip tesis correlaci n parte 6 regression lineal simple regresi n lineal m ltiple y regresi n polinomial variables categ ricas y tratamiento de outliers parte 7 clasificaci n con regresi n log stica estimaci n con m xima verosimititud validaci n cruzada k fold cross validation curvas roc parte 8 clustering k means k medoides dendrogramas y clustering jer rquico t cnica del codo y an lisis de la silueta parte 9 clasificaci n con rboles bosques aleatorios t cnicas de poda entrop a maximizaci n de la informaci n parte 10 support vector machines para problemas de clasificaci n y regresi n kernels no lineales reconocimiento facial c mo funciona csi parte 11 los k vecinos m s cercanos decisi n por mayor a programaci n de algoritmos de machine learning vs librer as de python parte 12 an lisis de componentes principales reducci n de la dimensi n lda parte 13 deep learning reinforcement learning redes neuronales artificiales y convolucionales y tensor flow adem s en el curso encontrar s ejercicios datasets para practicar basados en ejemplos de la vida real de modo que no solo aprender s la teor a con los v deos si no tambi n a practicar para construir tus propios modelos de machine learning y como no olvidar que tendr s un github con todo el c digo fuente en python para descargar y utilizar en todos tus proyectos as que no esperes m s y ap ntate al curso de machine learning m s completo y til del mercado espa ol para qui n es este curso cualquiera interesado en aprender machine learning estudiantes que tienen un conocimiento de matem ticas que quieran aprender acerca del machine learning con python usuarios intermedios que conocen los fundamentos de machine learning como los algoritmos cl sicos de regresi n lineal o log stica pero buscan aprender m s y explorar otros campos del aprendizaje estad stico programadores que les guste el c digo y que est n interesados en aprender machine learning para aplicar dichas t cnicas a sus datasets estudiantes de universidad que busquen especializarse y aprender a ser data scientists analistas de datos que quieran ir m s all gracias al machine learning cualquier persona que no est satisfecha con su propio trabajo y busque empezar a trabajar como un data scientist profesional cualquier persona que quiera dar valor a adido a su propia empresa utilizando las potentes herramientas de machine learning | python machine-learning data-science svm regression-models artificial-neural-networks | ai |
audetect | audetect recognizes facial expressions using computer vision given a series of input images video returns a list of active facial action units http www cs cmu edu face facs htm methods are based loosely on valstar pantic 2006 http ibug doc ic ac uk media uploads documents cvpr06 valstarpantic final pdf a boring video demonstration http www youtube com watch v l1m 9wq dnk of the program slowly doing its thing requirements audetect has only been tested with python 2 7 opencv 2 4 7 installation python setup py install running audetect interactive py help should give you a good start | ai |
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friday-design-system | initial page getting super powers becoming a super hero is a fairly straight forward process give me super powers hint style info super powers are granted randomly so please submit an issue if you re not happy with yours endhint once you re strong enough save the world code title hello sh bash ain t no code for that yet sorry echo you got to trust me on this i saved the world endcode | chrome angular html-css reactjs | os |
RCRNet-Pytorch | rcrnet pytorch img align right src docs motorcross jump gif width 250px this repository contains the pytorch implementation for semi supervised video salient object detection using pseudo labels br pengxiang yan guanbin li yuan xie zhen li chuan wang tianshui chen liang lin br iccv 2019 project page https kinpzz com publication iccv19 semi vsod arxiv https arxiv org abs 1908 04051 cvf open access http openaccess thecvf com content iccv 2019 html yan semi supervised video salient object detection using pseudo labels iccv 2019 paper html br usage requirements this code is tested on ubuntu 16 04 python 3 6 via anaconda3 pytorch 0 4 1 cuda 9 0 install pytorch 0 4 1 conda install pytorch 0 4 1 torchvision 0 2 1 cuda90 c pytorch install other packages pip install pyyaml 3 13 addict 2 2 0 tqdm 4 28 1 scipy 1 1 0 datasets our proposed rcrnet is evaluated on three public benchmark vsod datsets including vos http cvteam net projects tip18 vos vos html davis https davischallenge org version 2016 480p and fbms https lmb informatik uni freiburg de resources datasets please orginaize the datasets according to config datasets yaml and put them in data datasets or you can set argument data to the path of the dataset folder evaluation comparison with state of the art comp video sota docs comp video sota png if you want to compare with our method option 1 you can download the saliency maps predicted by our model from google drive https drive google com open id 1fey3gdnbs lubt0udwwpa3fl9yhi4vxr baidu pan https pan baidu com s 1oxbr9qxyf 8vvilvv5kcpg passwd u079 option 2 or you can use our trained model for inference the weights of trained model are available at google drive https drive google com open id 1tsmi1dykivuzuxe1aw7t ygmcumjynn baidu pan https pan baidu com s 1ploajl6x s29i 4mresusq passwd 6pi3 then run the following command for inference vos cuda visible devices 0 python inference py data data datasets dataset vos split test davis cuda visible devices 0 python inference py data data datasets dataset davis split val fbms cuda visible devices 0 python inference py data data datasets dataset fbms split test then you can evaluate the saliency maps using your own evaluation code training if you want to train our proposed model from scratch including using pseudo labels please refer to our paper and the training instruction docs training instruction md carefully citation if you find this work helpful please consider citing inproceedings yan2019semi title semi supervised video salient object detection using pseudo labels author yan pengxiang and li guanbin and xie yuan and li zhen and wang chuan and chen tianshui and lin liang booktitle proceedings of the ieee international conference on computer vision pages 7284 7293 year 2019 acknowledge thanks to the third party libraries deeplab pytorch https github com kazuto1011 deeplab pytorch by kazuto1011 flownet2 pytorch https github com nvidia flownet2 pytorch by nvidia pytorch segmentation toolbox https github com speedinghzl pytorch segmentation toolbox by speedinghzl non local pytorch https github com alexhex7 non local pytorch by alexhex7 | video-object-segmentation video-saliency iccv2019 pytorch | ai |
iotop | iotop is your linux server too slow or load is too high one of the possible causes of such symptoms may be high io input output waiting time which basically means that some of your processes need to read or write to a hard drive while it is too slow and not ready yet serving data for some other processes common practice is to use iostat x in order to find out which block device hard drive is slow but this information is not always helpful it could help you much more if you knew which process reads or writes the most data from your slow disk so you could renice it using ionice or even kill it iotop identifies processes that use high amount of input output requests on your machine it is similar to the well known top utility but instead of showing you what consumes cpu the most it lists processes by their io usage inspired by iotop python script from guillaume chazarain rewritten in c by vyacheslav trushkin and improved by boian bonev so it runs without python at all iotop is licensed gpl 2 0 packaging status https repology org badge tiny repos iotop c svg https repology org project iotop c versions sample screenshot iotop screenshot sample screenshot png how to install from binary package many linux distributions already include this program under the name iotop c if your distribution is relatively new chances are that it already has iotop packaged follow these instructions in case it is not available follow the how to build from source how to build from source instructions details summary debian devuan ubuntu other derivatives summary nbsp use the following command note that y disables confirmation prompts sudo apt install iotop c y details details summary fedora summary nbsp use the following command note that y disables confirmation prompts sudo dnf install iotop c y details details summary centos 7 centos 8 rhel 7 rhel 8 rhel 9 summary nbsp use the following commands note that y disables confirmation prompts sudo yum install epel release y sudo yum install iotop c y details details summary void linux summary nbsp use the following command sudo xbps install iotop c details how to build from source please note that the installation and the usage of this program require root access details summary debian devuan ubuntu other derivatives summary nbsp use the following commands note that y disables confirmation prompts apt install git build essential libncurses dev libncursesw5 dev pkg config y git clone https github com tomas m iotop cd iotop make j details details summary fedora summary nbsp use the following commands note that y disables confirmation prompts dnf install git gcc make ncurses devel pkgconfig y git clone https github com tomas m iotop cd iotop make j details details summary centos 8 rhel 8 rhel 9 summary nbsp use the following commands note that y disables confirmation prompts yum install git gcc make ncurses devel pkgconfig y git clone https github com tomas m iotop cd iotop make j details details summary centos 7 rhel 7 summary nbsp note on centos 7 rhel 7 gcc does not support wdate time and needs a wno strict overflow to suppress a pile of bogus warnings use the following commands note that y disables confirmation prompts yum install git gcc make ncurses devel pkgconfig y git clone https github com tomas m iotop cd iotop sed i s wdate time wno strict overflow makefile make j details details summary void linux summary nbsp use the following commands xbps install git base devel ncurses devel git clone https github com tomas m iotop cd iotop make j details how to install as a system command sudo make install how to update to latest version cd iotop git checkout master git pull make clean make j options v version show program s version number and exit h help show this help message and exit h help type type set type of interactive help none win or inline o only only show processes or threads actually doing i o no only show all processes or threads b batch non interactive mode n num iter num number of iterations before ending infinite d sec delay sec delay between iterations 1 second p pid pid pid processes threads to monitor all u user user user users to monitor all p processes only show processes not all threads threads show all threads a accumulated show accumulated i o instead of bandwidth no accumulated show bandwidth a accum bw show accumulated bandwidth no accum bw show last iteration bandwidth k kilobytes use kilobytes instead of a human friendly unit no kilobytes use human friendly unit t time add a timestamp on each line implies batch c fullcmdline show full command line no fullcmdline show program names only 1 hide pid hide pid tid column show pid show pid tid column 2 hide prio hide prio column show prio show prio column 3 hide user hide user column show user show user column 4 hide read hide disk read column show read show disk read column 5 hide write hide disk write column show write show disk write column 6 hide swapin hide swapin column show swapin show swapin column 7 hide io hide io column show io show io column 8 hide graph hide graph column show graph show graph column 9 hide command hide command column show command show command column g type grtype type set graph data source io r w rw and sw r reverse graph reverse graph column direction no reverse graph do not reverse graph column direction q quiet suppress some lines of header implies batch x dead x show exited processes threads with letter x no dead x show exited processes threads with background e hide exited hide exited processes show exited show exited processes l no color do not colorize values color colorize values si use si units of 1000 when printing values no si use non si units of 1024 when printing values threshold 1 10 threshold to switch to next unit ascii disable using unicode unicode use unicode drawing chars w write write preceding options to the config and exit contribute iotop was originally written by vyacheslav trushkin in 2014 distributed by tomas matejicek and later improved by boian bonev iotop is maintaned on github at https github com tomas m iotop the preferred way to contribute to the project is to file a pull request at github contacts of current maintainers are tomas matejicek lt tomas slax org mailto tomas slax org gt boian bonev lt bbonev ipacct com mailto bbonev ipacct com gt the iotop community gathers in iotop on libera chat ircs irc libera chat 6697 iotop https web libera chat iotop notable contributions ordered by time of last contribution leah neukirchen lt leah vuxu org mailto leah vuxu org gt void linux packaging and testing vitaly chikunov lt vt altlinux org mailto vt altlinux org gt alt linux packaging and testing matteo bernardini lt ponce slackbuilds org mailto ponce slackbuilds org gt slackbuilds packaging and testing jonathan papineau lt jonathan jontech app mailto jonathan jontech app gt opensuse packaging and testing vladi belperchinov shabanski lt cade noxrun com mailto cade noxrun com gt scroller code improvement multiple reviews and ideas alexander monakov lt amonakov ispras ru mailto amonakov ispras ru gt improvement of ncurses color handling alexander rezvov lt alex rezvov ru mailto alex rezvov ru gt nixos packaging and testing einprofispieler readme md build system improvements paul wise lt pabs debian org mailto pabs debian org gt debian packaging man page multiple reviews and ideas rumen jekov lt rvjekov gmail com mailto rvjekov gmail com gt arch linux packaging and testing milan p stani lt mps arvanta net mailto mps arvanta net gt alpine linux packaging and testing arthur zamarin lt arthurzam gentoo gmail com mailto arthurzam gentoo gmail com gt gentoo packaging and testing yuriy m kaminskiy lt yumkam gmail com mailto yumkam gmail com gt code fixes and improvements alicektx lt alicekot13 gmail com mailto alicekot13 gmail com gt documentation improvements filip kofron lt filip kofron cz gmail com mailto filip kofron cz gmail com gt build system improvements thanks this project is what it is now because the steam you have put into it nb in case you have contributed to the project and do not see your name in the list please note that the above list is updated manually and it is an omission notify the maintainers to fix it | server |
