TensorFlow_ObjectDetection_Demo_Toronto_TrafficNetwork.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Object Detection Toronto Demo: City Network of Capture Points\n",
    "Welcome to the object detection inference walkthrough!  This notebook will walk you step by step through the process of using a pre-trained model to detect objects in an image. Make sure to follow the [installation instructions](https://github.com/tensorflow/models/blob/master/object_detection/g3doc/installation.md) before you start."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import os\n",
    "import six.moves.urllib as urllib\n",
    "import sys\n",
    "import tarfile\n",
    "import tensorflow as tf\n",
    "import zipfile\n",
    "import getpass\n",
    "import shutil\n",
    "\n",
    "from collections import defaultdict\n",
    "from io import StringIO\n",
    "from matplotlib import pyplot as plt\n",
    "from PIL import Image\n",
    "\n",
    "from PIL import ImageGrab\n",
    "import time\n",
    "import pandas as pd\n",
    "\n",
    "import cv2\n",
    "\n",
    "import requests\n",
    "from io import BytesIO\n",
    "\n",
    "from copy import deepcopy\n",
    "\n",
    "import scipy.misc\n",
    "\n",
    "from datetime import datetime\n",
    "\n",
    "import arcgis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Env setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# This is needed to display the images.\n",
    "%matplotlib inline\n",
    "\n",
    "# This is needed since the notebook is stored in the object_detection folder.\n",
    "sys.path.append(\"..\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Establish Connection to ArcGIS Online via ArcGIS API for Python"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Authenticate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Attempting to log in to 'https://esrifederal.maps.arcgis.com'...\n",
      "Please sign in to your GIS and paste the code that is obtained below.\n",
      "If a web browser does not automatically open, please navigate to the URL below yourself instead.\n",
      "Opening web browser to navigate to: https://esrifederal.maps.arcgis.com/sharing/rest/oauth2/authorize?client_id=wt3QUR1M4eum0TVI&response_type=code&expiration=-1&redirect_uri=urn%3Aietf%3Awg%3Aoauth%3A2.0%3Aoob\n",
      "Enter code obtained on signing in using SAML: ········\n",
      "Successfully logged in as: albe9057@esri.com_esrifederal\n"
     ]
    }
   ],
   "source": [
    "portals_dict = {\n",
    "    \"esrifederal_gis\": r\"https://esrifederal.maps.arcgis.com\",\n",
    "    \"natgov_gis\": r\"http://esri-natgov105.eastus.cloudapp.azure.com/arcgis\",\n",
    "    \"dot_gis\": r\"http://dot.esri.com/portal\",\n",
    "    \"dev_gis\": r\"http://govdev.eastus.cloudapp.azure.com/arcgis\",\n",
    "    \"local_gis\": r\"https://anieto.esri.com/arcgis\",\n",
    "    \"brett_gis\": r\"https://agsbase.dcwebgis.net/portal\",\n",
    "    \"bill_gis\": r\"https://idt.esri.com/portal\"\n",
    "}\n",
    "\n",
    "gis_url = portals_dict[\"esrifederal_gis\"]\n",
    "\n",
    "if gis_url == portals_dict[\"esrifederal_gis\"]:\n",
    "    gis_app_id = r\"wt3QUR1M4eum0TVI\"\n",
    "    print(\"Attempting to log in to '{0}'...\".format(gis_url))\n",
    "    gis = arcgis.gis.GIS(gis_url, client_id=gis_app_id)\n",
    "    print(\"Successfully logged in as: \" + gis.properties.user.username)\n",
    "else:\n",
    "    gis_username = getpass.getpass(prompt=\"Username: \")\n",
    "    gis_pw = getpass.getpass(prompt=\"Password: \")\n",
    "    print(\"Attempting to log in to '{0}'...\".format(gis_url))\n",
    "    gis = arcgis.gis.GIS(gis_url, gis_username, gis_pw, verify_cert=False)\n",
    "    print(\"Successfully logged in as: \" + gis.properties.user.username)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Object detection imports\n",
    "Here are the imports from the object detection module."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from utils import label_map_util\n",
    "\n",
    "from utils import visualization_utils as vis_util"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Model preparation "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Variables\n",
    "\n",
    "Any model exported using the `export_inference_graph.py` tool can be loaded here simply by changing `PATH_TO_CKPT` to point to a new .pb file.  \n",
    "\n",
    "By default we use an \"SSD with Mobilenet\" model here. See the [detection model zoo](https://github.com/tensorflow/models/blob/master/object_detection/g3doc/detection_model_zoo.md) for a list of other models that can be run out-of-the-box with varying speeds and accuracies."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model: SSD Mobilenet on COCO"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# What model to download.\n",
    "MODEL_NAME = 'ssd_mobilenet_v1_coco_11_06_2017'\n",
    "MODEL_FILE = MODEL_NAME + '.tar.gz'\n",
    "DOWNLOAD_BASE = 'http://download.tensorflow.org/models/object_detection/'\n",
    "\n",
    "# Path to frozen detection graph. This is the actual model that is used for the object detection.\n",
    "PATH_TO_CKPT = MODEL_NAME + '/frozen_inference_graph.pb'\n",
    "\n",
    "# List of the strings that is used to add correct label for each box.\n",
    "PATH_TO_LABELS = os.path.join('data', 'mscoco_label_map.pbtxt')\n",
    "\n",
    "NUM_CLASSES = 90"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load a (frozen) Tensorflow model into memory."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "detection_graph = tf.Graph()\n",
    "with detection_graph.as_default():\n",
    "    od_graph_def = tf.GraphDef()\n",
    "    with tf.gfile.GFile(PATH_TO_CKPT, 'rb') as fid:\n",
    "        serialized_graph = fid.read()\n",
    "        od_graph_def.ParseFromString(serialized_graph)\n",
    "        tf.import_graph_def(od_graph_def, name='')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Loading label map\n",
    "Label maps map indices to category names, so that when our convolution network predicts `5`, we know that this corresponds to `airplane`.  Here we use internal utility functions, but anything that returns a dictionary mapping integers to appropriate string labels would be fine"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "label_map = label_map_util.load_labelmap(PATH_TO_LABELS)\n",
