Quick test of Amazon rekognition output

rekognition-labels-analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "from random import randrange\n",
    "import webbrowser"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "DATAFILE = '/Users/umd-laptop/Downloads/rekognition-labels-2018-07-19.json'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(DATAFILE, 'r') as infile:\n",
    "    LABELS = json.loads(infile.read())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Abies',\n",
       " 'Acanthaceae',\n",
       " 'Accessories',\n",
       " 'Adapter',\n",
       " 'Adorable',\n",
       " 'Adventure',\n",
       " 'Aerial View',\n",
       " 'Affenpinscher',\n",
       " 'Afro Hairstyle',\n",
       " 'Agavaceae',\n",
       " 'Aircraft',\n",
       " 'Aircraft Carrier',\n",
       " 'Airedale',\n",
       " 'Airfield',\n",
       " 'Airmail',\n",
       " 'Airplane',\n",
       " 'Airport',\n",
       " 'Aisle',\n",
       " 'Alcohol',\n",
       " 'Algae']"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted(LABELS.keys())[:20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "432"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(LABELS['Document'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def img_picker(key):\n",
    "    pick = randrange(0, (len(LABELS[key])-1))\n",
    "    img_addr = 'https://s3.amazonaws.com/{0}'.format(LABELS[key][pick]['image'])\n",
    "    return img_addr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "doc_test_image = img_picker(\"Document\")\n",
    "person_test_image = img_picker(\"Human\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "webbrowser.open(doc_test_image)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "webbrowser.open(person_test_image)"
   ]
  }
 ],
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   "language": "python",
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