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Hands-On-Mobile-Development-with-.NET-Core | hands on mobile development with net core this is the code repository for hands on mobile development with net core published by packt build cross platform mobile applications with xamarin visual studio 2019 and net core 3 what is this book about net core is the general umbrella term used for microsoft s cross platform toolset xamarin used for developing mobile applications is one of the app model implementations for net core infrastructure in this book you will learn how to design architect and develop highly attractive maintainable efficient and robust mobile applications for multiple platforms including ios android and uwp with the toolset provided by microsoft using xamarin net core and azure cloud services this book will take you through various phases of application development with xamarin from environment setup design and architecture to publishing using real world scenarios throughout the book you will learn how to develop mobile apps using xamarin xamarin forms and net standard implement a webbased backend composed of microservices with net core using various azure services including but not limited to azure app services azure active directory notification hub logic apps and azure functions cognitive services create data stores using popular database technologies such as cosmos db sql and realm this book covers the following exciting features implement native applications for multiple mobile and desktop platforms understand and use various azure services with net core make use of architectural patterns designed for mobile and web applications understand the basic cosmos db concepts understand how different app models can be used to create an app service if you feel this book is for you get your copy https www amazon com dp 1789538513 today a href https www packtpub com utm source github utm medium banner utm campaign githubbanner img src https raw githubusercontent com packtpublishing github master github png alt https www packtpub com border 5 a instructions and navigations the chapters dealing with azure services would require an azure subscription to be created with current subscription model when an azure free subscription is created you can get 200 credit for premium services 12 months of free usage for certain services and a set of services are free without limitation net core and xamarin development chapters would require an ide such as visual studio 2019 and or visual studio for mac both of these applications are available with a freemium model in other words the community edition for both applications are available with certain limitations visual studio code can be an open source alternative for these ides when dealing with azure service implementations if the development environment is setup on a macos workstation then windows vm might be required for certain development and deployment scenarios while alternatives are listed above additional options are available for these type of a setup both of the alternatives that is parallels and vmware have trial versions available online saas product offers such as azure devops and visual studio app centre are also freemium products nevertheless the feature set offered with the free subscription should be enough for the majority of the samples outlined in this book all of the code is organizes into two projects that is client and web the code will look like the following namespace firstxamarinformsapplication public partial class mainpage contentpage public mainpage initializecomponent bindingcontext new mainpageviewmodel following is what you need for this book copy and paste the audience section from the epic with the following software and hardware list you can run all code files present in the book chapter 1 15 software and hardware list chapter software required os required hardware specifications free proprietary all xamarin development tools windows system with 16gb ram all xamarin development tools mac os x system with 16gb ram all optional vmware mac os x system with 16gb ram 88 95 euros all optional parallels mac os x system with 16gb ram 79 99 all xcode mac os x all visual studio for mac mac os x proprietary all visual studio2017 2019 windows proprietary all visual studio code windows mac os x 9 docker desktop windows mac os x all net core sdk windows mac os x we also provide a pdf file that has color images of the screenshots diagrams used in this book click here to download it https www packtpub com sites default files downloads 9781789538519 colorimages pdf related products paste books from the other books you may enjoy section hands on domain driven design with net core packt https www packtpub com catalog product view id 55713 s application development 252fhands domain driven design net utm source github utm medium repository utm campaign 9781788834094 amazon https www amazon com dp 1788834097 xamarin forms projects packt https www packtpub com application development xamarinforms projects utm source github utm medium repository utm campaign 9781789537505 amazon https www amazon com dp 1789537509 get to know the author can bilgin currently works with authority partners inc as a solution architect he has been working in the software industry primarily with microsoft technologies for over a decade and has been recognized as a microsoft most valuable professional for his technical contributions between 2014 and 2018 in this period he took key roles in projects for high profile clients using technologies such as biztalk sharepoint dynamics crm xamarin wcf azure serverless and other web cloud technologies he is passionate about mobile and iot development using the modern tools available for developers he shares his experience on his blog social media and through speaking engagements in local and international community events suggestions and feedback click here https docs google com forms d e 1faipqlsdy7datc6qmel81fiuuymz0wy9vh1jhkvpy57oimekgqib ow viewform if you have any feedback or suggestions download a free pdf i if you have already purchased a print or kindle version of this book you can get a drm free pdf version at no cost br simply click on the link to claim your free pdf i p align center a href https packt link free ebook 9781789538519 https packt link free ebook 9781789538519 a p | front_end |
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mini_blockchain | mini blockchain in python merkle spv kademlia p2p https shuwoom com p 916 miniblockchain1 miniblockchain1 jpg miniblockchain2 miniblockchain2 jpg miniblockchain3 miniblockchain3 jpg 1 2 step1 3 demo 3 python run py p 5000 python run py p 5001 python run py p 5002 step2 python simulation test py step3 json api json api api 1 http 127 0 0 1 5001 height code 0 value 2 2 http 127 0 0 1 5001 balance address 3q7kkthjr5qct7hm189akvtqyls8 address 3q7kkthjr5qct7hm189akvtqyls8 balance 24 3 http 127 0 0 1 5001 block info height 1 current hash 00003b4ff8851ab57625b8d6a432c9288659ce91f52a5b1854b37a34c07ffee8 difficulty 4 index 0 merkleroot 24b486df77c70ba076f92e1ccd078f8073d596c73a29baf0a8f3aea948a54815 nonce 7534 previous hash 00000000000000000000000000000000000000000000000000000000000000 timestamp 1496518102 transactions amount 0 receivers receiver 23dvz2mzroghqk4vsudcvsvjdevb value 100 senders timestamp 1496518102 txid ab9d943d8c126189f80484a0c8ade846038797968bf90fd1ed9e88f2f46f54fa 4 http 127 0 0 1 5000 transactions new amount 1 sender u 23dvz2mzroghqk4vsudcvsvjdevb receiver u 2dgzlqjgwkhdt3etnf3tfa9m4zpk message new transaction been created successfully current transactions timestamp 1538373019 txouts value 30 scriptpubkey op dup op hash160 752f3a7934aa60d041250346e24b1d7a2886dbb0 op equalverify op checksig value 14 scriptpubkey op dup op hash160 ac280f709f81ec4eca086f1abfd0f3bec8baf395 op equalverify op checksig txins prev tx out idx 1 pubkey hash ac280f709f81ec4eca086f1abfd0f3bec8baf395 prev txid 2f096e332b2371cd141d1f279c35fb820e3e5256c1a071c5a49636c2fcd9be3d signature e751d626ef0c147455ef0487b85f108ba56be57575f5133341e5e638dc697f94 txid 8851e30bd03cd81b396df1904a17a87b89a30092a92572f7a66fce7a25a634c4 timestamp 1538373058 txouts value 9 scriptpubkey op dup op hash160 752f3a7934aa60d041250346e24b1d7a2886dbb0 op equalverify op checksig value 46 scriptpubkey op dup op hash160 4a879c658a42fc162f8cb3c740a4e0c4b63e80de op equalverify op checksig txins prev tx out idx 0 pubkey hash 4a879c658a42fc162f8cb3c740a4e0c4b63e80de prev txid 2f096e332b2371cd141d1f279c35fb820e3e5256c1a071c5a49636c2fcd9be3d signature 0ff0b888d0dd468f1c6e37d1ab13d17f63747346dc0105b5e4974be71023079f prev tx out idx 0 pubkey hash 4a879c658a42fc162f8cb3c740a4e0c4b63e80de prev txid 72fb55e194e4d7dc71ab020483c61737c6a5b2e2474480cac4187f0633961423 signature de72585b9c7c6a47d1adc2851244232581cc5f3e0a4633d754736677bdea0a57 prev tx out idx 1 pubkey hash 4a879c658a42fc162f8cb3c740a4e0c4b63e80de prev txid 3bc92a17262ce2cc1fe7f34ef946fd10e0b9667f223b697bfaf520e5f443be11 signature 2871832295c53372ee44d9950676cb4675506676a9dce04db54e48b72b40a2b1 txid 252d4e493ff514e87f3c00d9adcb635aba5f7c3b7890b7ccc1e17d73c23d1bf4 timestamp 1538373093 txouts value 10 scriptpubkey op dup op hash160 ac280f709f81ec4eca086f1abfd0f3bec8baf395 op equalverify op checksig value 36 scriptpubkey op dup op hash160 4a879c658a42fc162f8cb3c740a4e0c4b63e80de op equalverify op checksig txins prev tx out idx 1 pubkey hash 4a879c658a42fc162f8cb3c740a4e0c4b63e80de prev txid 252d4e493ff514e87f3c00d9adcb635aba5f7c3b7890b7ccc1e17d73c23d1bf4 signature fc33dea5c178d38c4d98623e7a0fe881b9c6268088788b34c81b4b49a1cbe385 txid 31cabe8dd4c9b7b03b9159409bc1929acbcefe361099bad5839c17cce497af8e timestamp 1538373570 txouts value 1 scriptpubkey op dup op hash160 752f3a7934aa60d041250346e24b1d7a2886dbb0 op equalverify op checksig value 35 scriptpubkey op dup op hash160 4a879c658a42fc162f8cb3c740a4e0c4b63e80de op equalverify op checksig txins prev tx out idx 1 pubkey hash 4a879c658a42fc162f8cb3c740a4e0c4b63e80de prev txid 31cabe8dd4c9b7b03b9159409bc1929acbcefe361099bad5839c17cce497af8e signature adf76d1f32fb122fe2551b3e3059d64d9d11787f58cea37ec8e7ff1b3b540dd7 txid 5bc1e91e8156710706934ee109976a71bdbac04b0d83e081844decb2a4d6ed15 step4 mini blockchain browser nginx www http 127 0 0 1 browser | blockchain |
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msecs-macc-app | keeptime keeptime is an enterprise oriented collaborative time tracker it is composed by two parts an android application and a rails server https github com aserpi msecs macc server server the server acts both as an api backed for the app and as a control panel for system administrators admins can create and modify employees workspaces clients projects and activities and check the current cost for each element app the application is for exclusive use of workers they can change their bill rate and add new schedule items project masters can also create and modify new tasks and assign workers to them | cloud |
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jt-mobile-kit | jt mobile kit todo write a gem description installation add this line to your application s gemfile gem jt mobile kit and then execute bundle or install it yourself as gem install jt mobile kit usage todo write usage instructions here contributing 1 fork it 2 create your feature branch git checkout b my new feature 3 commit your changes git commit am add some feature 4 push to the branch git push origin my new feature 5 create new pull request we need a new baby step readme | front_end |