    "categories = label_map_util.convert_label_map_to_categories(label_map, max_num_classes=NUM_CLASSES, use_display_name=True)\n",
    "category_index = label_map_util.create_category_index(categories)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Helper code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def load_image_into_numpy_array(image):\n",
    "  (im_width, im_height) = image.size\n",
    "  return np.array(image.getdata()).reshape(\n",
    "      (im_height, im_width, 3)).astype(np.uint8)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is a helper function that takes the detection graph output tensor (np arrays), stacks the classes and scores, and determines if the class for a person (1) is available within a certain score and within a certain amount of objects"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def object_counter(classes_arr, scores_arr, score_thresh=0.5):\n",
    "    # Process the numpy array of classes from the model\n",
    "    stacked_arr = np.stack((classes_arr, scores_arr), axis=-1)\n",
    "    # Convert to pandas dataframe for easier querying\n",
    "    detection_df = pd.DataFrame(stacked_arr)\n",
    "    # Retrieve total count of cars with score threshold above param value\n",
    "    detected_cars = detection_df[(detection_df[0] == 3.0) & (detection_df[1] > score_thresh)]\n",
    "    detected_people =  detection_df[(detection_df[0] == 1.0) & (detection_df[1] > score_thresh)]\n",
    "    detected_bicycles =  detection_df[(detection_df[0] == 2.0) & (detection_df[1] > score_thresh)]\n",
    "    detected_motorcycles =  detection_df[(detection_df[0] == 4.0) & (detection_df[1] > score_thresh)]\n",
    "    detected_buses =  detection_df[(detection_df[0] == 6.0) & (detection_df[1] > score_thresh)]\n",
    "    detected_trucks =  detection_df[(detection_df[0] == 8.0) & (detection_df[1] > score_thresh)]\n",
    "    \n",
    "    car_count = len(detected_cars)\n",
    "    people_count = len(detected_people)\n",
    "    bicycle_count = len(detected_bicycles)\n",
    "    motorcycle_count = len(detected_motorcycles)\n",
    "    bus_count = len(detected_buses)\n",
    "    truck_count = len(detected_trucks)\n",
    "\n",
    "    return car_count, people_count, bicycle_count, motorcycle_count, bus_count, truck_count\n",
    "\n",
    "def return_lat(row):\n",
    "    return row['location']['latitude']\n",
    "\n",
    "def return_lon(row):\n",
    "    return row['location']['longitude']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Network Camera Processing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Camera Number</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>Main Road</th>\n",
       "      <th>Cross Street</th>\n",
       "      <th>Group</th>\n",
       "      <th>Traffic Image</th>\n",
       "      <th>North Reference Static Image</th>\n",
       "      <th>South Reference Static Image</th>\n",
       "      <th>East Reference Static Image</th>\n",
       "      <th>West Reference Static Image</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Camera8001</td>\n",
       "      <td>43.643023</td>\n",
       "      <td>-79.381606</td>\n",
       "      <td>YORK ST</td>\n",
       "      <td>BREMNER BLVD</td>\n",
       "      <td>Arterial</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
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       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Camera8002</td>\n",
       "      <td>43.642163</td>\n",
       "      <td>-79.384267</td>\n",
       "      <td>BREMNER BLVD</td>\n",
       "      <td>LOWER SIMCOE ST</td>\n",
       "      <td>Arterial</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Camera8003</td>\n",
       "      <td>43.649405</td>\n",
       "      <td>-79.371467</td>\n",
       "      <td>JARVIS ST</td>\n",
       "      <td>FRONT ST E</td>\n",
       "      <td>Arterial</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Camera8004</td>\n",
       "      <td>43.645097</td>\n",
       "      <td>-79.382773</td>\n",
       "      <td>UNIVERSITY AVE</td>\n",
       "      <td>FRONT ST W / YORK ST</td>\n",
       "      <td>Arterial</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Camera8005</td>\n",
       "      <td>43.644628</td>\n",
       "      <td>-79.385060</td>\n",
       "      <td>FRONT ST W</td>\n",
       "      <td>SIMCOE ST / LOWER SIMCOE ST</td>\n",
       "      <td>Arterial</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Camera8006</td>\n",
       "      <td>43.643800</td>\n",
       "      <td>-79.389043</td>\n",
       "      <td>FRONT ST W</td>\n",
       "      <td>JOHN ST / PRIVATE ACCESS</td>\n",
       "      <td>Arterial</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Camera8007</td>\n",
       "      <td>43.642683</td>\n",
       "      <td>-79.393781</td>\n",
       "      <td>SPADINA AVE</td>\n",
       "      <td>FRONT ST W</td>\n",
       "      <td>Arterial</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Camera8008</td>\n",
       "      <td>43.640830</td>\n",
       "      <td>-79.401523</td>\n",
       "      <td>BATHURST ST</td>\n",
       "      <td>FRONT ST W</td>\n",
       "      <td>Arterial</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Camera8009</td>\n",
       "      <td>43.650278</td>\n",
       "      <td>-79.372145</td>\n",
       "      <td>JARVIS ST</td>\n",
       "      <td>KING ST E</td>\n",
       "      <td>Arterial</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Camera8010</td>\n",
       "      <td>43.652849</td>\n",
       "      <td>-79.363390</td>\n",
       "      <td>KING ST E</td>\n",
       "      <td>PARLIAMENT ST</td>\n",
       "      <td>Arterial</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Camera8011</td>\n",
       "      <td>43.653433</td>\n",
       "      <td>-79.363641</td>\n",
       "      <td>ADELAIDE ST E</td>\n",
       "      <td>PARLIAMENT ST</td>\n",
       "      <td>Arterial</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Camera8012</td>\n",
       "      <td>43.651208</td>\n",
       "      <td>-79.375016</td>\n",
       "      <td>ADELAIDE ST E</td>\n",
       "      <td>CHURCH ST</td>\n",
       "      <td>Arterial</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Camera8013</td>\n",
