{
"cells": [
{
"cell_type": "markdown",
"id": "259a50df-42d1-497d-862c-bc6137f5c0ae",
"metadata": {},
"source": [
"# Setup"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "9bc0cb9f-ae27-48cd-8562-8ed4f33d331d",
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"from pycocotools.coco import COCO\n",
"import os\n",
"from colorama import Fore, Style\n",
"import json\n",
"import numpy as np"
]
},
{
"cell_type": "code",
"execution_count": 55,
"id": "a6843cd1-030a-4df8-a461-8f230d0c7871",
"metadata": {},
"outputs": [],
"source": [
"use_skf_splits = False"
]
},
{
"cell_type": "markdown",
"id": "428bb1c7-36ba-4919-bc73-188f0f1aa697",
"metadata": {},
"source": [
"# Dataset load"
]
},
{
"cell_type": "code",
"execution_count": 89,
"id": "c6fb9073-5dcc-40fa-bd6a-f0538de52f8d",
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"dataset_path = './dataset_archive/'\n",
"train_annotations_path = os.path.join(dataset_path, 'train/', '_annotations.coco.json')\n",
"valid_annotations_path = os.path.join(dataset_path, 'valid/', '_annotations.coco.json')\n",
"\n",
"with open(train_annotations_path) as f1, open(valid_annotations_path) as f2:\n",
" train_data_in = json.load(f1)\n",
" valid_data_in = json.load(f2)"
]
},
{
"cell_type": "code",
"execution_count": 90,
"id": "d2f36b48-c584-4927-9558-f88ce82adaf7",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"5009"
]
},
"execution_count": 90,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(train_data_in['annotations'])"
]
},
{
"cell_type": "code",
"execution_count": 92,
"id": "ccf3258b-39ec-4b3b-be3e-e5f02b65003e",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"1648"
]
},
"execution_count": 92,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(valid_data_in['annotations'])"
]
},
{
"cell_type": "markdown",
"id": "bd265787-d3d0-4d41-b057-85e8ff10b7f3",
"metadata": {},
"source": [
"# (Optional) Split the dataset using the multi-Stratified K-fold CSV files"
]
},
{
"cell_type": "markdown",
"id": "9ea78bc7-c374-44ea-b791-91dd8ae02e34",
"metadata": {},
"source": [
"The CSV files have been previously generated using the multilabel Stratified K-Fold (**mskf**) technique in order to balance classes distributions across dataset splits. If you wish to generate different versions of dataset splits (e.g. with different *k*, different algorithm, etc...), you can do that in the `stratified_kfold.ipynb` notebook. We have provided these splits to make them a baseline as they are used for our metrics. \n",
"\n",
"Each CSV file has the following columns:\n",
"\n",
"- `IMADE_ID` - an integer representing the image ID from the original json annottaions file\n",
"- `IMAGE_PATH` - the corresponding image path\n",
"- `SPLIT` - either **train** or **valid**"
]
},
{
"cell_type": "code",
"execution_count": 67,
"id": "e850bac4-c548-4721-998d-a2e0d40af961",
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"import pandas as pd\n",
"import utils\n",
"\n",
"if use_skf_splits:\n",
" csv_files = ['mskf_0.csv', 'mskf_1.csv', 'mskf_2.csv', 'mskf_3.csv'] \n",
" \n",
" for idx, csv_file in enumerate(csv_files):\n",
" mskf = pd.read_csv(csv_file)\n",
" utils.create_directories_and_copy_files('path/to/dest', data_in, mskf, idx)"
]
},
{
"cell_type": "markdown",
"id": "c9b2c0ae-0d88-4bb1-a636-040f28b83fdf",
"metadata": {},
"source": [
"# Visualise a dataset version"
]
},
{
"cell_type": "markdown",
"id": "629d7f66-0ded-4c6f-94c9-bd26149912ad",
"metadata": {},
"source": [
"Now, let's choose one of the dataset versions and visualize it."