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rt-node | rt node license https img shields io badge licence apache 202 0 brightgreen svg style flat license rt node is a lightweight javascript framework for rtos also support unix like systems for debugging the following runtime modules are built in timer require utils console n api n api is supported in order to be compatible with different embed javascript engines the following n api features are wip thread safe function dependencies jerryscript deps jerryscript a lightweight javascript engine rv deps rv a tiny event loop library javascript sample speaker js javascript use strict class speaker constructor content this content content say console log this content module exports speaker app js javascript use strict const speaker require speaker const speaker new speaker hello world settimeout speaker say 3000 n api sample javascript use strict the curl module depends on libcurl the source file is sample unix curl c const curl require curl const starttime date now curl get http www example com body console log get body in date now starttime ms body build javascript sources are packaged in src rtnode snapshots c h set js root as your javascript sources root directory for cmake to package them app js is the entry of user code rtnode use cmake https cmake org to build library or samples the easiest way to build is as follows shell cmake b build h djs root your js files root directory make c build j8 the above commands will generate librtnode a in build directory for cross compile add the following flags cmake c compiler full path for c compiler cmake system processor the name of the cpu cmake is building for cmake system name set generic to indicate cross compile here is an example for xtensa toolchain shell cmake b build xtensa h dcmake c compiler xtensa esp32 elf gcc dcmake system processor xtensa dcmake system name generic djs root your js files root directory make c build xtensa j8 sample currently support unix and esp idf build framework for unix like systems shell cmake b build h dsample unix djs root samples djerry profile es2015 subset make c build build rtnode unix rtnode unix run sample for esp idf shell cmake b build espidf h dcmake c compiler xtensa esp32 elf gcc dcmake system processor xtensa dcmake system name generic dsample esp idf djs root samples djerry profile es2015 subset make c build espidf j8 the esp idf products will generate in build espidf rtnode build then use idf py flash to flash the binaries that you just built onto your esp32 board for more information please refer to the esp idf document https docs espressif com projects esp idf en latest get started step 9 flash onto the device license apache 2 0 license | rtos nodejs | os |
LibFinder | libfinder libfinder is a prototype that recommend potential third party libraries for mobile app develoment or enhancement we realize it by two different languages the first one is programmed in matlab with a gui and is proposed in this respository the second one is programmed in python and is deployed as a web service and you can use it through any browsers difference matlab version has a gui and you can choose the libraries your app has invoked then libfinder will give you new recommendations so you d better known your app well before using it python version can analyse your app automaticly even you known nothing about your app then give you some recommendations usage of matlab version needs matlab steps clone and download all files in libfinder change the root folder of matlab to the folder of libfinder type guide in matlab open libfinder m cheers usage of python version needs apk files steps visit http 144 6 225 20 on nectar use libfinder step by step according to the hints cheers | front_end |
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fewd-resources | treehouse front end web development techdegree resources this is a community based list of resources for the front end web development techdegree https www teamtreehouse com want to help and add resources awesome checkout our contributing guidelines contributing md index html html css css javascript javascript general general slack slack career career book recommendations book recommendations project 1 personal profile page project 1 project 2 responsive layout project 2 project 3 online registration form project 3 project 4 interactive photo gallery project 4 project 5 sass style guide project 5 project 6 interactive video player project 6 project 7 game show app project 7 project 8 svg animations project 8 project 9 web app dashboard project 9 project 10 public api project 10 project 11 react flickr gallery project 11 project 12 capstone online portfolio project 12 html html validation https validator w3 org browser support table for html css and js features http caniuse com code guide by mdo http codeguide co standards for developing flexible durable and sustainable html and css css css validation https jigsaw w3 org css validator css tricks https css tricks com css complete guide to flexbox https css tricks com snippets css a guide to flexbox flexbox froggy http flexboxfroggy com a game that helps you practice flexbox css code challenges https 100dayscss com javascript javascript mdn https developer mozilla org en us docs web javascript js hint http jshint com a javascript validator es6 features https github com lukehoban es6features a list of es6 features making it easier to see what s new general treehouse blog http blog teamtreehouse com dirty markup https www 10bestdesign com dirtymarkup great tool for helping to keep your code clean organized and properly indented front end cheatsheets https medium freecodecamp org modern frontend hacking cheatsheets df9c2566c72a overcomming imposter syndrome https medium com learn love code developers how to overcome imposter syndrome 48edee803cf4 overcomming imposter syndrome https medium freecodecamp org clobbering imposter syndrome with your mental searchlight b9df0b2e88eb google s material design guidelines https material io guidelines great for getting a handle on the principles of modern web design google pagespeed tools https developers google com speed pagespeed tools to analyze and optimize your site following web best practices steps to the perfect website layout http www creativebloq com web design steps perfect website layout 812625 a list apart http alistapart com slack how to add channels https get slack help hc en us articles 205239967 browse and join channels formatting messages https get slack help hc en us articles 202288908 format your messages search for messages and files https get slack help hc en us articles 202528808 search for messages and files keyboard shortcuts https get slack help hc en us articles 201374536 slack keyboard shortcuts career how to get your first job in tech https medium com team treehouse how to get your first job in tech 7478a51fc78 awesome article by treehouse founder and ceo ryan carson book recommendations html beginner head first html5 programming https www wickedlysmart com head first html5 javascript beginner head first javascript programming https www wickedlysmart com hfjs intermediate javascript and jquery by jon duckett http javascriptbook com you don t know js es6 beyond by kyle simpson https github com getify you dont know js tree master es6 20 26 20beyond advanced eloquent javascript a modern introduction to programming http amzn to 2gd98k7 javascript the good parts http amzn to 2hb5xej project specific resources project 1 study guide https docs google com document d 1hzjspw2cedqkfe 4k ete56ocihqoxpe1uzfbiivt0w edit text editors https teamtreehouse com library introducing text editors using treehouse workspaces https teamtreehouse com library using treehouse workspaces adding images https teamtreehouse com library adding images to the page set up an html document https teamtreehouse com library set up an html document understanding file paths https teamtreehouse com library understanding file paths anchor tags https teamtreehouse com library introduction to html and css html the structural foundation of web pages and applications anchor tags linking it all up https teamtreehouse com library introduction to html and css adding a new web page linking it all up image tags https teamtreehouse com library introduction to html and css html the structural foundation of web pages and applications image tags adding images https teamtreehouse com library adding images to the page free online image editing tool http www picresize com validation checklist https docs google com document d 1rwlgab3ac0tob8cohx0xzmuy oxa33qjqzh cbs5kdk edit html validator https validator w3 org validate by input css validator https jigsaw w3 org css validator validate by input project 2 study guide https drive google com file d 1qvmox1qixjj7bl0d9ooidbm4jd00vct7 view usp sharing project 3 project 4 project 5 study guide https drive google com file d 1d hznfkwo4gigusceeeqp9joprgvmbrw view usp sharing project 6 study guide https drive google com file d 1mtnjv5xtbywvivc2xmnwf5t2dhxjexxf view usp sharing project 7 project 8 project 9 project 10 project 11 project 12 formspree to receive emails without server support https formspree io | front_end |
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math-for-machine-learning | math for machine learning statistics and math for machine learning and data science | ai |
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udagram-api | udagram frontend udagram api | cloud |
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ESD_Lab1_GUI | esd lab1 gui | os |
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dhivehi_nlp | p align center a href https dhivehi nlp mismaah com target blank img width 100 src https user images githubusercontent com 48324626 114336169 c8ef6100 9b67 11eb 848b 31abf6a68e3b png alt dhivehi nlp logo a p dhivehi nlp natural language processing tools for the dhivehi language demo website to test features https dhivehi nlp mismaah com read the docs https dhivehi nlp mismaah com docs index html installation pip install dhivehi nlp modules tokenizer tokenize text into separate sentences or words tokens stopwords remove stopwords from text and return the resulting tokens stemmer remove suffixes from words to return their root form language models create language models to predict future additions language models will give probability based on selected ngram an ngram is a contiguous sequence of n tokens from the given input text use previously built models to predict future words dictionary get definitions of dhivehi words and the word list definitions obtained from radheef mv corpus collections of various dhivehi texts trigram similarity divides words or phrases into sequences of three consecutive letters placed in a set where the order doesn t matter and duplicates are removed used to find string matches even if certain characters are different or out of order based on similarity value tagger tag words in text according to specified rules or patterns for example tagging words based on which part of speech it belongs to contribution there are many potential improvements to be made to this library whether it be optimizing current modules creating new modules or fixing bugs for instance the stemmer and stopwords modules use a predefined set of rules to perform their operations these rule sets are still incomplete and can be expanded upon to propose any changes simply open a pull request bug reports suggestions questions etc can be done by creating a new issue https github com mismaah dhivehi nlp issues new code formatting is done using black https github com psf black to ensure consistency | natural-language-processing python dhivehi nlp maldives | ai |
ML4NLP | ml4nlp material for the practical seminar machine learning for natural language processing institute of cognitive science osnabr ck university winter term 2018 2019 the master branch contains the basic scripts and examples provided by the lecturer all other branches include the project work done by the students one branch per group in oder to run the code please use the conda environment provided in environment yml execute conda env create f environment yml to install the environment activate it with source activate ml4nlp and deactivate it with source deactivate useful links about the knowledgestore web interface of our knowledgestore instance http knowledgestore2 fbk eu nwr wikinews ui overall structure of the knowledgestore https knowledgestore fbk eu ontologies knowledgestore html additional structure imposed by newsreader https knowledgestore fbk eu ontologies newsreader html rest api https knowledgestore fbk eu ks server http webdocs webdocs html knowledgestore javadoc documentation https knowledgestore fbk eu apidocs index html knowledgestore source code https github com dkmfbk knowledgestore knowledgestore paper https knowledgestore fbk eu files icsc2013 pdf specification of sparql https www w3 org tr sparql11 query more condensed spaqrl reference https www dajobe org 2005 04 sparql sparqlreference 1 8 pdf some slides on spaqrl http www iro umontreal ca lapalme ift6281 sparql 1 1 cheat sheet pdf wikibook on sparql https en wikibooks org wiki sparql installing docker https www digitalocean com community tutorials how to install and use docker on ubuntu 16 04 knwoledgestore docker https github com dkmfbk knowledgestore docker development environment links spyder ide https www spyder ide org installing git https git scm com book en v2 getting started installing git installing git cola https git cola github io downloads html downloading anaconda https www anaconda com download installing miniconda https conda io docs user guide install index html how to deal with conda environments https conda io docs user guide tasks manage environments html markdown syntax https help github com articles basic writing and formatting syntax links about machine learning the secret to good code documentation https www intertech com blog secret to good code documentation getting better at machine learning https medium com rchang getting better at machine learning 16b4dd913a1f how to deliver on machine learning projects https blog insightdatascience com how to deliver on machine learning projects c8d82ce642b0 scikit learn splitting up the data set https scikit learn org stable modules cross validation html scikit learn evaluation metrics https scikit learn org stable modules model evaluation html classification metrics feature engineering https machinelearningmastery com discover feature engineering how to engineer features and how to get good at it scikit learn feature selection https scikit learn org stable modules feature selection html useful machine learning resources wordnet https wordnet princeton edu nltk wordnet interface http www nltk org howto wordnet html framenet https framenet icsi berkeley edu fndrupal nltk framenet interface http www nltk org howto framenet html pretrained word2vec embeddings on googlenews https code google com archive p word2vec | ai |