       "      <td>43.649980</td>\n",
       "      <td>-79.380931</td>\n",
       "      <td>BAY ST</td>\n",
       "      <td>ADELAIDE ST W</td>\n",
       "      <td>Arterial</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Camera8014</td>\n",
       "      <td>43.648926</td>\n",
       "      <td>-79.385529</td>\n",
       "      <td>UNIVERSITY AVE</td>\n",
       "      <td>ADELAIDE ST W</td>\n",
       "      <td>Arterial</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Camera8015</td>\n",
       "      <td>43.648551</td>\n",
       "      <td>-79.386682</td>\n",
       "      <td>ADELAIDE ST W</td>\n",
       "      <td>SIMCOE ST</td>\n",
       "      <td>Arterial</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Camera8016</td>\n",
       "      <td>43.654642</td>\n",
       "      <td>-79.364157</td>\n",
       "      <td>RICHMOND ST E</td>\n",
       "      <td>PARLIAMENT ST</td>\n",
       "      <td>Arterial</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Camera8017</td>\n",
       "      <td>43.652484</td>\n",
       "      <td>-79.375551</td>\n",
       "      <td>RICHMOND ST E</td>\n",
       "      <td>CHURCH ST</td>\n",
       "      <td>Arterial</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Camera8018</td>\n",
       "      <td>43.651112</td>\n",
       "      <td>-79.381613</td>\n",
       "      <td>BAY ST</td>\n",
       "      <td>RICHMOND ST W</td>\n",
       "      <td>Arterial</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Camera8019</td>\n",
       "      <td>43.649859</td>\n",
       "      <td>-79.386705</td>\n",
       "      <td>UNIVERSITY AVE</td>\n",
       "      <td>RICHMOND ST W</td>\n",
       "      <td>Arterial</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Camera8020</td>\n",
       "      <td>43.647687</td>\n",
       "      <td>-79.396344</td>\n",
       "      <td>SPADINA AVE</td>\n",
       "      <td>RICHMOND ST W</td>\n",
       "      <td>Arterial</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Camera8021</td>\n",
       "      <td>43.650771</td>\n",
       "      <td>-79.387149</td>\n",
       "      <td>UNIVERSITY AVE</td>\n",
       "      <td>QUEEN ST W</td>\n",
       "      <td>Arterial</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Camera8022</td>\n",
       "      <td>43.650730</td>\n",
       "      <td>-79.386467</td>\n",
       "      <td>UNIVERSITY AVE</td>\n",
       "      <td>QUEEN ST W</td>\n",
       "      <td>Arterial</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Camera8023</td>\n",
       "      <td>43.639569</td>\n",
       "      <td>-79.460077</td>\n",
       "      <td>THE QUEENSWAY</td>\n",
       "      <td>COLBORNE LODGE DR</td>\n",
       "      <td>Arterial</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Camera8024</td>\n",
       "      <td>43.638665</td>\n",
       "      <td>-79.446060</td>\n",
       "      <td>THE QUEENSWAY</td>\n",
       "      <td>KING ST W / RONCESVALLES AVE</td>\n",
       "      <td>Arterial</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Camera8025</td>\n",
       "      <td>43.638499</td>\n",
       "      <td>-79.446396</td>\n",
       "      <td>THE QUEENSWAY</td>\n",
       "      <td>KING ST W / RONCESVALLES AVE</td>\n",
       "      <td>Arterial</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Camera8026</td>\n",
       "      <td>43.637925</td>\n",
       "      <td>-79.466725</td>\n",
       "      <td>THE QUEENSWAY</td>\n",
       "      <td>ELLIS AVE</td>\n",
       "      <td>Arterial</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Camera8027</td>\n",
       "      <td>43.637300</td>\n",
       "      <td>-79.470459</td>\n",
       "      <td>THE QUEENSWAY</td>\n",
       "      <td>WINDERMERE AVE</td>\n",
       "      <td>Arterial</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Camera8028</td>\n",
       "      <td>43.623638</td>\n",
       "      <td>-79.515258</td>\n",
       "      <td>THE QUEENSWAY</td>\n",
       "      <td>ISLINGTON AVE</td>\n",
       "      <td>Arterial</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Camera8030</td>\n",
       "      <td>43.620991</td>\n",
       "      <td>-79.527264</td>\n",
       "      <td>KIPLING AVE</td>\n",
       "      <td>THE QUEENSWAY</td>\n",
       "      <td>Arterial</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Camera8031</td>\n",
       "      <td>43.656875</td>\n",
       "      <td>-79.374830</td>\n",
       "      <td>JARVIS ST</td>\n",
       "      <td>DUNDAS ST E</td>\n",
       "      <td>Arterial</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>249</th>\n",
       "      <td>Camera9312</td>\n",
       "      <td>43.631690</td>\n",
       "      <td>-79.431187</td>\n",
       "      <td>LAKE SHORE BLVD W</td>\n",
       "      <td>BRITISH COLUMBIA RD / LAKESHORE BRITISH COLUMB...</td>\n",
       "      <td>Lake Shore</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>250</th>\n",
       "      <td>Camera9313</td>\n",
       "      <td>43.632021</td>\n",
       "      <td>-79.430317</td>\n",
       "      <td>LAKE SHORE BLVD W</td>\n",
       "      <td>BRITISH COLUMBIA RD / LAKESHORE BRITISH COLUMB...</td>\n",
       "      <td>Lake Shore</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td></td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>251</th>\n",
       "      <td>Camera9314</td>\n",
       "      <td>43.632580</td>\n",
       "      <td>-79.436398</td>\n",
       "      <td>LAKE SHORE BLVD W</td>\n",
       "      <td>OARSMAN DR</td>\n",
       "      <td>Lake Shore</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>252</th>\n",
       "      <td>Camera9315</td>\n",
       "      <td>43.637321</td>\n",
       "      <td>-79.450137</td>\n",
       "      <td>LAKE SHORE BLVD W</td>\n",
       "      <td>PRIVATE ACCESS</td>\n",
       "      <td>Lake Shore</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253</th>\n",
       "      <td>Camera9316</td>\n",
       "      <td>43.638202</td>\n",
       "      <td>-79.455976</td>\n",
       "      <td>LAKE SHORE BLVD W</td>\n",
       "      <td>COLBORNE LODGE DR</td>\n",
       "      <td>Lake Shore</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>254</th>\n",
       "      <td>Camera9317</td>\n",
