AI Jupyter Notebooks/CropID_Model/Ag-Analytics-Crop Identification API-Demo.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Ag-Analytics - Crop Identification API - Demo"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The Crop Identification API is a new machine learning product developed from our high accuracy, near real-time ground truth agriculture data, the historical weather and soil data, and high-resolution remote sensing imagery. This product provides a timely and accurate crop type identification for the most common cash crops in the U.S. at 8m spatial resolution. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The Ag-Analytics provides the Crop Identification API service which a user can provide a polygon in specific formats and a year to retrieve the crop type of their land in the given year. Additionally, this service also provides a summary of remote sensing information of their fields and display as time series chart on our website interface."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Experience the usage of this service on Ag-Analytics website using below link:\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Required libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "IPython.notebook.set_autosave_interval(0)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Autosave disabled\n"
     ]
    }
   ],
   "source": [
    "import requests\n",
    "import json\n",
    "import time\n",
    "import os\n",
    "from pandas.io.json import json_normalize\n",
    "from collections import defaultdict\n",
    "import pandas as pd\n",
    "import zipfile, io\n",
    "from IPython.display import Image\n",
    "\n",
    "%matplotlib inline\n",
    "%autosave 0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Request Parameter Details"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Request URL:  https://agflaskdev.eastus2.cloudapp.azure.com/flask_api/api/v1.0/CropIDmodel_Forecast\n",
    "\n",
    "1). __SHAPE__ (geometry, file/text, required): Desired area-of-interest. The structure of the geometry can be one of the following.\n",
    "    \n",
    "    i. JSON geometry objects returned by the arcgis rest api, (file/text) \n",
    "    \n",
    "    ii. GEOJSON (file/text)\n",
    "    \n",
    "    iii. Shapefile (file)\n",
    "       \n",
    "2). __CropSeason__(string): The year of interest to retrieve the crop type information of the area-of-interest.\n",
    "    \n",
    "    Parameter example: \"2018\"\n",
    "\n",
    "3). _ModelType(string)_: Classificaiton algorithums. This version of Crop Identification supports: Decision Tree and Neural Networks classification algorithum.\n",
    "\n",
    "    Prameter example:'TREE' or 'NN'(Optional, default as 'NN)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Request in Json"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The Crop Identification API service takes the request in Json format. Below are examples formatted in Json. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Request Example 1\n",
    "\n",
    "request ={\n",
