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"cells": [
{
"cell_type": "code",
"execution_count": 16,
"id": "5bdfe87c",
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"import json\n",
"from itertools import combinations\n",
"IMAGE_DIR = \"/root/siton-tmp/images_divided\""
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "fb8c9036",
"metadata": {},
"outputs": [],
"source": [
"folders = sorted([\n",
" f for f in os.listdir(IMAGE_DIR)\n",
" if os.path.isdir(os.path.join(IMAGE_DIR, f)) and not f.startswith('.')\n",
"])\n",
"data = []\n",
"for cnt, idx in enumerate(folders):\n",
" folder_path = os.path.join(IMAGE_DIR, idx)\n",
" images = sorted([img for img in os.listdir(folder_path) if img.endswith('.png')])\n",
" first_indices, second_indices = zip(*[\n",
" list(map(int, img.split('.')[0].split('_')))\n",
" for img in images\n",
" ])\n",
" first_indices = sorted(set(first_indices))\n",
" second_indices = sorted(set(second_indices))\n",
" \n",
" for i in first_indices:\n",
" for j in second_indices:\n",
" ref_img = f\"{i}_{j}.png\"\n",
" candidates = [\n",
" [\n",
" f\"{x}_{y}.png\"\n",
" for x in first_indices\n",
" ]\n",
" for y in second_indices if y != j\n",
" ]\n",
" items = [\n",
" {\n",
" 'ref_image': ref_img,\n",
" 'rank_images': cand,\n",
" 'idx': idx,\n",
" } for cand in candidates\n",
" ]\n",
" data.extend(items)\n"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "36e0603b",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[{'ref_image': '0_0.png',\n",
" 'rank_images': ['0_1.png', '1_1.png', '2_1.png', '3_1.png'],\n",
" 'idx': '0000'},\n",
" {'ref_image': '0_0.png',\n",
" 'rank_images': ['0_2.png', '1_2.png', '2_2.png', '3_2.png'],\n",
" 'idx': '0000'},\n",
" {'ref_image': '0_1.png',\n",
" 'rank_images': ['0_0.png', '1_0.png', '2_0.png', '3_0.png'],\n",
" 'idx': '0000'},\n",
" {'ref_image': '0_1.png',\n",
" 'rank_images': ['0_2.png', '1_2.png', '2_2.png', '3_2.png'],\n",
" 'idx': '0000'},\n",
" {'ref_image': '0_2.png',\n",
" 'rank_images': ['0_0.png', '1_0.png', '2_0.png', '3_0.png'],\n",
" 'idx': '0000'},\n",
" {'ref_image': '0_2.png',\n",
" 'rank_images': ['0_1.png', '1_1.png', '2_1.png', '3_1.png'],\n",
" 'idx': '0000'},\n",
" {'ref_image': '1_0.png',\n",
" 'rank_images': ['0_1.png', '1_1.png', '2_1.png', '3_1.png'],\n",
" 'idx': '0000'},\n",
" {'ref_image': '1_0.png',\n",
" 'rank_images': ['0_2.png', '1_2.png', '2_2.png', '3_2.png'],\n",
" 'idx': '0000'},\n",
" {'ref_image': '1_1.png',\n",
" 'rank_images': ['0_0.png', '1_0.png', '2_0.png', '3_0.png'],\n",
" 'idx': '0000'},\n",
" {'ref_image': '1_1.png',\n",
" 'rank_images': ['0_2.png', '1_2.png', '2_2.png', '3_2.png'],\n",
" 'idx': '0000'}]"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data[:10]"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "pytorch-env",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.11"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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