       "      <td>43.637632</td>\n",
       "      <td>-79.458943</td>\n",
       "      <td>LAKE SHORE BLVD W</td>\n",
       "      <td>COLBORNE LODGE DR</td>\n",
       "      <td>Lake Shore</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td></td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>255</th>\n",
       "      <td>Camera9318</td>\n",
       "      <td>43.636244</td>\n",
       "      <td>-79.465303</td>\n",
       "      <td>LAKE SHORE BLVD W</td>\n",
       "      <td>ELLIS AVE</td>\n",
       "      <td>Lake Shore</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>256</th>\n",
       "      <td>Camera9319</td>\n",
       "      <td>43.631298</td>\n",
       "      <td>-79.472649</td>\n",
       "      <td>LAKE SHORE BLVD W</td>\n",
       "      <td>PALACE PIER CRT</td>\n",
       "      <td>Lake Shore</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>257</th>\n",
       "      <td>Camera9320</td>\n",
       "      <td>43.631219</td>\n",
       "      <td>-79.474692</td>\n",
       "      <td>LAKE SHORE BLVD W</td>\n",
       "      <td>PALACE PIER CRT</td>\n",
       "      <td>Lake Shore</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>258</th>\n",
       "      <td>Camera9321</td>\n",
       "      <td>43.629104</td>\n",
       "      <td>-79.478597</td>\n",
       "      <td>LAKE SHORE BLVD W</td>\n",
       "      <td>PALACE PIER CRT</td>\n",
       "      <td>Lake Shore</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td></td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>259</th>\n",
       "      <td>Camera9322</td>\n",
       "      <td>43.623096</td>\n",
       "      <td>-79.481494</td>\n",
       "      <td>LAKE SHORE BLVD W</td>\n",
       "      <td>PARK LAWN RD / MARINE PARADE DR</td>\n",
       "      <td>Lake Shore</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260</th>\n",
       "      <td>Camera9323</td>\n",
       "      <td>43.659251</td>\n",
       "      <td>-79.328950</td>\n",
       "      <td>LAKE SHORE BLVD E</td>\n",
       "      <td>LESLIE ST</td>\n",
       "      <td>Lake Shore</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261</th>\n",
       "      <td>Camera9324</td>\n",
       "      <td>43.662173</td>\n",
       "      <td>-79.314756</td>\n",
       "      <td>LAKE SHORE BLVD E</td>\n",
       "      <td>COXWELL AVE / ASHBRIDGES BAY PARK RD</td>\n",
       "      <td>Lake Shore</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>262</th>\n",
       "      <td>Camera9325</td>\n",
       "      <td>43.648046</td>\n",
       "      <td>-79.354786</td>\n",
       "      <td>LAKE SHORE BLVD E</td>\n",
       "      <td>CHERRY ST</td>\n",
       "      <td>Lake Shore</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>263</th>\n",
       "      <td>Camera9326</td>\n",
       "      <td>43.649304</td>\n",
       "      <td>-79.356790</td>\n",
       "      <td>LAKE SHORE BLVD E</td>\n",
       "      <td>CHERRY ST</td>\n",
       "      <td>Lake Shore</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td></td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>264</th>\n",
       "      <td>Camera9327</td>\n",
       "      <td>43.646165</td>\n",
       "      <td>-79.366392</td>\n",
       "      <td>LAKE SHORE BLVD E</td>\n",
       "      <td>LOWER SHERBOURNE ST</td>\n",
       "      <td>Lake Shore</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>265</th>\n",
       "      <td>Camera9328</td>\n",
       "      <td>43.646365</td>\n",
       "      <td>-79.366433</td>\n",
       "      <td>LAKE SHORE BLVD E</td>\n",
       "      <td>LOWER SHERBOURNE ST</td>\n",
       "      <td>Lake Shore</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>266</th>\n",
       "      <td>Camera9329</td>\n",
       "      <td>43.640341</td>\n",
       "      <td>-79.383321</td>\n",
       "      <td>LAKE SHORE BLVD W</td>\n",
       "      <td>LOWER SIMCOE ST</td>\n",
       "      <td>Lake Shore</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>267</th>\n",
       "      <td>Camera9330</td>\n",
       "      <td>43.638861</td>\n",
       "      <td>-79.392309</td>\n",
       "      <td>LAKE SHORE BLVD W</td>\n",
       "      <td>SPADINA AVE</td>\n",
       "      <td>Lake Shore</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>268</th>\n",
       "      <td>Camera9331</td>\n",
       "      <td>43.636708</td>\n",
       "      <td>-79.399813</td>\n",
       "      <td>LAKE SHORE BLVD W</td>\n",
       "      <td>BATHURST ST / FLEET ST</td>\n",
       "      <td>Lake Shore</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>269</th>\n",
       "      <td>Camera9332</td>\n",
       "      <td>43.635520</td>\n",
       "      <td>-79.407257</td>\n",
       "      <td>LAKE SHORE BLVD W</td>\n",
       "      <td>FORT YORK BLVD</td>\n",
       "      <td>Lake Shore</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td></td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>270</th>\n",
       "      <td>Camera9333</td>\n",
       "      <td>43.638205</td>\n",
       "      <td>-79.453860</td>\n",
       "      <td>LAKE SHORE BLVD W</td>\n",
       "      <td>PARKSIDE DR</td>\n",
       "      <td>Lake Shore</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>271</th>\n",
       "      <td>Camera9400</td>\n",
       "      <td>43.698513</td>\n",
       "      <td>-79.436464</td>\n",
       "      <td>W R ALLEN RD</td>\n",
       "      <td>EGLINTON AVE W</td>\n",
       "      <td>Allen</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td></td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>272</th>\n",
       "      <td>Camera9401</td>\n",
       "      <td>43.702742</td>\n",
       "      <td>-79.438170</td>\n",
       "      <td>W R ALLEN RD</td>\n",
       "      <td>ELM RIDGE DR</td>\n",
       "      <td>Allen</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>273</th>\n",
       "      <td>Camera9402</td>\n",
       "      <td>43.707561</td>\n",
       "      <td>-79.440666</td>\n",
       "      <td>W R ALLEN RD</td>\n",
       "      <td>VIEWMOUNT AVE</td>\n",
       "      <td>Allen</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>274</th>\n",
       "      <td>Camera9403</td>\n",
       "      <td>43.711167</td>\n",
       "      <td>-79.442952</td>\n",