    "    \"SHAPE\": \"{\\\"type\\\":\\\"Feature\\\",\\\"properties\\\":{},\\\"geometry\\\":{\\\"type\\\":\\\"Polygon\\\",\\\"coordinates\\\":[[[-100.953840994,38.5946753571],[-100.953832008,38.5948720599],[-100.953876941,38.5952162884],[-100.953957821,38.5955324152],[-100.953984781,38.5955745654],[-100.954029714,38.5957361407],[-100.954245394,38.5961716896],[-100.954452087,38.5964807873],[-100.95473966,38.5968179832],[-100.954910406,38.596965506],[-100.954910406,38.5969795557],[-100.954982299,38.5970287299],[-100.954982299,38.5970427797],[-100.955359739,38.5973378239],[-100.955377712,38.5973378239],[-100.955629338,38.5975134449],[-100.956042724,38.5977312143],[-100.956357257,38.5978646856],[-100.956707736,38.5979911318],[-100.957175042,38.598110553],[-100.957615388,38.5981878255],[-100.958055734,38.598229974],[-100.958514053,38.5982369988],[-100.958963386,38.5982088998],[-100.959412719,38.5981456769],[-100.959906984,38.5980332805],[-100.96023949,38.5979279087],[-100.960598957,38.5977874128],[-100.960976396,38.5976047676],[-100.961281942,38.597422122],[-100.961560528,38.5972113765],[-100.961578502,38.5972113765],[-100.961848101,38.5969865806],[-100.961982901,38.5968390579],[-100.962018848,38.5968179832],[-100.962189594,38.5966283107],[-100.962315407,38.5964526876],[-100.962405274,38.5964526876],[-100.962405274,38.5963894631],[-100.962369327,38.5963894631],[-100.962369327,38.5963754133],[-100.962513113,38.5961716896],[-100.96262994,38.5959539155],[-100.962800686,38.5955324152],[-100.962908526,38.595054712],[-100.962926499,38.5948580097],[-100.962890553,38.5948509846],[-100.962962446,38.5948650348],[-100.963025352,38.5947947839],[-100.962998393,38.5947877588],[-100.962989406,38.5947666835],[-100.962917513,38.5947526333],[-100.962935486,38.5947245329],[-100.962926499,38.5946894073],[-100.962881566,38.5947034575],[-100.962665886,38.5946823822],[-100.958541013,38.5946753571],[-100.9584152,38.5947175077],[-100.958316347,38.5947175077],[-100.958298374,38.5947034575],[-100.958154587,38.5946753571],[-100.953840994,38.5946753571]]]}}\",\n",
    "    \"ScalarVariables\": {\"CropSeason\": \"2018\"},\n",
    "    \"ModelType\":\"NN\"\n",
    "}\n",
    "\n",
    "#Request Example 2\n",
    "\n",
    "# request = {\n",
    "#     \"SHAPE\": \"{\\\"type\\\":\\\"Feature\\\",\\\"properties\\\":{},\\\"geometry\\\":{\\\"type\\\":\\\"Polygon\\\",\\\"coordinates\\\":[[[-93.7748032713,41.6148440891],[-93.7747312917,41.6148642376],[-93.7746593121,41.6149179668],[-93.7746683095,41.6149381153],[-93.7746413172,41.6149649799],[-93.7746233223,41.6150254252],[-93.7746233223,41.633700319],[-93.7748392611,41.633700319],[-93.7748392611,41.6511615865],[-93.7748842483,41.6513092587],[-93.7749742228,41.65136967],[-93.7751001871,41.6513830947],[-93.7751811642,41.6513629576],[-93.7752441463,41.6513226834],[-93.775298131,41.6512287103],[-93.7753251234,41.6513092587],[-93.7753611132,41.6513428205],[-93.7754420902,41.6513763823],[-93.7755410622,41.6513830947],[-93.7756580291,41.6513428205],[-93.7757300087,41.6512488474],[-93.7757300087,41.6445831177],[-93.7759549449,41.6445831177],[-93.7759549449,41.6150052768],[-93.7759279526,41.6149313992],[-93.7758919628,41.6148911022],[-93.7757749959,41.6148440891],[-93.775676024,41.6148440891],[-93.7756130418,41.6148642376],[-93.7755410622,41.6149179668],[-93.7755500596,41.6149313992],[-93.7755050724,41.6149918445],[-93.7754960749,41.6149448315],[-93.7754330928,41.6148776699],[-93.7753431183,41.6148440891],[-93.7752351489,41.6148440891],[-93.7751361769,41.6148843861],[-93.7751361769,41.6148978184],[-93.7751001871,41.6149179668],[-93.7751091846,41.6149313992],[-93.7750821922,41.6149851284],[-93.7750641973,41.6149918445],[-93.7750551999,41.6149448315],[-93.7749922177,41.6148776699],[-93.7749022432,41.6148440891],[-93.7748032713,41.6148440891]]]}}\",\n",