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blockchain-consensus | readme blockchain consensus encyclopedia more than 84 blockchain consensus described consensus by nick youngson cc by sa 3 0 imagecreator gitbook assets consensus jpg by https www tokens economy com https www tokens economy com and https disruptr ch https disruptr ch visit the book at https tokens economy gitbook io consensus https tokens economy gitbook io consensus donations ethereum 0xc23473b911e86dc614412b3341d1c206abac6996 https etherscan io address 0xc23473b911e86dc614412b3341d1c206abac6996 bitcoin 3erppuflljmraookictn7rqkkqjdws8ype https www blocktrail com btc address 3erppuflljmraookictn7rqkkqjdws8ype | blockchain blockchain-technology consensus consensus-algorithm ethereum bitcoin smart-contracts consensus-protocol proof-of-stake proof-of-authority proof-of-work proof-of-existence dlt | blockchain |
cs733 | cs733 engineering the cloud copyright c jatin khurana all right reserved this package contains file server which manages files this package manages 4 operations on file 1 write 2 read 3 cas compare and swap 4 delete follwoing is the command for each operation write write filename numberofbytes exptime r n contentoffile r n read read filename r n compare and swap cas filename version numberofbytes exptime r n contentoffile r n delete delete filename quickstart first set the variable gppath and gobin and put the cs733 folder inside gopath install the server with the following command go install gopath cs733 assignment1 now executable file would be available in gobin go to bin folder and run the server server now connect the client and perform the above operation specification and assumption 1 server run on port 8080 2 server stoers the file in memory only so when we close the server all data are lost 3 maximum number of bytes in a file should be 1000000000 testing there is a seperate test file with the name basic test go which contains a lot of test cases in order to run these test case run the following command go test gopath cs733 assignment1 it will output ok which means all the test cases are executed successfully | cloud |
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software-policy | category management policy improving the acquisition and management of common information technology software licensing the office of management and budget is accepting public comment on draft guidance to improve the acquisition and management of enterprise software this policy is the second in a series of category management https www whitehouse gov sites default files omb procurement memo simplifying federal procurement to improve performance drive innovation increase savings pdf policies to drive greater performance efficiencies and savings in commonly purchased information technology goods and services the first memo in the series m 16 02 https www whitehouse gov sites default files omb memoranda 2016 m 16 02 pdf addressed the acquisition of laptops and desktops the proposed guidance is now open for public comment on this page the public feedback period will be 30 days starting on december 21 2015 and closing on january 20 2016 following the public feedback period omb will analyze all submitted feedback and revise the policy as necessary public domain this project is in the worldwide public domain license md as stated in contributing contributing md this project is in the public domain within the united states and copyright and related rights in the work worldwide are waived through the cc0 1 0 universal public domain dedication https creativecommons org publicdomain zero 1 0 all contributions to this project will be released under the cc0 dedication by submitting a pull request you are agreeing to comply with this waiver of copyright interest privacy all comments messages pull requests and other submissions received through official white house pages including this github page may be subject to archiving requirements see the https www whitehouse gov privacy for more information developing on the site locally this site uses jekyll http jekyllrb com sass http sass lang com bourbon http bourbon io neat http neat bourbon io and requires ruby 2 x install dependencies with bundler bundle install and run the site with jekyll bundle exec jekyll serve watch if all goes well visit the site at http localhost 4000 | server |
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Project_4 | project 4 information systems and technologies | server |
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livedev | livedev livedev is a development proxy server for golang that allows live reloading it supports multiple server configuration it uses the request s header host field to determine which server the request should be routed to if no match is found the request is routed the default server compatible with go version go1 0 2 features cross platform unobstructive no code change required simple json configuration file multiple server support automated build service dependency change detection autorealod the page when assets js css image html change installation go get u github com qrtz livedev configuration livedev is controlled by a json configuration file port int default 80 proxy port goroot string optional gopath string optional server server a list of server object with the following options goroot string optional server specific goroot for compiling with different go version gopath string optional server specific gopath host string server hostname must be unique port int optional server port target string optional build target the file that contains the main function if target is not in the gopath livedev will attempt to add it by guessing the workspace from the filename when target is ommited the build step is skipped workingdir string optional workingdir specifies the working directory of the server executable if workingdir is empty it defaults to the parent directory of the executable env map optional a map of key value pairs to set as environment variables on the server resources optional a list of resources such as template files any change to these files will cause the server to restart ignore string optional filename pattern to ignore paths string a list of files or directories to monitor assets optional a list of assets such as css javascript image files any change to these files will cause a page to reload ignore string optional filename pattern to ignore paths string a list of files or directories to monitor bin string optional server executable file when absent it default to tmp livedev hostname builder string optional to use a builder other than the go build tool the first element is the command and the rest its arguments startup string optional server startup argument list default bool optinal specifies the default server defaults to the first server in the list startuptimeout int default 5 specifies the time in seconds limit to wait for the server to complete the startup operation in the server configuration block properties can be referred on using property or property variable substutitions along with the configuration properties the process environment variables are also available usage shell livedev c config json config json port 8080 server host dev service1 com port 8081 target projects src serviceone main go workingdir projects src serviceone resources ignore static paths workingdir templates startup host host port port bin projects bin serviceone host dev service2 com env host host port port target projects src servicetwo main go workingdir projects src servicetwo resources ignore static paths workingdir templates bin projects bin servicetwo shell host file 127 0 0 1 dev service1 com dev service2 com dev service1 com url http dev service1 com 8080 the request is forwarded to http dev serviceone com 8081 the server access host and port from the command line argument as specified in the startup property of the configuration go packgage main import flag net net http func main host flag string host localhost host name port flag string port 8081 port flag parse addr net joinhostport host port http listenandserve addr handler dev service2 com url http dev service2 com 8080 the request is forwarded to http dev service2 com port where port is a randomly generated port the server gets access to host and port from environment variables as specified in the env property of the configuration go packgage main import net net http os func main host os getenv host port os getenv port addr net joinhostport host port http listenandserve addr handler live reload livedv uses a deceptively simple protocol to enable live reload it injects a small inline javascript into html pages at the end of the document right before the closing body tag the script opens a websocket connection and reloads the page once the connection is closed live reload events are as follow change to go files rebuild restart the server and close livereload websocket connections change to files listed under resources in the configuration restart the server and close livereload websocket connections change to files listed under assets in the configuration close livereload websocket connections closing livereload connections causes all connected html pages to reload | front_end |
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predix-nodejs-starter | predix development kit nodejs starter application this is simple starter node application that demonstrates user authentication with predix uaa and integration with microservices running locally edit the config json to run the application locally for your uaa client sample development clientid clientid uaauri uaa url base64clientcredential base 64 encoding of clientid secret appurl http localhost 3000 assetzoneid asset zone id for asset service instantiated tagname tag name list to query separated by comma asseturl the asset url to query the tags from https asseturi assettype timeseries zone timeseries zone id for timeseries service instantiated timeseriesurl timeseries to query for data timeseriesuri v1 datapoints uaaurl the uaa uri uaauri predix io note you can encode your clientid secret combination using https www base64encode org or the base64 command on unix mac osx echo n clientid clientsecret base64 install and start local web server npm install node app js or npm start navigate to http localhost 3000 in your web browser debugging debug predix boot node app npm start debug express npm start run sample tests a sample unit test is included which you can run with npm npm test running locally behind a corporate firewall if you are behind a corporate firewall make sure you have the http proxy environment variable set in the same terminal window where you start the server running in the cloud set up the manifest file for cloud deployment 1 copy manifest yml template to my app manifest yml 2 edit the my app manifest yml applications name front end app name memory 128m buildpack nodejs buildpack command debug express node app js command node app js services asset instance service name timeseries instance service name uaa instance service name env node env cloud uaa service label predix uaa clientid client id with timeseries and asset scope base64clientcredential base64 encoding of client id following properties configured only for timeseries winddata service integration assetmachine the asset name pushed to asset service tagname the asset tag pushed to asset service 3 predix push appname f my app manifest yml analytics https predix beacon appspot com ua 82773213 1 predix nodejs starter readme pixel https github com predixdev | front_end |
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q-wifi | q wifi esp8266 esp8266 rtos sdk q iot esp sdk https github com q iot esp8266 rtos sdk esp8266 http q iot cn group 2 app https q iot cn group 2 thread 4 esp8266 app app app ui ui https srv q iot cn app http q iot cn open course 47 3d http q iot cn my course 6 esp8266 stm32 linux | os |
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FYIT_78_IT_Tools | fyit 78 it tools information technology and practices | server |