       "      <td>W R ALLEN RD</td>\n",
       "      <td>GLENGROVE AVE</td>\n",
       "      <td>Allen</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>275</th>\n",
       "      <td>Camera9404</td>\n",
       "      <td>43.716403</td>\n",
       "      <td>-79.444987</td>\n",
       "      <td>W R ALLEN RD</td>\n",
       "      <td>LAWRENCE AVE W</td>\n",
       "      <td>Allen</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>276</th>\n",
       "      <td>Camera9405</td>\n",
       "      <td>43.728089</td>\n",
       "      <td>-79.448831</td>\n",
       "      <td>W R ALLEN RD</td>\n",
       "      <td>401 C E ALLEN RD RAMP</td>\n",
       "      <td>Allen</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td></td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>277</th>\n",
       "      <td>Camera9406</td>\n",
       "      <td>43.739554</td>\n",
       "      <td>-79.452767</td>\n",
       "      <td>W R ALLEN RD</td>\n",
       "      <td>TRANSIT RD</td>\n",
       "      <td>Allen</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td></td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>278</th>\n",
       "      <td>Camera9407</td>\n",
       "      <td>43.749920</td>\n",
       "      <td>-79.463787</td>\n",
       "      <td>W R ALLEN RD</td>\n",
       "      <td>SHEPPARD AVE W</td>\n",
       "      <td>Allen</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "      <td>http://opendata.toronto.ca/transportation/tmc...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>279 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Camera Number   Latitude  Longitude          Main Road  \\\n",
       "0      Camera8001  43.643023 -79.381606            YORK ST   \n",
       "1      Camera8002  43.642163 -79.384267       BREMNER BLVD   \n",
       "2      Camera8003  43.649405 -79.371467          JARVIS ST   \n",
       "3      Camera8004  43.645097 -79.382773     UNIVERSITY AVE   \n",
       "4      Camera8005  43.644628 -79.385060         FRONT ST W   \n",
       "5      Camera8006  43.643800 -79.389043         FRONT ST W   \n",
       "6      Camera8007  43.642683 -79.393781        SPADINA AVE   \n",
       "7      Camera8008  43.640830 -79.401523        BATHURST ST   \n",
       "8      Camera8009  43.650278 -79.372145          JARVIS ST   \n",
       "9      Camera8010  43.652849 -79.363390          KING ST E   \n",
       "10     Camera8011  43.653433 -79.363641      ADELAIDE ST E   \n",
       "11     Camera8012  43.651208 -79.375016      ADELAIDE ST E   \n",
       "12     Camera8013  43.649980 -79.380931             BAY ST   \n",
       "13     Camera8014  43.648926 -79.385529     UNIVERSITY AVE   \n",
       "14     Camera8015  43.648551 -79.386682      ADELAIDE ST W   \n",
       "15     Camera8016  43.654642 -79.364157      RICHMOND ST E   \n",
       "16     Camera8017  43.652484 -79.375551      RICHMOND ST E   \n",
       "17     Camera8018  43.651112 -79.381613             BAY ST   \n",
       "18     Camera8019  43.649859 -79.386705     UNIVERSITY AVE   \n",
       "19     Camera8020  43.647687 -79.396344        SPADINA AVE   \n",
       "20     Camera8021  43.650771 -79.387149     UNIVERSITY AVE   \n",
       "21     Camera8022  43.650730 -79.386467     UNIVERSITY AVE   \n",
       "22     Camera8023  43.639569 -79.460077      THE QUEENSWAY   \n",
       "23     Camera8024  43.638665 -79.446060      THE QUEENSWAY   \n",
       "24     Camera8025  43.638499 -79.446396      THE QUEENSWAY   \n",
       "25     Camera8026  43.637925 -79.466725      THE QUEENSWAY   \n",
       "26     Camera8027  43.637300 -79.470459      THE QUEENSWAY   \n",
       "27     Camera8028  43.623638 -79.515258      THE QUEENSWAY   \n",
       "28     Camera8030  43.620991 -79.527264        KIPLING AVE   \n",
       "29     Camera8031  43.656875 -79.374830          JARVIS ST   \n",
       "..            ...        ...        ...                ...   \n",
       "249    Camera9312  43.631690 -79.431187  LAKE SHORE BLVD W   \n",
       "250    Camera9313  43.632021 -79.430317  LAKE SHORE BLVD W   \n",
       "251    Camera9314  43.632580 -79.436398  LAKE SHORE BLVD W   \n",
       "252    Camera9315  43.637321 -79.450137  LAKE SHORE BLVD W   \n",
       "253    Camera9316  43.638202 -79.455976  LAKE SHORE BLVD W   \n",
       "254    Camera9317  43.637632 -79.458943  LAKE SHORE BLVD W   \n",
       "255    Camera9318  43.636244 -79.465303  LAKE SHORE BLVD W   \n",
       "256    Camera9319  43.631298 -79.472649  LAKE SHORE BLVD W   \n",
       "257    Camera9320  43.631219 -79.474692  LAKE SHORE BLVD W   \n",
       "258    Camera9321  43.629104 -79.478597  LAKE SHORE BLVD W   \n",
       "259    Camera9322  43.623096 -79.481494  LAKE SHORE BLVD W   \n",
       "260    Camera9323  43.659251 -79.328950  LAKE SHORE BLVD E   \n",
       "261    Camera9324  43.662173 -79.314756  LAKE SHORE BLVD E   \n",
       "262    Camera9325  43.648046 -79.354786  LAKE SHORE BLVD E   \n",
       "263    Camera9326  43.649304 -79.356790  LAKE SHORE BLVD E   \n",
       "264    Camera9327  43.646165 -79.366392  LAKE SHORE BLVD E   \n",
       "265    Camera9328  43.646365 -79.366433  LAKE SHORE BLVD E   \n",
       "266    Camera9329  43.640341 -79.383321  LAKE SHORE BLVD W   \n",
       "267    Camera9330  43.638861 -79.392309  LAKE SHORE BLVD W   \n",
       "268    Camera9331  43.636708 -79.399813  LAKE SHORE BLVD W   \n",
       "269    Camera9332  43.635520 -79.407257  LAKE SHORE BLVD W   \n",
       "270    Camera9333  43.638205 -79.453860  LAKE SHORE BLVD W   \n",
       "271    Camera9400  43.698513 -79.436464       W R ALLEN RD   \n",
       "272    Camera9401  43.702742 -79.438170       W R ALLEN RD   \n",
       "273    Camera9402  43.707561 -79.440666       W R ALLEN RD   \n",
       "274    Camera9403  43.711167 -79.442952       W R ALLEN RD   \n",
       "275    Camera9404  43.716403 -79.444987       W R ALLEN RD   \n",
       "276    Camera9405  43.728089 -79.448831       W R ALLEN RD   \n",
       "277    Camera9406  43.739554 -79.452767       W R ALLEN RD   \n",
       "278    Camera9407  43.749920 -79.463787       W R ALLEN RD   \n",
       "\n",
       "                                          Cross Street       Group  \\\n",
       "0                                         BREMNER BLVD    Arterial   \n",