    "#     \"ScalarVariables\": {\n",
    "#         \"CropSeason\": \"2018\"\n",
    "#     },\n",
    "#     \"ModelType\":\"NN\"\n",
    "# }"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### API Function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def CropIdentification(request):\n",
    "    try:\n",
    "        url = 'https://agflaskdev.eastus2.cloudapp.azure.com/flask_api/api/v1.0/CropIDmodel_Forecast'\n",
    "        \n",
    "        response = requests.post(url, json = request,headers = {}).json()\n",
    "        \n",
    "        print(response)\n",
    "        \n",
    "        return response\n",
    "    \n",
    "    except Exception as e:\n",
    "        print(e)\n",
    "        raise e\n",
    "                             "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Calling API Function and Displaying Response\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'feature_averages': [{'Key': 'Greenweek18', 'Value': 1138.131570659558}, {'Key': 'Redweek18', 'Value': 1903.1859603449168}, {'Key': 'SWIR2week18', 'Value': 2391.667558326072}, {'Key': 'SWIR1week18', 'Value': 3338.836322033022}, {'Key': 'NIRweek18', 'Value': 2970.0740078383446}, {'Key': 'Blueweek18', 'Value': 779.824844896861}, {'Key': 'Greenweek20', 'Value': 2254.270159289066}, {'Key': 'Redweek20', 'Value': 2480.602444221482}, {'Key': 'SWIR2week20', 'Value': 17.602483063970034}, {'Key': 'SWIR1week20', 'Value': 3808.579113377245}, {'Key': 'NIRweek20', 'Value': 3536.6660938053815}, {'Key': 'Blueweek20', 'Value': 1975.3829592151317}, {'Key': 'Greenweek22', 'Value': 1013.7187401697631}, {'Key': 'Redweek22', 'Value': 1324.5397082727213}, {'Key': 'SWIR2week22', 'Value': 2392.3059762302105}, {'Key': 'SWIR1week22', 'Value': 3199.2655615880494}, {'Key': 'NIRweek22', 'Value': 2412.510195847856}, {'Key': 'Blueweek22', 'Value': 733.3521051359988}, {'Key': 'Greenweek24', 'Value': 928.849268847287}, {'Key': 'Redweek24', 'Value': 1069.7853810301349}, {'Key': 'SWIR2week24', 'Value': 1066.0881596873523}, {'Key': 'SWIR1week24', 'Value': 1902.9297659572896}, {'Key': 'NIRweek24', 'Value': 3292.298120071036}, {'Key': 'Blueweek24', 'Value': 643.9180616872748}, {'Key': 'Greenweek26', 'Value': 571.9230231878212}, {'Key': 'Redweek26', 'Value': 512.0971963633662}, {'Key': 'SWIR2week26', 'Value': 577.5711350554554}, {'Key': 'SWIR1week26', 'Value': 1254.004163243775}, {'Key': 'NIRweek26', 'Value': 3535.8988991057713}, {'Key': 'Blueweek26', 'Value': 344.2115098055459}, {'Key': 'Greenweek28', 'Value': 457.9029104885397}, {'Key': 'Redweek28', 'Value': 379.9113349957818}, {'Key': 'SWIR1week28', 'Value': 681.5643129864352}, {'Key': 'SWIR2week28', 'Value': 14.780317492926729}, {'Key': 'NIRweek28', 'Value': 3721.192446778267}, {'Key': 'Blueweek28', 'Value': 236.699024285531}, {'Key': 'Greenweek30', 'Value': 384.7649838193378}, {'Key': 'Redweek30', 'Value': 283.1936926800272}, {'Key': 'SWIR2week30', 'Value': 305.1543742073506}, {'Key': 'SWIR1week30', 'Value': 962.4707162781339}, {'Key': 'NIRweek30', 'Value': 3591.1494805204393}, {'Key': 'Blueweek30', 'Value': 204.9539935971929}, {'Key': 'Greenweek32', 'Value': 375.24875445591255}, {'Key': 'Redweek32', 'Value': 279.2847222138893}, {'Key': 'SWIR2week32', 'Value': 299.5264928749243}, {'Key': 'SWIR1week32', 'Value': 