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carbon | p align center a href https www carbondesignsystem com img alt carbon design system src https user images githubusercontent com 3901764 57545698 ce5f2380 7320 11e9 8682 903df232d7b0 png width 100 a p h1 align center carbon design system h1 carbon is an open source design system built by ibm with the ibm design language as its foundation the system consists of working code design tools and resources human interface guidelines and a vibrant community of contributors p align center a href https github com carbon design system carbon blob master license img src https img shields io badge license apache 2 0 blue svg alt carbon is released under the apache 2 0 license a a href https github com carbon design system carbon actions workflows ci yml img src https github com carbon design system carbon actions workflows ci yml badge svg alt ci workflow status a a href https lerna js org img src https img shields io badge maintained 20with lerna cc00ff svg alt maintained with lerna a a href https github com carbon design system carbon blob master github contributing md img src https img shields io badge prs welcome brightgreen svg alt prs welcome a a href https bestpractices coreinfrastructure org projects 7034 img src https bestpractices coreinfrastructure org projects 7034 badge a a href https discord gg j7jeuektrx img src https img shields io discord 689212587170201628 color 5865f2 alt chat with us on discord a p getting started if you re just getting started check out carbon react packages react we also have community contributed components for the following technologies angular https github com ibm carbon components angular svelte https github com ibm carbon components svelte vue https github com carbon design system carbon components vue web components https github com carbon design system carbon web components if you re trying to find something specific here s a full list of packages that we support package name description carbon react packages react react components and styles carbon styles packages styles sass styles for components carbon elements packages elements ibm design language elements like colors type iconography and more carbon colors packages colors work with ibm design language colors carbon grid packages grid build layouts using the new 16 column grid system carbon icons packages icons iconography assets we also offer support in react packages icons react angular https github com carbon design system carbon icons angular vue packages icons vue and svelte https github com ibm carbon icons svelte carbon pictograms packages pictograms pictogram assets we also offer support in react packages pictograms react and svelte https github com ibm carbon pictograms svelte carbon layout packages layout layout based units and spacing scale carbon motion packages motion productive and expressive motion curves carbon themes packages themes color tokens available in the carbon design system like interactive 01 carbon type packages type new type tokens used alongside ibm plex books documentation see our documentation site here https www carbondesignsystem com developing frameworks react for full how to docs and guidelines contributing github contributing md guidelines for making contributions to this repo migration guides v10 to v11 docs migration v11 md v9 to v10 vanilla packages carbon components docs migration migrate to 10 x md v9 to v10 v6 to v7 react packages react docs migration migrate to 7 x md contributing we re always looking for contributors to help us fix bugs build new features or help us improve the project documentation if you re interested definitely check out our contributing guide github contributing md and our developer guide docs developer handbook md contributors all contributors list start do not remove or modify this section prettier ignore start markdownlint disable table tr td align center a href https github com tay1orjones img src https avatars0 githubusercontent com u 3360588 v 4 s 100 width 100px alt br sub b taylor jones b sub a br a href https github com carbon design system carbon commits author tay1orjones title code a a href https github com carbon design system carbon commits author tay1orjones title documentation a a href a11y tay1orjones title accessibility a td td align center a href https github com tw15egan img src https avatars1 githubusercontent com u 11928039 v 4 s 100 width 100px alt br sub b tj egan b sub a br a href https github com carbon design system carbon commits author tw15egan title code a a href https github com carbon design system carbon commits author tw15egan title documentation a a href infra tw15egan title infrastructure hosting build tools etc a a href https github com carbon design system carbon pulls q is 3apr reviewed by 3atw15egan title reviewed pull requests a a href a11y tw15egan title accessibility a td td align center a href https github com aledavila img src https avatars2 githubusercontent com u 12533409 v 4 s 100 width 100px alt br sub b alessandra davila b sub a br a href https github com carbon design system carbon commits author aledavila title code a a href https github com carbon design system carbon commits author aledavila title documentation a a href https github com carbon design system carbon pulls q is 3apr reviewed by 3aaledavila title reviewed pull requests a a href a11y aledavila title accessibility a td td align center a href https www linkedin com in andrea cardona b647594b img src https avatars2 githubusercontent com u 32720851 v 4 s 100 width 100px alt br sub b andrea n cardona b sub a br a href https github com carbon design system carbon commits author andreancardona title code a a href https github com carbon design system carbon commits author andreancardona title documentation a a href https github com carbon design system carbon pulls q is 3apr reviewed by 3aandreancardona title reviewed pull requests a a href a11y andreancardona title accessibility a td td align center a href https github com francinelucca img src https avatars githubusercontent com u 40550942 v 4 s 100 width 100px alt br sub b francine lucca b sub a br a href https github com carbon design system carbon commits author francinelucca title code a a href https github com carbon design system carbon commits author francinelucca title documentation a a href https github com carbon design system carbon pulls q is 3apr reviewed by 3afrancinelucca title reviewed pull requests a a href a11y francinelucca title accessibility a td td align center a href https github com sstrubberg img src https avatars2 githubusercontent com u 15822070 v 4 s 100 width 100px alt br sub b scott strubberg b sub a br a href https github com carbon design system carbon commits author sstrubberg title code a a href https github com carbon design system carbon commits author sstrubberg title documentation a a href https github com carbon design system carbon pulls q is 3apr reviewed by 3asstrubberg title reviewed pull requests a a href a11y sstrubberg title accessibility a td td align center a href https github com alisonjoseph img src https avatars0 githubusercontent com u 2753488 v 4 s 100 width 100px alt br sub b alison joseph b sub a br a href https github com carbon design system carbon commits author alisonjoseph title code a a href https github com carbon design system carbon commits author alisonjoseph title documentation a a href https github com carbon design system carbon pulls q is 3apr reviewed by 3aalisonjoseph title reviewed pull requests a a href a11y alisonjoseph title accessibility a td tr tr td align center a href https github com aagonzales img src https avatars3 githubusercontent com u 11670886 v 4 s 100 width 100px alt br sub b anna gonzales b sub a br a href design aagonzales title design a a href https github com carbon design system carbon pulls q is 3apr reviewed by 3aaagonzales title reviewed pull requests a td td align center a href https github com laurenmrice img src https avatars3 githubusercontent com u 43969356 v 4 s 100 width 100px alt br sub b lauren rice b sub a br a href design laurenmrice title design a a href https github com carbon design system carbon pulls q is 3apr reviewed by 3alaurenmrice title reviewed pull requests a td td align center a href https github com joshblack img src https avatars1 githubusercontent com u 3901764 v 4 s 100 width 100px alt br sub b josh black b sub a br a href https github com carbon design system carbon commits author joshblack title code a a href https github com carbon design system carbon commits author joshblack title documentation a a href infra joshblack title infrastructure hosting build tools etc a a href https github com carbon design system carbon pulls q is 3apr reviewed by 3ajoshblack title reviewed pull requests a a href a11y joshblack title accessibility a td td align center a href https dakahn netlify com img src https avatars3 githubusercontent com u 40970507 v 4 s 100 width 100px alt br sub b dak b sub a br a href https github com carbon design system carbon commits author dakahn title code a a href https github com carbon design system carbon commits author dakahn title documentation a a href https github com carbon design system carbon pulls q is 3apr reviewed by 3adakahn title reviewed pull requests a a href a11y dakahn title accessibility a td td align center a href https github com jnm2377 img src https avatars0 githubusercontent com u 32556167 v 4 s 100 width 100px alt br sub b josefina mancilla b sub a br a href https github com carbon design system carbon commits author jnm2377 title code a a href https github com carbon design system carbon commits author jnm2377 title documentation a a href https github com carbon design system carbon pulls q is 3apr reviewed by 3ajnm2377 title reviewed pull requests a a href a11y jnm2377 title accessibility a td td align center a href https github com emyarod img src https avatars3 githubusercontent com u 8265238 v 4 s 100 width 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https github com carbon design system carbon pulls q is 3apr reviewed by 3avpicone title reviewed pull requests a a href a11y vpicone title accessibility a td td align center a href https github com jillianhowarth img src https avatars0 githubusercontent com u 20690344 v 4 s 100 width 100px alt br sub b jillianhowarth b sub a br a href content jillianhowarth title content a a href design jillianhowarth title design a a href https github com carbon design system carbon pulls q is 3apr reviewed by 3ajillianhowarth title reviewed pull requests a td td align center a href http turpialcreative img src https avatars0 githubusercontent com u 4718579 v 4 s 100 width 100px alt br sub b ricardo henriquez b sub a br a href https github com carbon design system carbon commits author rjhenriquez title code a a href https github com carbon design system carbon commits author rjhenriquez title documentation a a href https github com carbon design system carbon pulls q is 3apr reviewed by 3arjhenriquez title reviewed pull requests a a href a11y rjhenriquez title accessibility a td td align center a href https github com johnbister img src https avatars3 githubusercontent com u 70543333 v 4 s 100 width 100px alt br sub b johnbister b sub a br a href design johnbister title design a a href https github com carbon design system carbon pulls q is 3apr reviewed by 3ajohnbister title reviewed pull requests a td td align center a href https github com dbrugger img src https avatars1 githubusercontent com u 10086178 v 4 s 100 width 100px alt br sub b dominik brugger b sub a br a href https github com carbon design system carbon commits author dbrugger title code a a href maintenance dbrugger title maintenance a td td align center a href https janhassel de img src https avatars2 githubusercontent com u 28265588 v 4 s 100 width 100px alt br sub b jan hassel b sub a br a href https github com carbon design system carbon commits author janhassel title code a a href https github com carbon design system carbon commits author janhassel title documentation a a href a11y janhassel title accessibility a a href design janhassel title design a td td align center a href https github com alexanderlyon img src https avatars0 githubusercontent com u 17458641 v 4 s 100 width 100px alt br sub b alexander lyon b sub a br a href https github com carbon design system carbon commits author alexanderlyon title code a td tr tr td align center a href https github com rzhekova img src https avatars2 githubusercontent com u 35401262 v 4 s 100 width 100px alt br sub b rosie z b sub a br a href https github com carbon design system carbon commits author rzhekova title code a td td align center a href https nishithp live img src https avatars3 githubusercontent com u 34577844 v 4 s 100 width 100px alt br sub b nishith p b sub a br a href https github com carbon design system carbon commits author nishithp2004 title documentation a td td align center a href https github com echarpibm img src https avatars2 githubusercontent com u 22177887 v 4 s 100 width 100px alt br sub b eric charpentier b sub a br a href https github com carbon design system carbon commits author echarpibm title code a td td align center a href https www linkedin com in luizamendes img src https avatars0 githubusercontent com u 31076607 v 4 s 100 width 100px alt br sub b luiza mendes b sub a br a href https github com carbon design system carbon commits author luizamendes title code a a href maintenance luizamendes title maintenance a td td align center a href https github com akmalhakimi1991 img src https avatars0 githubusercontent com u 10990690 v 4 s 100 width 100px alt br sub b akmal hakimi mohd zamri b sub a br a href https github com carbon design system carbon commits author akmalhakimi1991 title code a td td align center a href https github com sanjitbauli img src https avatars1 githubusercontent com u 272230 v 4 s 100 width 100px alt br sub b sanjitbauli b sub a br a href https github com 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sub a br a href https github com carbon design system carbon commits author metonym title code a a href https github com carbon design system carbon commits author metonym title documentation a td td align center a href https github com rvsia img src https avatars0 githubusercontent com u 32869456 v 4 s 100 width 100px alt br sub b richard v iansk b sub a br a href https github com carbon design system carbon commits author rvsia title code a td td align center a href https github com lee chase img src https avatars0 githubusercontent com u 15086604 v 4 s 100 width 100px alt br sub b lee chase b sub a br a href https github com carbon design system carbon commits author lee chase title code a a href https github com carbon design system carbon commits author lee chase title documentation a td td align center a href https github com goldenfishe img src https avatars3 githubusercontent com u 29215242 v 4 s 100 width 100px alt br sub b anton b sub a br a href https github com carbon design system carbon commits author goldenfishe title code a td td align center a href https github com panpan lin img src https avatars0 githubusercontent com u 22054715 v 4 s 100 width 100px alt br sub b panpan lin b sub a br a href https github com carbon design system carbon commits author panpan lin title documentation a td tr tr td align center a href https github com ashharrison90 img src https avatars0 githubusercontent com u 20999846 v 4 s 100 width 100px alt br sub b ashley harrison b sub a br a href https github com carbon design system carbon commits author ashharrison90 title code a td td align center a href https jendowns com img src https avatars0 githubusercontent com u 9057921 v 4 s 100 width 100px alt br sub b jen downs b sub a br a href https github com carbon design system carbon commits author jendowns title code a a href https github com carbon design system carbon commits author jendowns title documentation a a href