Init

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
+best.pth.tar filter=lfs diff=lfs merge=lfs -text

.gitignore

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+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/#use-with-ide
+.pdm.toml
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/

README.md

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+---
+title: Pizza NotPizza
+emoji: 🍕
+colorFrom: yellow
+colorTo: red
+sdk: streamlit
+sdk_version: 1.10.0
+app_file: app.py
+pinned: false
+license: openrail
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import streamlit as st
+import torch
+from PIL import Image
+
+from read import classify
+
+st.title("Pizza & Not Pizza")
+
+device = torch.device("cpu")
+checkpoint = torch.load(r"best.pth.tar", map_location=device)
+
+model = checkpoint['model']
+classes = checkpoint['classes']
+tran = checkpoint['transform']
+
+# upload image
+uploaded_file = st.file_uploader("Choose an image...", type="jpg")
+taking_picture = st.camera_input("Take a picture...")
+
+if uploaded_file is not None:
+    img = Image.open(uploaded_file)
+    st.image(img, caption='Uploaded Image.', use_column_width=True)
+    label = classify(model, img, tran, classes, device)
+    st.write(label)
+    
+elif taking_picture is not None:
+    img = Image.open(taking_picture)
+    st.image(img, caption='Uploaded Image.', use_column_width=True)
+    label = classify(model, img, tran, classes, device)
+    st.write(label)

best.pth.tar

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+version https://git-lfs.github.com/spec/v1
+oid sha256:0482d7e2c55d598f96e718a62a494f87d4d04ae3b6473c9fa40818845769f7ba
+size 27168873

model.py

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+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+
+class Net(nn.Module):
+    
+    def __init__(self):
+        super(Net, self).__init__()
+        self.conv1 = nn.Conv2d(3, 32, 5)
+        self.conv2 = nn.Conv2d(32, 64, 5)
+        self.conv3 = nn.Conv2d(64, 128, 5)
+        self.conv4 = nn.Conv2d(128, 256, 5)
+        self.conv5 = nn.Conv2d(256, 512, 5)
+
+        self.fc1 = None
+        self.fc2 = nn.Linear(512, 128)
+        self.fc3 = nn.Linear(128, 64)
+        self.fc4 = nn.Linear(64, 2)
+
+    def forward(self, x):
+        x = x.float()
+        """ x = F.relu(self.conv1(x))
+        x = F.relu(self.conv2(x))
+        x = F.max_pool2d(x, 2)
+        x = F.relu(self.conv3(x))
+        x = F.relu(self.conv4(x))
+        x = F.max_pool2d(x, 2)
+        x = F.relu(self.conv5(x))
+        x = F.max_pool2d(x, 2) """
+        
+        x = F.max_pool2d(F.relu(self.conv1(x)), 2)
+        x = F.max_pool2d(F.relu(self.conv2(x)), 2)
+        x = F.max_pool2d(F.relu(self.conv3(x)), 2)
+        x = F.max_pool2d(F.relu(self.conv4(x)), 2)
+        x = F.max_pool2d(F.relu(self.conv5(x)), 2)
+
+        #x = x.view(x.size(0), -1)
+        x = torch.flatten(x, 1)
+        
+        if self.fc1 is None:
+            self.fc1 = nn.Linear(x.shape[1], 512).to(x.device)
+        
+        x = F.relu(self.fc1(x))
+        x = F.relu(self.fc2(x))
+        x = F.relu(self.fc3(x))
+        x = self.fc4(x)
+        return x

read.py

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+import random
+import torch
+from PIL import Image
+import requests
+
+def classify(model, imgPath, trans=None, classes=[], device=torch.device("cpu")):
+    
+    try:
+        model = model.eval()
+        img = imgPath
+        img = img.convert("RGB")
+        img = trans(img)
+        img = img.unsqueeze(0)
+        img = img.to(device)
+
+        output = model(img)
+        _, pred = torch.max(output, 1)
+        procent = torch.sigmoid(output)
+        
+        return f"It {classes[pred.item()]} i'm {procent[0][pred[0]]*100:.2f}% sure"
+    except Exception:
+        return "Something went wrong😕, please notify the developer with the following message: " + str(Exception)
+
+
+def get_random_quote():
+    with open("quotes.txt", "r") as file:
+        quotes = file.readlines()
+    return quotes[random.randint(0, len(quotes)-1)]

requirements.txt

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+Pillow==9.4.0
+requests==2.27.1
+streamlit==1.17.0
+torch==1.12.1
+torchvision==0.13.1