994.7986702873936}, {'Key': 'NIRweek32', 'Value': 3262.5500419977257}, {'Key': 'Blueweek32', 'Value': 216.0730864324732}, {'Key': 'Greenweek34', 'Value': 540.8961853834992}, {'Key': 'Redweek34', 'Value': 467.8558782624387}, {'Key': 'SWIR2week34', 'Value': 805.5621165630723}, {'Key': 'SWIR1week34', 'Value': 1417.8394552018106}, {'Key': 'NIRweek34', 'Value': 3102.557304281368}, {'Key': 'Blueweek34', 'Value': 266.59034645931484}, {'Key': 'Greenweek36', 'Value': 749.1587725403178}, {'Key': 'Redweek36', 'Value': 727.4151962193739}, {'Key': 'SWIR2week36', 'Value': 194.33282355324758}, {'Key': 'SWIR1week36', 'Value': 628.7585803430337}, {'Key': 'NIRweek36', 'Value': 2956.2606778525223}, {'Key': 'Blueweek36', 'Value': 621.9698331028843}, {'Key': 'GDD3', 'Value': 40.4415}, {'Key': 'Precipitation3', 'Value': 11.524}, {'Key': 'GDD4', 'Value': 88.57439999999998}, {'Key': 'Precipitation4', 'Value': 25.41900000000001}, {'Key': 'GDD5', 'Value': 567.5903999999999}, {'Key': 'Precipitation5', 'Value': 70.78399999999999}, {'Key': 'GDD6', 'Value': 808.3584}, {'Key': 'Precipitation6', 'Value': 152.91100000000003}, {'Key': 'GDD7', 'Value': 216.13589999999996}, {'Key': 'Precipitation7', 'Value': 1.4809999999999999}, {'Key': 'GDD8', 'Value': 0.0}, {'Key': 'Precipitation8', 'Value': 0.0}], 'raster_filename': 'result_cropidraster_20191204_211603_5071.tif', 'rasterinfo': {'CellSize': [0.0001, -0.0001], 'CoordinateSystem': 'GEOGCS[\"WGS 84\",DATUM[\"WGS_1984\",SPHEROID[\"WGS 84\",6378137,298.257223563,AUTHORITY[\"EPSG\",\"7030\"]],AUTHORITY[\"EPSG\",\"6326\"]],PRIMEM[\"Greenwich\",0],UNIT[\"degree\",0.0174532925199433],AUTHORITY[\"EPSG\",\"4326\"]]', 'Extent': '-100.963025352, 38.5946369988, -100.953925352, 38.5982369988', 'Legend': [{'Area': 4.969644751890395, 'AreaPercent': '3.82 %', 'AreaUnit': 'ac', 'Count': 101, 'CountAllPixels': 2645, 'CropID': 1, 'CropName': 'CORN_WET', 'color': '#a1d822'}, {'Area': 125.17600246345707, 'AreaPercent': '96.18 %', 'AreaUnit': 'ac', 'Count': 2544, 'CountAllPixels': 2645, 'CropID': 4, 'CropName': 'WHEAT_HRD_RD_SPR', 'color': '#d93757'}], 'pngb64': 'data:image/png;base64, iVBORw0KGgoAAAANSUhEUgAAAFsAAAAkCAYAAADmQkaNAAABCklEQVR4nO3XyxGCMBSF4SQ92AAbS7AU62NpKXaANdCEKx2MSbh53BMe598yA8PnmTBas6Fet/uscd/r83HRuG9utufDtXAl9fgB4Ng9gWOh4CHYWwSOpQmvir0nZD8NdBXsPSP7tURvin0kZL8W6E2wj4zsV4Puah9+Jmhj6t63eNlnQ/YrWXgR9tmhl+WgZx8jhP4txyMLm9DhpC5ibEKnk/iIsAkta81pFZvQeaW8ktiELivmFsUmdF0hv+p/kExeEJurbpPv+IdNaL14jCi3HK+LXWDt47IBfUZMbGBfbB4huo3TMHPZwIgNzBnDIwQVlw2M2MCIDYzYwBw/jri4bGB2nAYuG9QbP4BnTDQbWIwAAAAASUVORK5CYII='}}\n"
     ]
    }
   ],
   "source": [
    "CropIDresponse = CropIdentification(request)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Response Example 1\n",
    "CropIDresponse = {'feature_averages': [{'Key': 'Greenweek18', 'Value': 1138.131570659558}, {'Key': 'Redweek18', 'Value': 1903.1859603449168}, {'Key': 'SWIR2week18', 'Value': 2391.667558326072}, {'Key': 'SWIR1week18', 'Value': 3338.836322033022}, {'Key': 'NIRweek18', 'Value': 2970.0740078383446}, {'Key': 'Blueweek18', 'Value': 779.824844896861}, {'Key': 'Greenweek20', 'Value': 1007.8605842345153}, {'Key': 'Redweek20', 'Value': 2480.602444221482}, {'Key': 'SWIR2week20', 'Value': 17.602483063970034}, {'Key': 'SWIR1week20', 'Value': 3808.579113377245}, {'Key': 'NIRweek20', 'Value': 3536.6660938053815}, {'Key': 'Blueweek20', 'Value': 1975.3450576969717}, {'Key': 'Greenweek22', 'Value': 