a11y jendowns title accessibility a td td align center a href http abdul sen github io portfolio img src https avatars2 githubusercontent com u 38502132 v 4 s 100 width 100px alt br sub b abdul rehman b sub a br a href https github com carbon design system carbon commits author abdul sen title code a td td align center a href https github com dudley ibm img src https avatars1 githubusercontent com u 54119397 v 4 s 100 width 100px alt br sub b michael dudley b sub a br a href design dudley ibm title design a td td align center a href https davidbradshaw us img src https avatars1 githubusercontent com u 8028956 v 4 s 100 width 100px alt br sub b david bradshaw b sub a br a href https github com carbon design system carbon commits author dabrad26 title code a td td align center a href https github com simonfinney img src https avatars2 githubusercontent com u 3846874 v 4 s 100 width 100px alt br sub b simon finney b sub a br a href https github com carbon design system carbon commits author simonfinney title code a a href a11y simonfinney title accessibility a td td align center a href https github com atikenny img src https avatars2 githubusercontent com u 6061509 v 4 s 100 width 100px alt br sub b attila bartha b sub a br a href https github com carbon design system carbon commits author atikenny title code a td tr tr td align center a href https baeharam netlify com img src https avatars0 githubusercontent com u 35518072 v 4 s 100 width 100px alt br sub b b sub a br a href https github com carbon design system carbon commits author baeharam title code a td td align center a href https github com yohanna img src https avatars0 githubusercontent com u 6926228 v 4 s 100 width 100px alt br sub b yohanna gadelrab b sub a br a href https github com carbon design system carbon commits author yohanna title documentation a td td align center a href https asudoh github io img src https avatars1 githubusercontent com u 1259051 v 4 s 100 width 100px alt br sub b akira sudoh b sub a br a href https github com carbon design system carbon commits author asudoh title code a a href https github com carbon design system carbon commits author asudoh title documentation a a href a11y asudoh title accessibility a a href infra asudoh title infrastructure hosting build tools etc a td td align center a href https github com oyin k img src https avatars2 githubusercontent com u 22506709 v 4 s 100 width 100px alt br sub b oyinkan oyetunmibi b sub a br a href https github com carbon design system carbon commits author oyin k title documentation a td td align center a href https github com pbenson322 img src https avatars1 githubusercontent com u 59934268 v 4 s 100 width 100px alt br sub b pbenson322 b sub a br a href https github com carbon design system carbon commits author pbenson322 title documentation a td td align center a href https github com abbeyhrt img src https avatars2 githubusercontent com u 17281178 v 4 s 100 width 100px alt br sub b abbey hart b sub a br a href https github com carbon design 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width 100px alt br sub b hao cheng b sub a br a href https github com carbon design system carbon commits author haocheng6 title code a td td align center a href https github com cordesmj img src https avatars githubusercontent com u 7409239 v 4 s 100 width 100px alt br sub b cordesmj b sub a br a href https github com carbon design system carbon commits author cordesmj title code a td td align center a href https med aziz chebbi web app img src https avatars githubusercontent com u 60013060 v 4 s 100 width 100px alt br sub b aziz chebbi b sub a br a href https github com carbon design system carbon commits author azizchebbi title code a td td align center a href https github com misiekhardcore img src https avatars githubusercontent com u 58469680 v 4 s 100 width 100px alt br sub b micha konopski b sub a br a href https github com carbon design system carbon commits author misiekhardcore title code a td td align center a href https omkarajagunde web app img src https avatars 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html-css-standards | the nerdery front end coding standards table of contents 1 overview overview 2 html formatting standards html md html formatting 3 html best practices standards html md html best practices 4 css formatting standards css md css formatting 5 css best practices standards css md css best practices 6 scss standards scss md 7 accessibility standards accessibility md 8 browser amp device support standards browser device support md 9 files amp folders standards files folders md 10 changelog changelog md a name overview a overview prime directive the standards herein are a guide to keep developers at the nerdery interoperable amongst each other and able to produce the highest quality code given the timeline and budget constraints of a project for a successful project always favor solutions that benefit the project and end users over producing perfect code always aim to meet the standards knowing you ll have to break the rules at some point be thoughtful about when you deviate and check with a senior software engineer or a principal software engineer for guidance expectations understand and follow the standards outlined in this document understand and follow the methodology standards methodology md write code knowing that someone else might be maintaining it select tools that benefit the project goals strive to make your code semantic accessible predictable reusable flexible resilient understandable scalable performant maintainable interoperable | style-guide | front_end |
LURE | analyzing and mitigating object hallucination in large vision language models yiyang zhou https yiyangzhou github io chenhang cui https gzcch github io jaehong yoon https jaehong31 github io linjun zhang https linjunz github io zhun deng https www zhundeng org chelsea finn https ai stanford edu cbfinn mohit bansal https www cs unc edu mbansal huaxiu yao https www huaxiuyao io div align center equal contribution div div align center a href https arxiv org pdf 2310 00754 pdf img src assets paper arxiv orange svg a div news 10 03 our code and data have been organized and are about to be released 10 03 our paper is online now https arxiv org pdf 2310 00754 pdf getting started installation 1 prepare the code and the environment git clone our repository creating a python environment and ativate it via the following command bash git clone https github com yiyangzhou lure git cd lure conda env create f environment yml conda activate lure 2 prepare the pretrained vicuna weights the current version of minigpt 4 is built on the v0 versoin of vicuna 13b download the corresponding llm weights from the following huggingface space via clone the repository using git lfs vicuna v0 13b downlad https huggingface co vision cair vicuna tree main the final weights would be in a single folder in a structure similar to the following vicuna weights config json generation config json pytorch model bin index json pytorch model 00001 of 00003 bin then set the path to the vicuna weight in the model config file here minigpt4 configs models minigpt4 yaml l16 at line 16 3 prepare the pretrained minigpt 4 checkpoint download the pretrained checkpoints according to the vicuna model from minigpt 4 https github com vision cair minigpt 4 in our paper the initial parameters we used are from minigpt 4 s stage1 checkpoint aligned with vicuna 13b stage 1 checkpoint aligned with vicuna 13b stage 2 downlad https drive google com file d 1u9frrbb3vovp1hxcalpd9lw4t4p6 yq8 view downlad https drive google com file d 1a4zlvaidbr 36pasffmgpvh5p7ckmpze view then set the path to the pretrained checkpoint in the evaluation config file in eval configs minigpt4 eval yaml eval configs minigpt4 eval yaml l11 at line 11 4 how to train your own lure step 1 prepare dataset you can modify your data set path here minigpt4 configs datasets cc sbu align yaml l5 at line 5 the final dataset path would be organized in a single folder following a structure similar to what s described below dataset train filter cap json image 2 jpg 3 jpg the file filter cap json contains our prepared 5000 lure training data entries each sample within includes three fields image id which represents the name of the image in the training data caption which denotes the detailed description obtained from llava instruct 150k https huggingface co datasets liuhaotian llava instruct 150k tree main corresponding to the image and h caption which signifies the hallucinated description we constructed based on caption this might include ambiguous objects and contributing objects the images can be directly downloaded from coco2014 train https cocodataset org download as for filter cap json we have already prepared a version containing data masked for uncertain objects which can be found at here dataset train we have also uploaded a dataset hallucination5k train jsonl without masks which includes several fields value represents the corresponding caption in filter cap json while h value represents the unmasked version of h caption in filter cap json additionally co objects indicates the co occurring objects extracted by gpt and uncertain objects represents the uncertain objects extracted by lvlms during the image description process step 2 training to launch the second stage alignment first specify the path to the initial checkpoint file in train configs minigpt4 stage2 finetune yaml train configs minigpt4 stage2 finetune yaml you can also specify the output path there then run the following command in our experiments we use 1 a100 80g bash torchrun nproc per node num gpu train py cfg path train configs minigpt4 stage2 finetune yaml model inference prepare model captions in the format similiar to the following id image path answer caption of llvm p all word1 probs word2 probs objs obj1 obj2 for extracting objects from sentences natural language processing nlp libraries can be used for part of speech tagging or named entity recognition such as nltk natural language toolkit and spacy to output probabilities we modify the generation utils py file in the transformers library to generate probabilities for each token we store the probability of each word s first token in a dictionary named p all to get the masked caption of prepared captions run the following command bash python generate idk py input file path to caption file jsonl output file path to idk caption file jsonl then run the following command to obtain the rewriting response bash python output lure py cfg path path to config yaml gpu id gpu id input caption path to idk caption file input image path to image file output file path to output jsonl citation if you found this work useful consider giving this repository a star and citing our paper as followed misc zhou2023analyzing title analyzing and mitigating object hallucination in large vision language models author yiyang zhou and chenhang cui and jaehong yoon and linjun zhang and zhun deng and chelsea finn and mohit bansal and huaxiu yao year 2023 eprint 2310 00754 archiveprefix arxiv primaryclass cs lg | ai |
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BlockchainIllustrations | blockchain illustrations a place to store high level graphical overviews of decentralised technology hypercore local first apps with hypercore https github com 4c656554 blockchainillustrations blob master hypercore 2021 02 06 1534 v0 hypercoreappslo png raw true title ethereum local first apps with hypercore https github com 4c656554 blockchainillustrations blob master ethereum ethblockchain5 png raw true title see also http ethereum stackexchange com a 6413 820 | blockchain |
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Machine-Learning-in-Java | machine learning in java supporting material code libs etc for machine learning in java https www packtpub com big data and business intelligence machine learning java utm source github utm medium repository utm campaign 9781784396589 packtpub publishing machine learning in java https www packtpub com big data and business intelligence machine learning java utm source github utm medium repository utm campaign 9781784396589 will provide you with the techniques and tools you need to quickly gain insight from complex data you will start by learning how to apply machine learning methods to a variety of common tasks including classification prediction forecasting market basket analysis and clustering moving on you will discover how to detect anomalies and fraud and ways to perform activity recognition image recognition and text analysis by the end of the book you will explore related web resources and technologies that will help you take your learning to the next level code is organized by chapters each chapter is a seperate eclipse project with all the corresponding libraries and datasets chapters 1 applied machine learning quick start 1 java tools and libraries for machine learning 1 basic algorithms classification regression and clustering 1 customer relationship prediction 1 affinity analysis 1 recommendation engine with apache mahout 1 fraud and anomaly detection 1 image recognition with deeplearning4java 1 activity recognition with mobile phone sensors 1 text mining with mallet topic modelling and spam detection 1 what is next sample chapters http machine learning in java com and additional materials are available related books python machine learning https www packtpub com big data and business intelligence python machine learning utm source github utm medium repository utm campaign 9781783555130 r machine learning by example https www packtpub com big data and business intelligence r machine learning example utm source github utm medium repository utm campaign 9781784390846 | ai |