]
},
{
"cell_type": "code",
"execution_count": 86,
"id": "b93ed46b-d1ad-4193-8eb7-ac2dda791b42",
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"loading annotations into memory...\n",
"Done (t=0.08s)\n",
"creating index...\n",
"index created!\n",
"\u001b[34mClass categories in train: ['central-ring', 'other', 'read-out-streak', 'smoke-ring', 'star-loop']\u001b[0m\n",
"\u001b[34mNumber of annotations in train: 5009\u001b[0m\n",
"\u001b[34mNumber of images in train: 791\u001b[0m\n",
"loading annotations into memory...\n",
"Done (t=0.03s)\n",
"creating index...\n",
"index created!\n",
"\u001b[34mClass categories in valid: ['central-ring', 'other', 'read-out-streak', 'smoke-ring', 'star-loop']\u001b[0m\n",
"\u001b[34mNumber of annotations in valid: 1648\u001b[0m\n",
"\u001b[34mNumber of images in valid: 264\u001b[0m\n"
]
}
],
"source": [
"data_dir = dataset_path\n",
"splits = ['train', 'valid']\n",
"\n",
"coco_objects = {}\n",
"\n",
"for split in splits:\n",
" annotations_file = os.path.join(str(data_dir), str(split), '_annotations.coco.json')\n",
" coco_objects[split] = COCO(annotations_file)\n",
" \n",
" # get class categories in the current split\n",
" categories = coco_objects[split].loadCats(coco_objects[split].getCatIds())\n",
" category_names = [cat['name'] for cat in categories]\n",
" print(f\"{Fore.BLUE}Class categories in {split}: {category_names}{Style.RESET_ALL}\")\n",
"\n",
" annotation_ids = {}\n",
"\n",
" # get annotations in the current split\n",
" annotation_ids[split] = coco_objects[split].getAnnIds()\n",
" annotations = coco_objects[split].loadAnns(annotation_ids[split])\n",
" print(f\"{Fore.BLUE}Number of annotations in {split}: {len(annotations)}{Style.RESET_ALL}\")\n",
" \n",
" # get image IDs in the current split\n",
" img_ids = coco_objects[split].getImgIds()\n",
" images = coco_objects[split].loadImgs(img_ids)\n",
" print(f\"{Fore.BLUE}Number of images in {split}: {len(images)}{Style.RESET_ALL}\")"
]
},
{
"cell_type": "code",
"execution_count": 87,
"id": "eb018f21-beae-48cb-9f63-1793b8f9a558",
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"loading annotations into memory...\n",
"Done (t=0.08s)\n",
"creating index...\n",
"index created!\n",
"loading annotations into memory...\n",
"Done (t=0.03s)\n",
"creating index...\n",
"index created!\n"
]
},
{
"data": {
"text/html": [
"\n",
"
\n",
" Annotation Counts and Percentages by Filter and Split\n",
" \n",
" \n",
" Split | \n",
" #Train (%) | \n",
" #Valid (%) | \n",
"
\n",
" \n",
" Category | \n",
" | \n",
" | \n",
"
\n",
" \n",
" \n",
" \n",
" central-ring | \n",
" 503.0 (10.042) | \n",
" 168.0 (10.194) | \n",
"
\n",
" \n",
" other | \n",
" 34.0 (0.679) | \n",
" 7.0 (0.425) | \n",
"
\n",
" \n",
" read-out-streak | \n",
" 1861.0 (37.153) | \n",
" 607.0 (36.833) | \n",
"
\n",
" \n",
" smoke-ring | \n",
" 1223.0 (24.416) | \n",
" 418.0 (25.364) | \n",
"
\n",
" \n",
" star-loop | \n",
" 1388.0 (27.71) | \n",
" 448.0 (27.184) | \n",
"
\n",
" \n",
"
\n"
],
"text/plain": [
""
]
},
"execution_count": 87,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from tabulate import tabulate\n",
"\n",
"table_data = []\n",
"\n",
"for split in splits:\n",
" annotations_file = os.path.join(data_dir, split, '_annotations.coco.json')\n",
" coco = COCO(annotations_file)\n",
" cat_ids = coco.getCatIds()\n",
" categories = coco.loadCats(cat_ids)\n",
" cat_names = [cat['name'] for cat in categories]\n",
" cat_counts = [len(coco.getAnnIds(catIds=[cat_id])) for cat_id in cat_ids]\n",
" total_count = sum(cat_counts)\n",
"\n",
" for cat_name, count in zip(cat_names, cat_counts):\n",
" percentage = (count / total_count) * 100 if total_count > 0 else 0\n",
" if percentage > 0:\n",
" table_data.append({\n",
" 'Split': '#'+split.capitalize()+' (%)',\n",
" 'Category': cat_name,\n",
" 'Count': count,\n",
" 'Percentage': np.round(percentage, 3)\n",
" })\n",
"\n",
"df = pd.DataFrame(table_data)\n",
"pivot_count = df.pivot_table(index='Category', columns='Split', values='Count', fill_value=0)\n",
"pivot_percentage = df.pivot_table(index='Category', columns='Split', values='Percentage', fill_value=0.0)\n",
"combined_df = pivot_count.astype(str) + \" (\" + pivot_percentage.astype(str) + \")\"\n",
"\n",
"styled_df = combined_df.style.apply(utils.highlight_max_str, subset=['#Train (%)', '#Valid (%)'])\\\n",
" .format({'#Train (%)': \"{:}\", '#Valid (%)': \"{:}\"})\\\n",
" .set_properties(**{'text-align': 'center', 'font-size': '10pt'})\\\n",
" .set_table_styles([{'selector': 'th', 'props': [('font-size', '12pt')]}])\\\n",
" .set_caption(\"Annotation Counts and Percentages by Filter and Split\")\n",
"styled_df"
]
},
{
"cell_type": "markdown",
"id": "9bbe486b-117c-4545-b952-959b53979b16",
"metadata": {},
"source": [
"We can also see how many images per filter we have."