993.7888856711144}, {'Key': 'Redweek22', 'Value': 1324.5397082727213}, {'Key': 'SWIR2week22', 'Value': 2392.3059762302105}, {'Key': 'SWIR1week22', 'Value': 3199.2655615880494}, {'Key': 'NIRweek22', 'Value': 2412.510195847856}, {'Key': 'Blueweek22', 'Value': 733.3521051359988}, {'Key': 'Greenweek24', 'Value': 928.849268847287}, {'Key': 'Redweek24', 'Value': 1069.7853810301349}, {'Key': 'SWIR2week24', 'Value': 1066.0881596873523}, {'Key': 'SWIR1week24', 'Value': 1902.9297659572896}, {'Key': 'NIRweek24', 'Value': 3292.298120071036}, {'Key': 'Blueweek24', 'Value': 643.9180616872748}, {'Key': 'Greenweek26', 'Value': 571.9230231878212}, {'Key': 'Redweek26', 'Value': 512.0971963633662}, {'Key': 'SWIR2week26', 'Value': 577.5711350554554}, {'Key': 'SWIR1week26', 'Value': 1254.004163243775}, {'Key': 'NIRweek26', 'Value': 3535.8988991057713}, {'Key': 'Blueweek26', 'Value': 344.2115098055459}, {'Key': 'Greenweek28', 'Value': 457.9029104885397}, {'Key': 'Redweek28', 'Value': 379.21622211189487}, {'Key': 'SWIR1week28', 'Value': 677.788417488776}, {'Key': 'SWIR2week28', 'Value': 14.881174763569534}, {'Key': 'NIRweek28', 'Value': 3721.192446778267}, {'Key': 'Blueweek28', 'Value': 236.699024285531}, {'Key': 'Greenweek30', 'Value': 384.7649838193378}, {'Key': 'Redweek30', 'Value': 283.1936926800272}, {'Key': 'SWIR2week30', 'Value': 305.1543742073506}, {'Key': 'SWIR1week30', 'Value': 962.4707162781339}, {'Key': 'NIRweek30', 'Value': 3591.1494805204393}, {'Key': 'Blueweek30', 'Value': 204.9539935971929}, {'Key': 'Greenweek32', 'Value': 375.24875445591255}, {'Key': 'Redweek32', 'Value': 279.2847222138893}, {'Key': 'SWIR2week32', 'Value': 299.5264928749243}, {'Key': 'SWIR1week32', 'Value': 994.7986702873936}, {'Key': 'NIRweek32', 'Value': 3262.5500419977257}, {'Key': 'Blueweek32', 'Value': 216.0730864324732}, {'Key': 'Greenweek34', 'Value': 427.83056221801525}, {'Key': 'Redweek34', 'Value': 368.11916439871254}, {'Key': 'SWIR2week34', 'Value': 805.5621165630723}, {'Key': 'SWIR1week34', 'Value': 1417.8394552018106}, {'Key': 'NIRweek34', 'Value': 3102.557304281368}, {'Key': 'Blueweek34', 'Value': 266.59034645931484}, {'Key': 'Greenweek36', 'Value': 749.1587725403178}, {'Key': 'Redweek36', 'Value': 727.4151962193739}, {'Key': 'SWIR2week36', 'Value': 194.33282355324758}, {'Key': 'SWIR1week36', 'Value': 628.7585803430337}, {'Key': 'NIRweek36', 'Value': 2956.2606778525223}, {'Key': 'Blueweek36', 'Value': 621.9698331028843}, {'Key': 'GDD3', 'Value': 40.4415}, {'Key': 'Precipitation3', 'Value': 11.524}, {'Key': 'GDD4', 'Value': 88.57439999999998}, {'Key': 'Precipitation4', 'Value': 25.41900000000001}, {'Key': 'GDD5', 'Value': 567.5903999999999}, {'Key': 'Precipitation5', 'Value': 70.78399999999999}, {'Key': 'GDD6', 'Value': 808.3584}, {'Key': 'Precipitation6', 'Value': 152.91100000000003}, {'Key': 'GDD7', 'Value': 216.13589999999996}, {'Key': 'Precipitation7', 'Value': 1.4809999999999999}, {'Key': 'GDD8', 'Value': 0.0}, {'Key': 'Precipitation8', 'Value': 0.0}], 'raster_filename': 'result_cropidraster_20191126_232751_3827.tif', 'rasterinfo': {'CellSize': [0.0001, -0.0001], 'CoordinateSystem': 'GEOGCS[\"WGS 84\",DATUM[\"WGS_1984\",SPHEROID[\"WGS 84\",6378137,298.257223563,AUTHORITY[\"EPSG\",\"7030\"]],AUTHORITY[\"EPSG\",\"6326\"]],PRIMEM[\"Greenwich\",0],UNIT[\"degree\",0.0174532925199433],AUTHORITY[\"EPSG\",\"4326\"]]', 'Extent': '-100.963025352, 38.5946369988, -100.953925352, 