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{
"cells": [
{
"cell_type": "code",
"execution_count": 60,
"id": "0dbc59b3",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import os\n",
"import glob\n",
"from omegaconf import OmegaConf"
]
},
{
"cell_type": "code",
"execution_count": 58,
"id": "1fac2763",
"metadata": {},
"outputs": [],
"source": [
"test_len = {}\n",
"train_len = {}\n",
"files = glob.glob(\"../../AVA_src/aesthetics_image_lists/*.jpgl\")\n",
"for file in files:\n",
" file = file.split('/')[-1]\n",
" if 'test' in file:\n",
" test_len[file] = len(pd.read_csv(os.path.join(\"../../AVA_src/aesthetics_image_lists\",file), sep=\" \",header = None))\n",
" elif 'train' in file:\n",
" train_len[file] = len(pd.read_csv(os.path.join(\"../../AVA_src/aesthetics_image_lists\",file), sep=\" \",header = None))\n",
" else:\n",
" print(f\"Pass {file}\")"
]
},
{
"cell_type": "code",
"execution_count": 61,
"id": "0d089d64",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"cityscape_test.jpgl: 2500\n",
"portrait_test.jpgl: 2500\n",
"stilllife_test.jpgl: 2500\n",
"floral_test.jpgl: 2500\n",
"architecture_test.jpgl: 2500\n",
"animal_test.jpgl: 2500\n",
"generic_test.jpgl: 20000\n",
"landscape_test.jpgl: 2500\n",
"fooddrink_test.jpgl: 2500\n",
"\n",
"generic_ls_train.jpgl: 20000\n",
"portrait_train.jpgl: 2500\n",
"landscape_train.jpgl: 2500\n",
"architecture_train.jpgl: 2500\n",
"animal_train.jpgl: 2500\n",
"cityscape_train.jpgl: 2500\n",
"floral_train.jpgl: 2500\n",
"stilllife_train.jpgl: 2500\n",
"fooddrink_train.jpgl: 2500\n",
"generic_ss_train.jpgl: 2500\n",
"\n"
]
}
],
"source": [
"print(OmegaConf.to_yaml(test_len))\n",
"print(OmegaConf.to_yaml(train_len))"
]
},
{
"cell_type": "code",
"execution_count": 62,
"id": "7e25c9f8",
"metadata": {},
"outputs": [],
"source": [
"test_len = {}\n",
"train_len = {}\n",
"files = glob.glob(\"../../AVA_src/style_image_lists/*.jpgl\")\n",
"for file in files:\n",
" file = file.split('/')[-1]\n",
" if 'test' in file:\n",
" test_len[file] = len(pd.read_csv(os.path.join(\"../../AVA_src/style_image_lists\",file), sep=\" \",header = None))\n",
" elif 'train' in file:\n",
" train_len[file] = len(pd.read_csv(os.path.join(\"../../AVA_src/style_image_lists\",file), sep=\" \",header = None))\n",
" else:\n",
" print(f\"Pass {file}\")"
]
},
{
"cell_type": "code",
"execution_count": 63,
"id": "86ff27df",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"test.jpgl: 2809\n",
"\n",
"train.jpgl: 11270\n",
"\n"
]
}
],
"source": [
"print(OmegaConf.to_yaml(test_len))\n",
"print(OmegaConf.to_yaml(train_len))"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "huggingface",
"language": "python",
"name": "huggingface"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.15"
},
"varInspector": {
"cols": {
"lenName": 16,
"lenType": 16,
"lenVar": 40
},
"kernels_config": {
"python": {
"delete_cmd_postfix": "",
"delete_cmd_prefix": "del ",
"library": "var_list.py",
"varRefreshCmd": "print(var_dic_list())"
},
"r": {
"delete_cmd_postfix": ") ",
"delete_cmd_prefix": "rm(",
"library": "var_list.r",
"varRefreshCmd": "cat(var_dic_list()) "
}
},
"types_to_exclude": [
"module",
"function",
"builtin_function_or_method",
"instance",
"_Feature"
],
"window_display": false
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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