       "1                                      LOWER SIMCOE ST    Arterial   \n",
       "2                                           FRONT ST E    Arterial   \n",
       "3                                 FRONT ST W / YORK ST    Arterial   \n",
       "4                          SIMCOE ST / LOWER SIMCOE ST    Arterial   \n",
       "5                             JOHN ST / PRIVATE ACCESS    Arterial   \n",
       "6                                           FRONT ST W    Arterial   \n",
       "7                                           FRONT ST W    Arterial   \n",
       "8                                            KING ST E    Arterial   \n",
       "9                                        PARLIAMENT ST    Arterial   \n",
       "10                                       PARLIAMENT ST    Arterial   \n",
       "11                                           CHURCH ST    Arterial   \n",
       "12                                       ADELAIDE ST W    Arterial   \n",
       "13                                       ADELAIDE ST W    Arterial   \n",
       "14                                           SIMCOE ST    Arterial   \n",
       "15                                       PARLIAMENT ST    Arterial   \n",
       "16                                           CHURCH ST    Arterial   \n",
       "17                                       RICHMOND ST W    Arterial   \n",
       "18                                       RICHMOND ST W    Arterial   \n",
       "19                                       RICHMOND ST W    Arterial   \n",
       "20                                          QUEEN ST W    Arterial   \n",
       "21                                          QUEEN ST W    Arterial   \n",
       "22                                   COLBORNE LODGE DR    Arterial   \n",
       "23                        KING ST W / RONCESVALLES AVE    Arterial   \n",
       "24                        KING ST W / RONCESVALLES AVE    Arterial   \n",
       "25                                           ELLIS AVE    Arterial   \n",
       "26                                      WINDERMERE AVE    Arterial   \n",
       "27                                       ISLINGTON AVE    Arterial   \n",
       "28                                       THE QUEENSWAY    Arterial   \n",
       "29                                         DUNDAS ST E    Arterial   \n",
       "..                                                 ...         ...   \n",
       "249  BRITISH COLUMBIA RD / LAKESHORE BRITISH COLUMB...  Lake Shore   \n",
       "250  BRITISH COLUMBIA RD / LAKESHORE BRITISH COLUMB...  Lake Shore   \n",
       "251                                         OARSMAN DR  Lake Shore   \n",
       "252                                     PRIVATE ACCESS  Lake Shore   \n",
       "253                                  COLBORNE LODGE DR  Lake Shore   \n",
       "254                                  COLBORNE LODGE DR  Lake Shore   \n",
       "255                                          ELLIS AVE  Lake Shore   \n",
       "256                                    PALACE PIER CRT  Lake Shore   \n",
       "257                                    PALACE PIER CRT  Lake Shore   \n",
       "258                                    PALACE PIER CRT  Lake Shore   \n",
       "259                    PARK LAWN RD / MARINE PARADE DR  Lake Shore   \n",
       "260                                          LESLIE ST  Lake Shore   \n",
       "261               COXWELL AVE / ASHBRIDGES BAY PARK RD  Lake Shore   \n",
       "262                                          CHERRY ST  Lake Shore   \n",
       "263                                          CHERRY ST  Lake Shore   \n",
       "264                                LOWER SHERBOURNE ST  Lake Shore   \n",
       "265                                LOWER SHERBOURNE ST  Lake Shore   \n",
       "266                                    LOWER SIMCOE ST  Lake Shore   \n",
       "267                                        SPADINA AVE  Lake Shore   \n",
       "268                             BATHURST ST / FLEET ST  Lake Shore   \n",
       "269                                     FORT YORK BLVD  Lake Shore   \n",
       "270                                        PARKSIDE DR  Lake Shore   \n",
       "271                                     EGLINTON AVE W       Allen   \n",
       "272                                       ELM RIDGE DR       Allen   \n",
       "273                                      VIEWMOUNT AVE       Allen   \n",
       "274                                      GLENGROVE AVE       Allen   \n",
       "275                                     LAWRENCE AVE W       Allen   \n",
       "276                              401 C E ALLEN RD RAMP       Allen   \n",
       "277                                         TRANSIT RD       Allen   \n",
       "278                                     SHEPPARD AVE W       Allen   \n",
       "\n",
       "                                        Traffic Image   \\\n",
       "0     http://opendata.toronto.ca/transportation/tmc...   \n",
       "1     http://opendata.toronto.ca/transportation/tmc...   \n",
       "2     http://opendata.toronto.ca/transportation/tmc...   \n",
       "3     http://opendata.toronto.ca/transportation/tmc...   \n",
       "4     http://opendata.toronto.ca/transportation/tmc...   \n",
       "5     http://opendata.toronto.ca/transportation/tmc...   \n",
       "6     http://opendata.toronto.ca/transportation/tmc...   \n",
       "7     http://opendata.toronto.ca/transportation/tmc...   \n",
       "8     http://opendata.toronto.ca/transportation/tmc...   \n",
       "9     http://opendata.toronto.ca/transportation/tmc...   \n",
       "10    http://opendata.toronto.ca/transportation/tmc...   \n",
       "11    http://opendata.toronto.ca/transportation/tmc...   \n",
       "12    http://opendata.toronto.ca/transportation/tmc...   \n",
       "13    http://opendata.toronto.ca/transportation/tmc...   \n",
       "14    http://opendata.toronto.ca/transportation/tmc...   \n",
       "15    http://opendata.toronto.ca/transportation/tmc...   \n",
       "16    http://opendata.toronto.ca/transportation/tmc...   \n",
       "17    http://opendata.toronto.ca/transportation/tmc...   \n",
