{
 "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))"
   ]
  }
 ],
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