38.5982369988', 'Legend': [{'Area': 4.969644751890395, 'AreaPercent': '3.82 %', 'AreaUnit': 'ac', 'Count': 101, 'CountAllPixels': 2645, 'CropID': 1, 'CropName': 'CORN_WET', 'color': '#7fb367'}, {'Area': 125.17600246345707, 'AreaPercent': '96.18 %', 'AreaUnit': 'ac', 'Count': 2544, 'CountAllPixels': 2645, 'CropID': 4, 'CropName': 'WHEAT_HRD_RD_SPR', 'color': '#b1de70'}], 'pngb64': 'data:image/png;base64, iVBORw0KGgoAAAANSUhEUgAAAFsAAAAkCAYAAADmQkaNAAABDklEQVR4nO3YyxGCMBSF4ZCxBRuwIVuxFFuxEXZsbcAC2LrSwZiEm8c9AXL+rTOgH2fi6GA21ON5e2lc93q5nzWum9rQ8uZauJJaPAA4dkvgUCh4CPYWgUNpwqti7wnZTQNdBXvPyG410atiHwnZrQZ6FewjI7uVoNvSm/cEbUzZ581edm/IbjkLz8LuHXpZCnryMULo31I8krAJ7U/qIsYmdDyJjwib0LLWnFaxCZ1WzCuKTei8Qm5BbEKX5fMr/gXJ5Hmxueo6uY5/2ITWi8eIcsvx2tALrH5cNqDPiIkN7PsXK48Q3cZp5rKRERuYNYZHCCouGxixgREbGLGBWX454uKygZ3GaW79HrrpDQsadk4r1itjAAAAAElFTkSuQmCC'}}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Output Summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "    #T_7653829e_16db_11ea_8e24_40a8f0580b71row0_col4 {\n",
       "            background-color:  #d93757;\n",
       "        }    #T_7653829e_16db_11ea_8e24_40a8f0580b71row1_col4 {\n",
       "            background-color:  #a1d822;\n",
       "        }</style>  \n",
       "<table id=\"T_7653829e_16db_11ea_8e24_40a8f0580b71\" > \n",
       "<thead>    <tr> \n",
       "        <th class=\"blank level0\" ></th> \n",
       "        <th class=\"col_heading level0 col0\" >CropName</th> \n",
       "        <th class=\"col_heading level0 col1\" >Area</th> \n",
       "        <th class=\"col_heading level0 col2\" >AreaUnit</th> \n",
       "        <th class=\"col_heading level0 col3\" >AreaPercent</th> \n",
       "        <th class=\"col_heading level0 col4\" >Color</th> \n",
       "    </tr></thead> \n",
       "<tbody>    <tr> \n",
       "        <th id=\"T_7653829e_16db_11ea_8e24_40a8f0580b71level0_row0\" class=\"row_heading level0 row0\" >1</th> \n",
       "        <td id=\"T_7653829e_16db_11ea_8e24_40a8f0580b71row0_col0\" class=\"data row0 col0\" >WHEAT_HRD_RD_SPR</td> \n",
       "        <td id=\"T_7653829e_16db_11ea_8e24_40a8f0580b71row0_col1\" class=\"data row0 col1\" >125</td> \n",
       "        <td id=\"T_7653829e_16db_11ea_8e24_40a8f0580b71row0_col2\" class=\"data row0 col2\" >ac</td> \n",
       "        <td id=\"T_7653829e_16db_11ea_8e24_40a8f0580b71row0_col3\" class=\"data row0 col3\" >96.18 %</td> \n",
       "        <td id=\"T_7653829e_16db_11ea_8e24_40a8f0580b71row0_col4\" class=\"data row0 col4\" >#d93757</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_7653829e_16db_11ea_8e24_40a8f0580b71level0_row1\" class=\"row_heading level0 row1\" >0</th> \n",
       "        <td id=\"T_7653829e_16db_11ea_8e24_40a8f0580b71row1_col0\" class=\"data row1 col0\" >CORN_WET</td> \n",
       "        <td id=\"T_7653829e_16db_11ea_8e24_40a8f0580b71row1_col1\" class=\"data row1 col1\" >4</td> \n",
       "        <td id=\"T_7653829e_16db_11ea_8e24_40a8f0580b71row1_col2\" class=\"data row1 col2\" >ac</td> \n",
       "        <td id=\"T_7653829e_16db_11ea_8e24_40a8f0580b71row1_col3\" class=\"data row1 col3\" >3.82 %</td> \n",
       "        <td id=\"T_7653829e_16db_11ea_8e24_40a8f0580b71row1_col4\" class=\"data row1 col4\" >#a1d822</td> \n",
       "    </tr></tbody> \n",
       "</table> "
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x14b2f9af2e8>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df=defaultdict(list)\n",