       "18    http://opendata.toronto.ca/transportation/tmc...   \n",
       "19    http://opendata.toronto.ca/transportation/tmc...   \n",
       "20    http://opendata.toronto.ca/transportation/tmc...   \n",
       "21    http://opendata.toronto.ca/transportation/tmc...   \n",
       "22    http://opendata.toronto.ca/transportation/tmc...   \n",
       "23    http://opendata.toronto.ca/transportation/tmc...   \n",
       "24    http://opendata.toronto.ca/transportation/tmc...   \n",
       "25    http://opendata.toronto.ca/transportation/tmc...   \n",
       "26    http://opendata.toronto.ca/transportation/tmc...   \n",
       "27    http://opendata.toronto.ca/transportation/tmc...   \n",
       "28    http://opendata.toronto.ca/transportation/tmc...   \n",
       "29    http://opendata.toronto.ca/transportation/tmc...   \n",
       "..                                                 ...   \n",
       "249   http://opendata.toronto.ca/transportation/tmc...   \n",
       "250   http://opendata.toronto.ca/transportation/tmc...   \n",
       "251   http://opendata.toronto.ca/transportation/tmc...   \n",
       "252   http://opendata.toronto.ca/transportation/tmc...   \n",
       "253   http://opendata.toronto.ca/transportation/tmc...   \n",
       "254   http://opendata.toronto.ca/transportation/tmc...   \n",
       "255   http://opendata.toronto.ca/transportation/tmc...   \n",
       "256   http://opendata.toronto.ca/transportation/tmc...   \n",
       "257   http://opendata.toronto.ca/transportation/tmc...   \n",
       "258   http://opendata.toronto.ca/transportation/tmc...   \n",
       "259   http://opendata.toronto.ca/transportation/tmc...   \n",
       "260   http://opendata.toronto.ca/transportation/tmc...   \n",
       "261   http://opendata.toronto.ca/transportation/tmc...   \n",
       "262   http://opendata.toronto.ca/transportation/tmc...   \n",
       "263   http://opendata.toronto.ca/transportation/tmc...   \n",
       "264   http://opendata.toronto.ca/transportation/tmc...   \n",
       "265   http://opendata.toronto.ca/transportation/tmc...   \n",
       "266   http://opendata.toronto.ca/transportation/tmc...   \n",
       "267   http://opendata.toronto.ca/transportation/tmc...   \n",
       "268   http://opendata.toronto.ca/transportation/tmc...   \n",
       "269   http://opendata.toronto.ca/transportation/tmc...   \n",
       "270   http://opendata.toronto.ca/transportation/tmc...   \n",
       "271   http://opendata.toronto.ca/transportation/tmc...   \n",
       "272   http://opendata.toronto.ca/transportation/tmc...   \n",
       "273   http://opendata.toronto.ca/transportation/tmc...   \n",
       "274   http://opendata.toronto.ca/transportation/tmc...   \n",
       "275   http://opendata.toronto.ca/transportation/tmc...   \n",
       "276   http://opendata.toronto.ca/transportation/tmc...   \n",
       "277   http://opendata.toronto.ca/transportation/tmc...   \n",
       "278   http://opendata.toronto.ca/transportation/tmc...   \n",
       "\n",
       "                         North Reference Static Image   \\\n",
       "0     http://opendata.toronto.ca/transportation/tmc...   \n",
       "1     http://opendata.toronto.ca/transportation/tmc...   \n",
       "2     http://opendata.toronto.ca/transportation/tmc...   \n",
       "3     http://opendata.toronto.ca/transportation/tmc...   \n",
       "4     http://opendata.toronto.ca/transportation/tmc...   \n",
       "5     http://opendata.toronto.ca/transportation/tmc...   \n",
       "6     http://opendata.toronto.ca/transportation/tmc...   \n",
       "7     http://opendata.toronto.ca/transportation/tmc...   \n",
       "8     http://opendata.toronto.ca/transportation/tmc...   \n",
       "9     http://opendata.toronto.ca/transportation/tmc...   \n",
       "10    http://opendata.toronto.ca/transportation/tmc...   \n",
       "11    http://opendata.toronto.ca/transportation/tmc...   \n",
       "12    http://opendata.toronto.ca/transportation/tmc...   \n",
       "13    http://opendata.toronto.ca/transportation/tmc...   \n",
       "14    http://opendata.toronto.ca/transportation/tmc...   \n",
       "15    http://opendata.toronto.ca/transportation/tmc...   \n",
       "16    http://opendata.toronto.ca/transportation/tmc...   \n",
       "17    http://opendata.toronto.ca/transportation/tmc...   \n",
       "18    http://opendata.toronto.ca/transportation/tmc...   \n",
       "19    http://opendata.toronto.ca/transportation/tmc...   \n",
       "20    http://opendata.toronto.ca/transportation/tmc...   \n",
       "21    http://opendata.toronto.ca/transportation/tmc...   \n",
       "22    http://opendata.toronto.ca/transportation/tmc...   \n",
       "23    http://opendata.toronto.ca/transportation/tmc...   \n",
       "24    http://opendata.toronto.ca/transportation/tmc...   \n",
       "25    http://opendata.toronto.ca/transportation/tmc...   \n",
       "26    http://opendata.toronto.ca/transportation/tmc...   \n",
       "27    http://opendata.toronto.ca/transportation/tmc...   \n",
       "28    http://opendata.toronto.ca/transportation/tmc...   \n",
       "29    http://opendata.toronto.ca/transportation/tmc...   \n",
       "..                                                 ...   \n",
       "249   http://opendata.toronto.ca/transportation/tmc...   \n",
       "250   http://opendata.toronto.ca/transportation/tmc...   \n",
       "251   http://opendata.toronto.ca/transportation/tmc...   \n",
       "252   http://opendata.toronto.ca/transportation/tmc...   \n",
       "253                                                      \n",
       "254   http://opendata.toronto.ca/transportation/tmc...   \n",
       "255   http://opendata.toronto.ca/transportation/tmc...   \n",
       "256                                                      \n",
       "257                                                      \n",
       "258                                                      \n",
       "259   http://opendata.toronto.ca/transportation/tmc...   \n",
       "260   http://opendata.toronto.ca/transportation/tmc...   \n",
       "261   http://opendata.toronto.ca/transportation/tmc...   \n",
       "262   http://opendata.toronto.ca/transportation/tmc...   \n",
       "263                                                      \n",
