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EasyOCR-model

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EasyOCR-model
File size: 2,892 Bytes 
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{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-07-23T04:19:23.488642Z",
     "start_time": "2021-07-23T04:19:21.854534Z"
    }
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import torch.backends.cudnn as cudnn\n",
    "import yaml\n",
    "from train import train\n",
    "from utils import AttrDict\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-07-23T04:19:23.885144Z",
     "start_time": "2021-07-23T04:19:23.880564Z"
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    "code_folding": []
   },
   "outputs": [],
   "source": [
    "cudnn.benchmark = True\n",
    "cudnn.deterministic = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-07-23T04:19:24.119144Z",
     "start_time": "2021-07-23T04:19:24.112032Z"
    },
    "code_folding": [
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   },
   "outputs": [],
   "source": [
    "def get_config(file_path):\n",
    "    with open(file_path, 'r', encoding=\"utf8\") as stream:\n",
    "        opt = yaml.safe_load(stream)\n",
    "    opt = AttrDict(opt)\n",
    "    if opt.lang_char == 'None':\n",
    "        characters = ''\n",
    "        for data in opt['select_data'].split('-'):\n",
    "            csv_path = os.path.join(opt['train_data'], data, 'labels.csv')\n",
    "            df = pd.read_csv(csv_path, sep='^([^,]+),', engine='python', usecols=['filename', 'words'], keep_default_na=False)\n",
    "            all_char = ''.join(df['words'])\n",
    "            characters += ''.join(set(all_char))\n",
    "        characters = sorted(set(characters))\n",
    "        opt.character= ''.join(characters)\n",
    "    else:\n",
    "        opt.character = opt.number + opt.symbol + opt.lang_char\n",
    "    os.makedirs(f'./saved_models/{opt.experiment_name}', exist_ok=True)\n",
    "    return opt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-07-23T04:49:07.045060Z",
     "start_time": "2021-07-23T04:20:15.050992Z"
    }
   },
   "outputs": [],
   "source": [
    "opt = get_config(\"config_files/en_filtered_config.yaml\")\n",
    "train(opt, amp=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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