google-vision-api-notebook.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "I86tgLoXN-fN"
   },
   "outputs": [],
   "source": [
    "import cv2\n",
    "import imutils\n",
    "import json\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import os\n",
    "import pandas as pd\n",
    "import requests\n",
    "import time\n",
    "from base64 import b64encode\n",
    "from IPython.display import Image\n",
    "from pylab import rcParams"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "87ckNcIOiIjf"
   },
   "outputs": [],
   "source": [
    "rcParams['figure.figsize'] = 10, 20"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "j1x8BO5AORgS"
   },
   "outputs": [],
   "source": [
    "def makeImageData(imgpath):\n",
    "    img_req = None\n",
    "    with open(imgpath, 'rb') as f:\n",
    "        ctxt = b64encode(f.read()).decode()\n",
    "        img_req = {\n",
    "            'image': {\n",
    "                'content': ctxt\n",
    "            },\n",
    "            'features': [{\n",
    "                'type': 'DOCUMENT_TEXT_DETECTION',\n",
    "                'maxResults': 1\n",
    "            }]\n",
    "        }\n",
    "    return json.dumps({\"requests\": img_req}).encode()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "5PH_sr9TN7eS"
   },
   "outputs": [],
   "source": [
    "def requestOCR(url, api_key, imgpath):\n",
    "  imgdata = makeImageData(imgpath)\n",
    "  response = requests.post(ENDPOINT_URL, \n",
    "                           data = imgdata, \n",
    "                           params = {'key': api_key}, \n",
    "                           headers = {'Content-Type': 'application/json'})\n",
    "  return response"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "ia3SZkwhQi8t"
   },
   "outputs": [],
   "source": [
    "with open('vision_api.json') as f:\n",
    "    data = json.load(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "ziTG4b1-N0oU"
   },
   "outputs": [],
   "source": [
    "ENDPOINT_URL = 'https://vision.googleapis.com/v1/images:annotate'\n",
    "api_key = data[\"api_key\"]\n",
    "img_loc = \"Image.jpg\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "-RlRp1bllxbh"
   },
   "outputs": [],
   "source": [
    "Image(img_loc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "EU1SEPZWlhGt"
   },
   "outputs": [],
   "source": [
    "result = requestOCR(ENDPOINT_URL, api_key, img_loc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "mfZ_KT68OgV7"
   },
   "outputs": [],
   "source": [
    "if result.status_code != 200 or result.json().get('error'):\n",
    "    print (\"Error\")\n",
    "else:\n",
    "    result = result.json()['responses'][0]['textAnnotations']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "KlGzGqOzROk3"
   },
   "outputs": [],
   "source": [
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "o5AYbd9YfwL-"
   },
   "outputs": [],
   "source": [
    "for index in range(len(result)):\n",
    "  print(result[index][\"description\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "iIs5LgaAfwQ6"
   },
   "outputs": [],
   "source": [
    "def gen_cord(result):\n",
    "  cord_df = pd.DataFrame(result['boundingPoly']['vertices'])\n",
    "  x_min, y_min = np.min(cord_df[\"x\"]), np.min(cord_df[\"y\"])\n",
    "  x_max, y_max = np.max(cord_df[\"x\"]), np.max(cord_df[\"y\"])\n",
    "  return result[\"description\"], x_max, x_min, y_max, y_min"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "Q4LYtrQffm77"
   },
   "outputs": [],
   "source": [
    "text, x_max, x_min, y_max, y_min = gen_cord(result[-1])\n",
    "image = cv2.imread(img_loc)\n",
    "cv2.rectangle(image,(x_min,y_min),(x_max,y_max),(0,255, 0),2)\n",
    "plt.imshow(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))\n",
    "print (\"Text Detected = {}\".format(text))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "f3NoY3tCjDdZ"
   },
   "outputs": [],
   "source": []
  }
 ],
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   "name": "Untitled0.ipynb",
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  "kernelspec": {
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