    "for value in CropIDresponse['rasterinfo']['Legend']:\n",
    "    df['CropName'].append(value['CropName'])\n",
    "    df['Area'].append(int(value['Area']))\n",
    "    df['AreaUnit'].append(value['AreaUnit'])\n",
    "    df['AreaPercent'].append(value['AreaPercent'])\n",
    "    df['Color'].append(value['color'])\n",
    "cropdf=pd.DataFrame.from_dict(df)\n",
    "cropdf = cropdf.sort_values(by = ['Area'], ascending=False).style.applymap(lambda x:\"background-color: %s\"%x, subset=['Color'])\n",
    "cropdf"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Displaying Output Image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64, iVBORw0KGgoAAAANSUhEUgAAAFsAAAAkCAYAAADmQkaNAAABCklEQVR4nO3XyxGCMBSF4SQ92AAbS7AU62NpKXaANdCEKx2MSbh53BMe598yA8PnmTBas6Fet/uscd/r83HRuG9utufDtXAl9fgB4Ng9gWOh4CHYWwSOpQmvir0nZD8NdBXsPSP7tURvin0kZL8W6E2wj4zsV4Puah9+Jmhj6t63eNlnQ/YrWXgR9tmhl+WgZx8jhP4txyMLm9DhpC5ibEKnk/iIsAkta81pFZvQeaW8ktiELivmFsUmdF0hv+p/kExeEJurbpPv+IdNaL14jCi3HK+LXWDt47IBfUZMbGBfbB4huo3TMHPZwIgNzBnDIwQVlw2M2MCIDYzYwBw/jri4bGB2nAYuG9QbP4BnTDQbWIwAAAAASUVORK5CYII=\" width=\"400\" height=\"200\"/>"
      ],
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Image\n",
    "cropImage = CropIDresponse['rasterinfo']['pngb64']\n",
    "\n",
    "Image(url = cropImage, width= 400, height =200)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# GET Request"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "GET Request for downloading the POST requested file to local machine."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Specify local path where file will be downloaded.\n",
    "local_path = r\"C:\\<Path to download directory>\" # E.g., r\"C:\\Users\\John_Doe\\Documents\\rasters\"\n",
    "\n",
    "# Create GET request payload.\n",
    "values = {'filename': CropIDresponse['raster_filename']}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "def cropID_get(values, local_path):\n",
    "    try:\n",
    "        url = 'https://agflaskdev.eastus2.cloudapp.azure.com/flask_api/api/v1.0/CropIDmodel_Forecast'\n",
    "    \n",
    "        download_path = os.path.join(local_path, values['filename'])\n",
    "     \n",
    "        response = requests.get(url, params=values)\n",
    "        open(download_path, 'wb').write(response.content)\n",
    "        \n",
    "        print(response.url)\n",
    "\n",
    "        return response\n",
    "    \n",
    "    except Exception as e:\n",
    "        print(e)\n",
    "        raise e"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "https://agflaskdev.eastus2.cloudapp.azure.com/flask_api/api/v1.0/CropIDmodel_Forecast?filename=result_cropidraster_20191204_211603_5071.tif\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Response [200]>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cropID_get(values, local_path)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To experience the usage of this service or other services provided by Ag-Analytics, please go to our API website page:\n",
    "    \n",
    "https://analytics.ag/ApiDeveloper"
   ]
  }
 ],
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  "kernelspec": {
   "display_name": "agflask-env",
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   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
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