]
},
{
"cell_type": "code",
"execution_count": 88,
"id": "1c74762d-3ead-4d24-8128-684cee708151",
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
" Counts of Images and Annotations per Filter\n",
" \n",
" \n",
" | \n",
" Observing Filter | \n",
" Image Count | \n",
" Annotation Count | \n",
"
\n",
" \n",
" \n",
" \n",
" 0 | \n",
" U | \n",
" 193 | \n",
" 1,711 | \n",
"
\n",
" \n",
" 1 | \n",
" V | \n",
" 102 | \n",
" 831 | \n",
"
\n",
" \n",
" 2 | \n",
" B | \n",
" 116 | \n",
" 1,183 | \n",
"
\n",
" \n",
" 3 | \n",
" W | \n",
" 3 | \n",
" 11 | \n",
"
\n",
" \n",
" 4 | \n",
" S | \n",
" 63 | \n",
" 224 | \n",
"
\n",
" \n",
" 5 | \n",
" M | \n",
" 175 | \n",
" 651 | \n",
"
\n",
" \n",
" 6 | \n",
" L | \n",
" 403 | \n",
" 2,046 | \n",
"
\n",
" \n",
"
\n"
],
"text/plain": [
""
]
},
"execution_count": 88,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"filter_count = {'U': 0, 'V': 0, 'B': 0, 'W': 0, 'S': 0, 'M': 0, 'L': 0}\n",
"filter_annots_count = filter_count.copy()\n",
"\n",
"\n",
"for split in splits:\n",
" annotations_file = os.path.join(data_dir, split, '_annotations.coco.json')\n",
" \n",
" with open(annotations_file) as f:\n",
" data_in = json.load(f)\n",
" \n",
" for img in data_in['images']:\n",
" filter = img['file_name'][:13][-1] # The OM observations IDs are 13 characters long, the last of them representing the filter\n",
" filter_count[filter] += 1\n",
" image_annots = [annot for annot in data_in['annotations'] if annot['image_id'] == img['id']]\n",
" for annot in image_annots:\n",
" filter_annots_count[filter] += 1\n",
" \n",
" df_counts = pd.DataFrame(list(filter_count.items()), columns=['Observing Filter', 'Image Count'])\n",
" df_annot_counts = pd.DataFrame(list(filter_annots_count.items()), columns=['Observing Filter', 'Annotation Count'])\n",
" df_merged = pd.merge(df_counts, df_annot_counts, on='Observing Filter')\n",
" \n",
"filters_df = df_merged.style.apply(utils.highlight_max, subset=['Image Count', 'Annotation Count'])\\\n",
" .format({'Image Count': \"{:,}\", 'Annotation Count': \"{:,}\"})\\\n",
" .set_properties(**{'text-align': 'center', 'font-size': '10pt'})\\\n",
" .set_table_styles([{'selector': 'th', 'props': [('font-size', '10pt')]}])\\\n",
" .set_caption(\"Counts of Images and Annotations per Filter\")\n",
" \n",
"filters_df"
]
},
{
"cell_type": "markdown",
"id": "0eec287f-68b3-44e3-9c96-d906e70c472e",
"metadata": {},
"source": [
"## Mask heatmap"
]
},
{
"cell_type": "code",
"execution_count": 71,
"id": "34e13739-98f0-4aff-bb4f-072ee36f38b7",
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"loading annotations into memory...\n",
"Done (t=0.08s)\n",
"creating index...\n",
"index created!\n",
"loading annotations into memory...\n",
"Done (t=0.03s)\n",
"creating index...\n",
"index created!\n"
]
},
{
"data": {
"image/png": 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",
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