{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# IBM Watson Visual Recognition\n",
    "Create an account on [IBM Watson Studio](https://www.ibm.com/cloud/watson-studio) and add the [Watson Visual Recognition](https://www.ibm.com/cloud/watson-visual-recognition) service to your free account."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "pip install --upgrade --user \"ibm-watson>=4.5.0\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "apikey = \"<your-apikey>\"\n",
    "version = \"2018-03-19\"\n",
    "url = \"<your-url>\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "from ibm_watson import VisualRecognitionV3\n",
    "from ibm_cloud_sdk_core.authenticators import IAMAuthenticator\n",
    "\n",
    "authenticator = IAMAuthenticator(apikey)\n",
    "visual_recognition = VisualRecognitionV3(\n",
    "    version=version,\n",
    "    authenticator=authenticator\n",
    ")\n",
    "\n",
    "visual_recognition.set_service_url(url)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "visual_recognition.set_default_headers({'x-watson-learning-opt-out': \"true\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = [\n",
    "{\n",
    "  \"title\": \"Bear Country, South Dakota\",\n",
    "  \"url\": \"https://example.com/photos/highres/20140717.jpg\"\n",
    "},\n",
    "{\n",
    "  \"title\": \"Pactola Lake\",\n",
    "  \"url\": \"https://example.com/photos/highres/20140718.jpg\"\n",
    "},\n",
    "{\n",
    "  \"title\": \"Welcome to Utah\",\n",
    "  \"url\": \"https://example.com/photos/highres/20190608_02.jpg\"\n",
    "},\n",
    "{\n",
    "  \"title\": \"Honey Badger\",\n",
    "  \"url\": \"https://example.com/photos/highres/20190611_03.jpg\"\n",
    "},\n",
    "{\n",
    "  \"title\": \"Grand Canyon Lizard\",\n",
    "  \"url\": \"https://example.com/photos/highres/20190612.jpg\"\n",
    "},\n",
    "{\n",
    "  \"title\": \"The Workhouse\",\n",
    "  \"url\": \"https://example.com/photos/highres/20191116_01.jpg\"\n",
    "}\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-------------------------------------------------------------------------------------------------------------------------------------\n",
      "Image Title:  Bear Country, South Dakota \n",
      "\n",
      "brown bear ( 0.944 )\n",
      "bear ( 1 )\n",
      "carnivore ( 1 )\n",
      "mammal ( 1 )\n",
      "animal ( 1 )\n",
      "Alaskan brown bear ( 0.759 )\n",
      "greenishness color ( 0.975 )\n",
      "-------------------------------------------------------------------------------------------------------------------------------------\n",
      "-------------------------------------------------------------------------------------------------------------------------------------\n",
      "Image Title:  Pactola Lake \n",
      "\n",
      "ponderosa pine ( 0.763 )\n",
      "pine tree ( 0.867 )\n",
      "tree ( 0.867 )\n",
      "plant ( 0.867 )\n",
      "blue color ( 0.959 )\n",
      "-------------------------------------------------------------------------------------------------------------------------------------\n",
      "-------------------------------------------------------------------------------------------------------------------------------------\n",
      "Image Title:  Welcome to Utah \n",
      "\n",
      "signboard ( 0.953 )\n",
      "building ( 0.79 )\n",
      "blue color ( 0.822 )\n",
      "purplish blue color ( 0.619 )\n",
      "-------------------------------------------------------------------------------------------------------------------------------------\n",
      "-------------------------------------------------------------------------------------------------------------------------------------\n",
      "Image Title:  Honey Badger \n",
      "\n",
      "American badger ( 0.689 )\n",
      "carnivore ( 0.689 )\n",
      "mammal ( 0.864 )\n",
      "animal ( 0.864 )\n",
      "armadillo ( 0.618 )\n",
      "light brown color ( 0.9 )\n",
      "reddish brown color ( 0.751 )\n",
      "-------------------------------------------------------------------------------------------------------------------------------------\n",
      "-------------------------------------------------------------------------------------------------------------------------------------\n",
      "Image Title:  Grand Canyon Lizard \n",
      "\n",
      "western fence lizard ( 0.724 )\n",
      "lizard ( 0.93 )\n",
      "reptile ( 0.93 )\n",
      "animal ( 0.93 )\n",
      "ultramarine color ( 0.633 )\n",
      "-------------------------------------------------------------------------------------------------------------------------------------\n",
      "-------------------------------------------------------------------------------------------------------------------------------------\n",
      "Image Title:  The Workhouse \n",
      "\n",
      "castle ( 0.896 )\n",
      "fortification ( 0.905 )\n",
      "defensive structure ( 0.96 )\n",
      "stronghold ( 0.642 )\n",
      "building ( 0.799 )\n",
      "mound ( 0.793 )\n",
      "blue color ( 0.745 )\n",
      "-------------------------------------------------------------------------------------------------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "from ibm_watson import ApiException\n",
    "\n",
    "for x in range(len(data)):\n",
    "    try:\n",
    "        url = data[x][\"url\"]\n",
    "        images_filename = data[x][\"title\"]\n",
    "        classes = visual_recognition.classify(\n",
    "            url=url,\n",
    "            images_filename=images_filename,\n",
    "            threshold='0.6',\n",
    "            owners=[\"IBM\"]).get_result()\n",
    "        print(\"-------------------------------------------------------------------------------------------------------------------------------------\")\n",
    "        print(\"Image Title: \", data[x][\"title\"], \"\\n\")\n",
    "        print(\"Image URL: \", data[x][\"url\"], \"\\n\")\n",
    "        classification_results = classes[\"images\"][0][\"classifiers\"][0][\"classes\"]\n",
    "        for result in classification_results:\n",
    "            print(result[\"class\"], \"(\", result[\"score\"], \")\")\n",
    "        print(\"-------------------------------------------------------------------------------------------------------------------------------------\")\n",
    "    except ApiException as ex:\n",
    "        print(\"Method failed with status code \" + str(ex.code) + \": \" + ex.message)"
   ]
  }
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