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coursera-ionic | multiplatform mobile app development with web technologies ionic framework universidad cient fica y tecnol gica de hong kong this course focuses on developing multiplatform mobile applications using the web skills html5 css and javascript that you have already acquired so far in the previous courses of this specialization in particular we make use of the cordova hybrid application framework to develop and target multiple mobile platforms with a single codebase we make use of the ionic framework one of fastest growing mobile application frameworks that is built with mobile optimized html5 and css based components and angularjs you will learn about ui development with ionic and then using cordova s modules to access the native mobile platform s capabilities from javascript you should have already completed the bootstrap and the angularjs courses in this specialization before proceeding with this course alternately you should already have sufficient knowledge of bootstrap and angularjs before you proceed with this course at the end of this course you will be able to build mobile applications targeting multiple platforms with a single codebase leverage your html5 css javascript and angularjs skills use various features of the ionic framework to build hybrid mobile applications https www coursera org learn hybrid mobile development | front_end |
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vision | torch vision this repository consists of vision datasets data loaders for popular vision datasets vision transforms common image transformations such as random crop rotations etc wip vision models model definitions and pre trained models for popular models such as alexnet vgg resnet etc installation binaries bash conda install torchvision c https conda anaconda org t 6n msq4wz7jo soumith from source bash pip install r requirements txt pip install datasets the following dataset loaders are available coco captioning and detection coco lsun classification lsun imagefolder imagefolder imagenet 12 imagenet 12 datasets have the api getitem len they all subclass from torch utils data dataset hence they can all be multi threaded python multiprocessing using standard torch utils data dataloader for example torch utils data dataloader coco cap batch size args batchsize shuffle true num workers args nthreads in the constructor each dataset has a slightly different api as needed but they all take the keyword args transform a function that takes in an image and returns a transformed version common stuff like totensor randomcrop etc these can be composed together with transforms compose see transforms section below target transform a function that takes in the target and transforms it for example take in the caption string and return a tensor of word indices coco this requires the coco api to be installed https github com pdollar coco tree master pythonapi captions dset cococaptions root dir where images are annfile json annotation file transform target transform example python import torchvision datasets as dset import torchvision transforms as transforms cap dset cococaptions root dir where images are annfile json annotation file transform transforms totensor print number of samples len cap img target cap 3 load 4th sample print image size img size print target output number of samples 82783 image size 3l 427l 640l u a plane emitting smoke stream flying over a mountain u a plane darts across a bright blue sky behind a mountain covered in snow u a plane leaves a contrail above the snowy mountain top u a mountain that has a plane flying overheard in the distance u a mountain view with a plume of smoke in the background detection dset cocodetection root dir where images are annfile json annotation file transform target transform lsun dset lsun db path classes train transform target transform db path root directory for the database files classes train all categories training set val all categories validation set test all categories test set bedroom train church train a list of categories to load imagefolder a generic data loader where the images are arranged in this way root dog xxx png root dog xxy png root dog xxz png root cat 123 png root cat nsdf3 png root cat asd932 png dset imagefolder root root folder path transform target transform it has the members self classes the class names as a list self class to idx corresponding class indices self imgs the list of image path class index tuples imagenet 12 this is simply implemented with an imagefolder dataset the data is preprocessed as described here https github com facebook fb resnet torch blob master install md download the imagenet dataset here is an example https github com pytorch examples blob 27e2a46c1d1505324032b1d94fc6ce24d5b67e97 imagenet main py l48 l62 transforms transforms are common image transforms they can be chained together using transforms compose totensor converts pil image to tensor normalize mean std normalizes the image given mean std for example mean 0 3 1 2 2 1 scale size interpolation image bilinear scales the smaller image edge to the given size interpolation modes are options from pil centercrop size center crops the image to the given size randomcrop size random crops the image to the given size randomhorizontalflip hflip the image with probability 0 5 randomsizedcrop size interpolation image bilinear random crop with size 0 08 1 and aspect ratio 3 4 4 3 inception style transforms compose one can compose several transforms together for example python transform transforms compose transforms randomsizedcrop 224 transforms randomhorizontalflip transforms totensor transforms normalize mean 0 485 0 456 0 406 std 0 229 0 224 0 225 | ai |
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STM32F407_FreeRTOS_LittlevGL | stm32f407 freertos littlevgl mcu stm32f407zg sarm s61wv12816dbll 10tl 2 1 sarm s61wv12816dbll 10tl 2 flash w25q32 w25q16 1 spiflash h define w25q16 2 sram h use exram 3 system stm32f4xx c data in extsram v0 0 0 1 mk makefile 2 littlefs freertos littlevgl v1 0 0 1 v1 0 1 1 2 | os |
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nitda-blockchain-scholarship | nitda blockchain scholarship course materials for the nitda blockchain scholarship | blockchain |
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RaspberryPi-FreeRTOS | freertos ported to raspberry pi this provides a very basic port of freertos to raspberry pi howto build type make if you get an error then cd dbuild pretty chmod x py currently the makefile expect an arm none eabi toolchain in the path either export the path to yours or modify the toolchain variable in dbuild config mk file you may also need to modify the library locations in the makefile kernel elf ldflags l c yagarto lib gcc arm none eabi 4 7 1 lgcc kernel elf ldflags l c yagarto arm none eabi lib lc the build system also expects find your python interpreter by using usr bin env python if this doesn t work you will get problems to resolve this modify the lines in the dbuild pretty py files hope this helps i m currently porting my bitthunder project to the pi which is a os based on freertos but with a comprehensive driver model and file systems etc http github com jameswalmsley bitthunder james | os |
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Analyzing-Chicago-Socio-Economic-Data | analyzing chicago socio economic data this is the final project from my data engineering foundation course offered by ibm skills network the project is about connecting to databases using python and analyzing chicago socio economic data in jupyter notebook introduction this python notebook will be used to 1 understand three chicago datasets 2 load the three datasets into three tables in a db2 database on cloud 3 analyze data in jupyter notebook datasets to complete the assignment problems in this notebook you will be using three datasets that are available on the city of chicago s data portal 1 a href https data cityofchicago org health human services census data selected socioeconomic indicators in c kn9c c2s2 utm medium exinfluencer utm source exinfluencer utm content 000026uj utm term 10006555 utm id na skillsnetwork channel skillsnetworkcoursesibmdeveloperskillsnetworkdb0201enskillsnetwork22 2022 01 01 socioeconomic indicators in chicago a 2 a href https data cityofchicago org education chicago public schools progress report cards 2011 9xs2 f89t utm medium exinfluencer utm source exinfluencer utm content 000026uj utm term 10006555 utm id na skillsnetwork channel skillsnetworkcoursesibmdeveloperskillsnetworkdb0201enskillsnetwork22 2022 01 01 chicago public schools a 3 a href https data cityofchicago org public safety crimes 2001 to present ijzp q8t2 utm medium exinfluencer utm source exinfluencer utm content 000026uj utm term 10006555 utm id na skillsnetwork channel skillsnetworkcoursesibmdeveloperskillsnetworkdb0201enskillsnetwork22 2022 01 01 chicago crime data a 1 socioeconomic indicators in chicago this dataset contains a selection of six socioeconomic indicators of public health significance and a hardship index for each chicago community area for the years 2008 2012 a detailed description of this dataset and the original dataset can be obtained from the chicago data portal at https data cityofchicago org health human services census data selected socioeconomic indicators in c kn9c c2s2 https data cityofchicago org health human services census data selected socioeconomic indicators in c kn9c c2s2 utm medium exinfluencer utm source exinfluencer utm content 000026uj utm term 10006555 utm id na skillsnetwork channel skillsnetworkcoursesibmdeveloperskillsnetworkdb0201enskillsnetwork22 2022 01 01 cm mmc email newsletter developer ed 2btech ww ww skillsnetwork courses ibmdeveloperskillsnetwork db0201en skillsnetwork 20127838 cm mmca1 000026uj cm mmca2 10006555 cm mmca3 m12345678 cvosrc email newsletter m12345678 cvo campaign 000026uj 2 chicago public schools this dataset shows all school level performance data used to create cps school report cards for the 2011 2012 school year this dataset is provided by the city of chicago s data portal a detailed description of this dataset and the original dataset can be obtained from the chicago data portal at https data cityofchicago org education chicago public schools progress report cards 2011 9xs2 f89t https data cityofchicago org education chicago public schools progress report cards 2011 9xs2 f89t utm medium exinfluencer utm source exinfluencer utm content 000026uj utm term 10006555 utm id na skillsnetwork channel skillsnetworkcoursesibmdeveloperskillsnetworkdb0201enskillsnetwork22 2022 01 01 cm mmc email newsletter developer ed 2btech ww ww skillsnetwork courses ibmdeveloperskillsnetwork db0201en skillsnetwork 20127838 cm mmca1 000026uj cm mmca2 10006555 cm mmca3 m12345678 cvosrc email newsletter m12345678 cvo campaign 000026uj 3 chicago crime data this dataset reflects reported incidents of crime with the exception of murders where data exists for each victim that occurred in the city of chicago from 2001 to present minus the most recent seven days a detailed description of this dataset and the original dataset can be obtained from the chicago data portal at https data cityofchicago org public safety crimes 2001 to present ijzp q8t2 https data cityofchicago org public safety crimes 2001 to present ijzp q8t2 utm medium exinfluencer utm source exinfluencer utm content 000026uj utm term 10006555 utm id na skillsnetwork channel skillsnetworkcoursesibmdeveloperskillsnetworkdb0201enskillsnetwork22 2022 01 01 cm mmc email newsletter developer ed 2btech ww ww skillsnetwork courses ibmdeveloperskillsnetwork db0201en skillsnetwork 20127838 cm mmca1 000026uj cm mmca2 10006555 cm mmca3 m12345678 cvosrc email newsletter m12345678 cvo campaign 000026uj introduction this python notebook will be used to 1 understand three chicago datasets 2 load the three datasets into three tables in a db2 database 3 execute sql queries to analyze data objectives store dataset in database tables connect to database query database system columns to ensure chicago public schools data is loaded analyze database data results expected from analyzing database data total number of crimes recorded in the crime table community areas with per capita income less than 11000 list of all case numbers for crimes involving minors children are not considered minors for the purposes of crime analysis list of all kidnapping crimes involving a child kinds of crimes recorded at schools average safety score for each type of school list 5 community areas with highest of households below poverty line most crime prone community area community area with highest hardship index using sub query community area name with most number of crimes using sub query | server |
