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Delete coco_format_to_parquet.ipynb
Browse files- coco_format_to_parquet.ipynb +0 -988
coco_format_to_parquet.ipynb
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"cells": [
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"cell_type": "code",
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"execution_count": 1,
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"id": "a333665e-77ee-43af-b539-8b2bc87c008c",
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"metadata": {},
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"outputs": [],
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"source": [
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"import json\n",
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"import pandas as pd\n",
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"from pathlib import Path\n",
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"from PIL import Image, ImageDraw, ImageFile\n",
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"import cv2\n",
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"import io \n",
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"import base64\n",
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"import numpy as np\n",
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"from pycocotools.coco import COCO\n",
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"import os\n",
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"import matplotlib.pyplot as plt\n",
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"import matplotlib.patches as patches\n",
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"from PIL import Image\n",
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"ImageFile.LOAD_TRUNCATED_IMAGES = True\n",
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"\n",
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"import utils\n",
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"\n",
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"dataset_dir = './mskf_0/'\n",
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"train_df, train_coco_data = utils.split_to_df(dataset_dir, 'train/')\n",
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"valid_df, valid_coco_data = utils.split_to_df(dataset_dir, 'valid')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "0e0d5a99-4eba-49d4-931b-0128691631b1",
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"metadata": {
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"scrolled": true
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{'id': 1,\n",
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" 'license': 1,\n",
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" 'file_name': 'S0505210301_M_png.rf.e47187e88c167fad1db290b0214e2175.jpg',\n",
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" 'height': 512,\n",
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" 'width': 512,\n",
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" 'date_captured': '2024-05-08T06:13:06+00:00'}"
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]
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},
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"execution_count": 2,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"train_coco_data['images'][0]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "df660d83-5afb-4b7c-83e4-f1f9d68577cd",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"array([1, 2, 3, 4, 5])"
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]
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},
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"execution_count": 3,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"np.unique(train_df['category_id'])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"id": "51f26d8d-0116-48fe-8cea-d070350df333",
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"metadata": {
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"scrolled": true
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{'image_id': array([<class 'int'>], dtype=object),\n",
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" 'category_id': array([<class 'int'>], dtype=object),\n",
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" 'bbox': array([<class 'list'>], dtype=object),\n",
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" 'area': array([<class 'float'>], dtype=object),\n",
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" 'segmentation': array([<class 'numpy.ndarray'>], dtype=object),\n",
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" 'iscrowd': array([<class 'int'>], dtype=object),\n",
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" 'width': array([<class 'int'>], dtype=object),\n",
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" 'height': array([<class 'int'>], dtype=object),\n",
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" 'observation': array([<class 'str'>], dtype=object),\n",
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" 'image': array([<class 'numpy.ndarray'>], dtype=object),\n",
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" 'annot_id': array([<class 'int'>], dtype=object)}"
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]
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},
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"unique_types = {col: train_df[col].apply(type).unique() for col in train_df.columns}\n",
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"unique_types"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"id": "6f464df1-9e86-47ed-a8c6-d5116a71085e",
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"metadata": {
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"scrolled": true
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},
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"outputs": [],
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"source": [
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"# train_df.head(20)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"id": "3f4afc2a-2ee4-458d-95c0-19e8497653da",
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"metadata": {
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"scrolled": true
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},
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"outputs": [],
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"source": [
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"from collections import defaultdict\n",
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"from datasets import Dataset, Features, Sequence\n",
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"import datasets\n",
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"from io import BytesIO\n",
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"\n",
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"cats_to_colours = { 1:('central-ring', (1,252,214)), \n",
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" 2:('other', (255,128,1)),\n",
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" 3:('read-out-streak', (20, 77, 158)), \n",
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" 4:('smoke-ring', (159,21,100)),\n",
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" 5:('star-loop', (255, 188, 248))}\n",
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"\n",
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"train_dataset=utils.df_to_dataset_dict(train_df, train_coco_data, cats_to_colours)\n",
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"valid_dataset=utils.df_to_dataset_dict(valid_df, valid_coco_data, cats_to_colours)"
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]
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},
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"execution_count": 7,
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"id": "e3ed2ab1-8632-4e49-a661-c306554bd010",
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"metadata": {
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"version_major": 2,
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"version_minor": 0
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"output_type": "display_data"
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{
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"data": {
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"text/plain": [
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"CommitInfo(commit_url='https://huggingface.co/datasets/iulia-elisa/XMM_OM_AI_dataset/commit/e4f969ebf7e6b84ece6a91380cbe2dd2fc669261', commit_message='Upload dataset', commit_description='', oid='e4f969ebf7e6b84ece6a91380cbe2dd2fc669261', pr_url=None, pr_revision=None, pr_num=None)"
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]
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},
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"execution_count": 7,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"from datasets import DatasetDict\n",
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"\n",
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"dataset_dict = DatasetDict({\n",
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" 'train': train_dataset,\n",
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" 'valid': valid_dataset\n",
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"})\n",
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"\n",
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"dataset_dict.push_to_hub('iulia-elisa/XMM_OM_AI_dataset', private=False)"
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]
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}
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],
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"display_name": "env_py311",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.7"
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