{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Prepare CSV URL for LFPW"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "%reload_ext autoreload\n",
    "%autoreload 2\n",
    "\n",
    "import os\n",
    "from os.path import join\n",
    "from glob import glob\n",
    "from pathlib import Path\n",
    "\n",
    "from tqdm import tqdm_notebook as tqdm\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import hashlib\n",
    "\n",
    "import sys\n",
    "sys.path.append('/work/megapixels_dev/megapixels')\n",
    "from app.utils import api_utils, identity_utils"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create CSV for Image Download"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "fp_in_train = '/data_store/datasets/people/lfpw/downloads/kbvt_lfpw_v1_train.csv'\n",
    "fp_in_test = '/data_store/datasets/people/lfpw/downloads/kbvt_lfpw_v1_test.csv'\n",
    "fp_out = '/data_store/datasets/people/lfpw/downloads/urls.csv'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train = pd.read_csv(fp_in_train, sep='\\t')\n",
    "df_test = pd.read_csv(fp_in_test, sep='\\t')\n",
    "df = pd.concat([df_test, df_train], sort=False)\n",
    "records = df.to_dict('records')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "urlmaps = []\n",
    "for record in records:\n",
    "  url = record['imgurl']\n",
    "  ext = Path(url).suffix.lower()\n",
    "  if ext == '.jpeg':\n",
    "    ext = '.jpg'\n",
    "  if ext != '':\n",
    "    ext = '.jpg'\n",
    "  sha256 = hashlib.sha256(str.encode(url)).hexdigest()\n",
    "  filepath = sha256 + ext\n",
    "  urlmaps.append({'url':url, 'filepath':filepath})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_urls = pd.DataFrame.from_dict(urlmaps)\n",
    "df_urls.to_csv(fp_out, index=False)"
   ]
  }
 ],
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  "kernelspec": {
   "display_name": "megapixels",
   "language": "python",
   "name": "megapixels"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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