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advanced-lane-detection-for-self-driving-cars | advanced lane detection for self driving cars video white output videos gif out track1 gif raw true https youtu be boe5hvpgnmq click the gif abobe for link to youtube video of the result dependencies python 3 5 x numpy cv2 matplotlib glob pil moviepy objectives compute the camera calibration matrix and distortion coefficients using a set of chessboard images apply a distortion correction to video frames use color transforms gradients to create a thresholded binary image apply a perspective transform to rectify binary image birds eye view detect lane pixels and fit to find the lane boundary determine the curvature of the lane and vehicle position with respect to center warp the detected lane boundaries back onto the original image output visual display of the lane boundaries and numerical estimation of lane curvature and vehicle position image video code file references image1 output images undistort output png undistorted image1b output images undistort road output png undistorted image2b output images cropped road png cropped image2c output images combined thresholding png thresholding image2d output images birdseyeview png bird s eye view image2e output images sliding window png sliding window search polynomial output images polynomial png polynomial fitpoly output images color fit lines jpg fit polynomial input img test images test3 jpg input image image3 examples binary combo example jpg binary example image4 output images warped straight lines jpg warp example image5 examples color fit lines jpg fit visual image6 examples example output jpg output video in project video mp4 video video out output videos video out track1 mp4 track 1 video gif track1 output videos gif out track1 gif track 1 gif calib1 test images calibration1 jpg chessboard calib chesss output images undist img calibration1 png calibration chessboard 01 calib road output images 01 undist img png calibration road 02 cropped output images 02 cropped png cropped road 03 sobel thresh output images 03 combined gradient img png sobel threshold 04 hls thresh output images 04 combined hls img png hls threshold 05 combined thresh output images 05 combined thresh result img png combined threshold 07 warped output images 07 warped img png warped thresholded 08 sliding window output images 08 searching img png sliding window 10 lane illustration output images 10 w color result img png lane illustration 11 lane rewarped output images 11 color result png original perspective 13 result output images 13 final result png result gui demo gui tool demo ezgif com video to gif gif parameter tuner gui tool implementation details camera calibration py camera calibration py to calculate calibration matrix br line py line py line class contains functions to detect lane lines br threshold py threshold py contains functions for thresholding an image br process py process py contains the image processing pipeline and main function br find parameters py find parameters py run gui tool to find right parameters for various inputs br guiutils py guiutils py gui builder class pipeline p align center img src output images pipeline pipeline png alt pipeline br b pipeline for detecting lanes b br p 1 camera calibration the camera that is being used may have distortion which can cause erros in calculations so we first need to calibrate the camera and calculate the calibration matrix camera looks at world points 3d and converts them to image points 2d using some chessboard images that would have predictable patterns i am calibrating the camera br the code for camera calibration step is contained in the camera calibration py camera calibration py i start by preparing object points which will be the x y z coordinates of the chessboard corners in the world here i am assuming the chessboard is fixed on the x y plane at z 0 such that the object points are the same for each calibration image thus objp is just a replicated array of coordinates and objpoints will be appended with a copy of it every time i successfully detect all chessboard corners in a test image imgpoints will be appended with the x y pixel position of each of the corners in the image plane with each successful chessboard detection i then used the output objpoints and imgpoints to compute the camera calibration and distortion coefficients using the cv2 calibratecamera function i applied this distortion correction to the test image using the cv2 undistort function and obtained this result undistorted chessboard image1 undistorted road image1b 2 perspective transform objects appear smaller the farther they are from view point and parallel lines seem to converge to a point when we project the 3d points to camera s 2d points this phenomenon needs to be taken into account when trying to find parallel lines of a lane with perspective transform we can transform road image to a bird eye view image in which it is easier to detect the curving angles of lanes br the code for perspective transformation is contain in the line py line py below is the outcome of perspective transform br perspective transform image4 3 cropping for the purpose of detecting lane lines we only need to focus on the regions where we are likely to see the lanes for this reason i am cropping the image and doing the further image processing only on certain regions of the image i also resize the image to smaller dimensions this helps with making the image processing pipeline faster below is the outcome of cropping the image cropped image2b 4 thresholding i used two methods of thresholding gradient thresholing hls thresholding br i used sobel kernel for gradient thresholding in both x and y directions since lane lines are likely to be vertical i put more weight on the gradient in y direction i took absolute gradient values and normalized them for appropriate scaling br in addition i used hls color channel to handle cases when the road color is too bright or too light i discarted l channel which contains the information about lightness bright or dark and put more emphasis on h and l channels this way i could eliminate the lightness of the pixel out of the equation br then i combined both of the gradient and hls color threshoding into one for the final thresholded binary image the code for this thresholding approach is contained in the threshold py threshold py below is the outcome of thresholding br combined thresholding image2c 5 birds eye view when we do perspective transform as discussed above we can get birds eye view in the example shown above the road is a flat plane this isn t strictly true but we can still get a good approximation i take 4 points in a trapezoidal shape that would represent a rectangle when looking down from road above this allows use to eliminate the phenomenon by which the parallel lines seem to converge to a single point in birds eye view we can view the lane lines as actual parallel lines the code for this is contained in the line py line py below is the outcome of transforming road to birds eye view perspective br birds eye view image2d as we can see it is very difficult to see in camera view that the lane is curving to the right however in birds eye view we can easily detect that the parallel lane lines are curving to right few meters ahead 6 sliding window search once we have already detected lane lines in an earlier frames we can use that information and use a sliding window placed around the line centers to find and follow lane lines from bottom to the top of the image frame this allows us to do a highly restricted search and saves a lot of processing time although it is not always possible to detect lane lines from the history that is saved in line class object so if we lose track of the lines we ca go back to the method of using thresholding and begin searching lane lines from scratch br i do this using two functions br line search reset https github com maunesh advanced lane detection for self driving cars blob master line py l114 line search tracking https github com maunesh advanced lane detection for self driving cars blob master line py l260 br below is the visualization of sliding window search br slidig window search image2e 7 radius of the curvature now with the located the lane line pixels we can use their x and y pixel positions to fit a second order polynomial curve fit polynomial polynomial i am fitting for f y rather than f x because the lane lines in the warped image are nearly vertical and may have the same x value for more than one y values fit polynomial fitpoly 8 parameter tuning parameter tuning is tricky especially for the challenge video in my pipeline parameters can be tuned in process py process py to update parameters modify this code parameter tuning https github com maunesh advanced lane detection for self driving cars blob master process py l31 i implemented a gui tool similar to the one i had implemented in basic lane line detection this was very helpful to determine better parameters for the challenge video the code for this tool is contained in guiutils py guiutils py and find parameters py find parameters py br below is a demo of the gui tool here i am trying to determine the correct threshold values for gradient in x direction and gradient in y direction video white gui tool demo ezgif com video to gif gif raw true 9 illustrating lane lines on image frames once we have detected the lane lines we can illustrate the lane on the current frame image by overlaying color pixels on top of the image i am illustrating lane lines measurement info and the birds eye view on each frame using following functions br illustrate driving lane https github com maunesh advanced lane detection for self driving cars blob master line py l370 illustrate info panel https github com maunesh advanced lane detection for self driving cars blob master line py l471 illustrate driving lane with topdownview https github com maunesh advanced lane detection for self driving cars blob master line py l498 br with everything combined when we run the pipeline on an image we get the follwing image as a final result br final result 13 result video output project video youtube link https youtu be boe5hvpgnmq br challenge video youtube link https youtu be clk4ilmaubw br reflection getting good results on harder challenge video was very difficult i did not try convolution method but i am leaving it for future experiements i love computer vision but having tried both the deep learning approach to drive the car autonomously and the computer vision approach to detect lane lines the experiece has made me really appreciate the potential of deep learning in self driving car domain | computer-vision self-driving-car | ai |
Web-Dev-Project-Hacktober | web devlopment project hacktober welcome web devlopment enthusiasts participating in hacktoberfest and want to contribute steps to follow fork the repository and clone it create a branch add your project or improve an existing project generate pull request cloning my project bash git clone https github com ritikraja07 web dev project hacktober git cd web dev project hacktober appendix kindly make valuable contribution any spammy pull request will not be tolerated authors ritikraja07 https github com ritikraja07 about me i am a passionate frontend devloper features created for beginners in open source based on rules and regulations set by hacktoberfest aims in creating a healthy competition platform | hacktoberfest hacktoberfest2023 webdevelopment | front_end |
nearcore | br br p align center img src docs images logo svg width 240 p br br reference implementation of near protocol buildkite https img shields io buildkite 0eae07525f8e44a19b48fa937813e2c21ee04aa351361cd851 stable status stable release prerelease status prerelease codecov codecov badge codecov url discord chat discord badge discord url telegram group telegram badge telegram url stable release https img shields io github v release nearprotocol nearcore label stable prerelease https img shields io github v release nearprotocol nearcore include prereleases label prerelease ci badge master https badge buildkite com a81147cb62c585cc434459eedd1d25e521453120ead9ee6c64 svg branch master ci url https buildkite com nearprotocol nearcore codecov badge https codecov io gh nearprotocol nearcore branch master graph badge svg codecov url https codecov io gh nearprotocol nearcore discord badge https img shields io discord 490367152054992913 svg discord url https near chat telegram badge https cdn jsdelivr net gh patrolavia telegram badge 8fe3382b3fd3a1c533ba270e608035a27e430c2e chat svg telegram url https t me cryptonear about near near s purpose is to enable community driven innovation to benefit people around the world to achieve this purpose near provides a developer platform where developers and entrepreneurs can create apps that put users back in control of their data and assets which is the foundation of open web movement open web url one of the components of near is the near protocol an infrastructure for server less applications and smart contracts powered by a blockchain near protocol is built to deliver usability and scalability of modern paas like firebase at fraction of the prices that blockchains like ethereum charge overall near provides a wide range of tools for developers to easily build applications js client library js api to connect to near protocol from your applications rust rust sdk and javascript typescript js sdk sdks to write smart contracts and stateful server less functions numerous examples examples url with links to hack on them right inside your browser lots of documentation docs url with tutorials tutorials url and api docs api docs url open web url https techcrunch com 2016 04 10 1301496 js api https github com near near api js rust sdk https github com near near sdk rs js sdk https github com near near sdk js examples url https near dev docs url https docs near org tutorials url https docs near org tutorials welcome api docs url https docs near org api rpc introduction join the network the easiest way to join the network is by using the nearup command which you can install as follows bash pip3 install user nearup you can join all the active networks mainnet nearup run mainnet testnet nearup run testnet betanet nearup run betanet check the nearup repository for more details https github com near nearup on how to run with or without docker to learn how to become validator checkout documentation https docs near org docs develop node validator staking and delegation contributing the workflow and details of setup to contribute are described in contributing md contributing md and security policy is described in security md security md to propose new protocol changes or standards use specification standards repository https github com nearprotocol neps getting in touch we use zulip for semi synchronous technical discussion feel free to chime in https near zulipchat com for non technical discussion and overall direction of the project see our discourse forum https gov near org | blockchain rust webassembly nearprotocol | blockchain |
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