       "264   http://opendata.toronto.ca/transportation/tmc...   \n",
       "265   http://opendata.toronto.ca/transportation/tmc...   \n",
       "266   http://opendata.toronto.ca/transportation/tmc...   \n",
       "267                                                      \n",
       "268   http://opendata.toronto.ca/transportation/tmc...   \n",
       "269   http://opendata.toronto.ca/transportation/tmc...   \n",
       "270                                                      \n",
       "271   http://opendata.toronto.ca/transportation/tmc...   \n",
       "272   http://opendata.toronto.ca/transportation/tmc...   \n",
       "273   http://opendata.toronto.ca/transportation/tmc...   \n",
       "274   http://opendata.toronto.ca/transportation/tmc...   \n",
       "275   http://opendata.toronto.ca/transportation/tmc...   \n",
       "276   http://opendata.toronto.ca/transportation/tmc...   \n",
       "277   http://opendata.toronto.ca/transportation/tmc...   \n",
       "278   http://opendata.toronto.ca/transportation/tmc...   \n",
       "\n",
       "                         South Reference Static Image   \\\n",
       "0     http://opendata.toronto.ca/transportation/tmc...   \n",
       "1     http://opendata.toronto.ca/transportation/tmc...   \n",
       "2     http://opendata.toronto.ca/transportation/tmc...   \n",
       "3     http://opendata.toronto.ca/transportation/tmc...   \n",
       "4     http://opendata.toronto.ca/transportation/tmc...   \n",
       "5     http://opendata.toronto.ca/transportation/tmc...   \n",
       "6     http://opendata.toronto.ca/transportation/tmc...   \n",
       "7     http://opendata.toronto.ca/transportation/tmc...   \n",
       "8     http://opendata.toronto.ca/transportation/tmc...   \n",
       "9     http://opendata.toronto.ca/transportation/tmc...   \n",
       "10    http://opendata.toronto.ca/transportation/tmc...   \n",
       "11    http://opendata.toronto.ca/transportation/tmc...   \n",
       "12    http://opendata.toronto.ca/transportation/tmc...   \n",
       "13    http://opendata.toronto.ca/transportation/tmc...   \n",
       "14    http://opendata.toronto.ca/transportation/tmc...   \n",
       "15    http://opendata.toronto.ca/transportation/tmc...   \n",
       "16    http://opendata.toronto.ca/transportation/tmc...   \n",
       "17    http://opendata.toronto.ca/transportation/tmc...   \n",
       "18    http://opendata.toronto.ca/transportation/tmc...   \n",
       "19    http://opendata.toronto.ca/transportation/tmc...   \n",
       "20    http://opendata.toronto.ca/transportation/tmc...   \n",
       "21    http://opendata.toronto.ca/transportation/tmc...   \n",
       "22    http://opendata.toronto.ca/transportation/tmc...   \n",
       "23    http://opendata.toronto.ca/transportation/tmc...   \n",
       "24    http://opendata.toronto.ca/transportation/tmc...   \n",
       "25    http://opendata.toronto.ca/transportation/tmc...   \n",
       "26    http://opendata.toronto.ca/transportation/tmc...   \n",
       "27    http://opendata.toronto.ca/transportation/tmc...   \n",
       "28    http://opendata.toronto.ca/transportation/tmc...   \n",
       "29    http://opendata.toronto.ca/transportation/tmc...   \n",
       "..                                                 ...   \n",
       "249   http://opendata.toronto.ca/transportation/tmc...   \n",
       "250                                                      \n",
       "251   http://opendata.toronto.ca/transportation/tmc...   \n",
       "252   http://opendata.toronto.ca/transportation/tmc...   \n",
       "253                                                      \n",
       "254                                                      \n",
       "255   http://opendata.toronto.ca/transportation/tmc...   \n",
       "256                                                      \n",
       "257                                                      \n",
       "258   http://opendata.toronto.ca/transportation/tmc...   \n",
       "259   http://opendata.toronto.ca/transportation/tmc...   \n",
       "260   http://opendata.toronto.ca/transportation/tmc...   \n",
       "261   http://opendata.toronto.ca/transportation/tmc...   \n",
       "262   http://opendata.toronto.ca/transportation/tmc...   \n",
       "263   http://opendata.toronto.ca/transportation/tmc...   \n",
       "264   http://opendata.toronto.ca/transportation/tmc...   \n",
       "265   http://opendata.toronto.ca/transportation/tmc...   \n",
       "266   http://opendata.toronto.ca/transportation/tmc...   \n",
       "267                                                      \n",
       "268   http://opendata.toronto.ca/transportation/tmc...   \n",
       "269                                                      \n",
       "270                                                      \n",
       "271                                                      \n",
       "272   http://opendata.toronto.ca/transportation/tmc...   \n",
       "273   http://opendata.toronto.ca/transportation/tmc...   \n",
       "274   http://opendata.toronto.ca/transportation/tmc...   \n",
       "275   http://opendata.toronto.ca/transportation/tmc...   \n",
       "276   http://opendata.toronto.ca/transportation/tmc...   \n",
       "277   http://opendata.toronto.ca/transportation/tmc...   \n",
       "278   http://opendata.toronto.ca/transportation/tmc...   \n",
       "\n",
       "                          East Reference Static Image   \\\n",
       "0     http://opendata.toronto.ca/transportation/tmc...   \n",
       "1     http://opendata.toronto.ca/transportation/tmc...   \n",
       "2     http://opendata.toronto.ca/transportation/tmc...   \n",
       "3     http://opendata.toronto.ca/transportation/tmc...   \n",
       "4     http://opendata.toronto.ca/transportation/tmc...   \n",
       "5     http://opendata.toronto.ca/transportation/tmc...   \n",
       "6     http://opendata.toronto.ca/transportation/tmc...   \n",
       "7     http://opendata.toronto.ca/transportation/tmc...   \n",
       "8     http://opendata.toronto.ca/transportation/tmc...   \n",
       "9     http://opendata.toronto.ca/transportation/tmc...   \n",
       "10    http://opendata.toronto.ca/transportation/tmc...   \n",
       "11    http://opendata.toronto.ca/transportation/tmc...   \n",
       "12    http://opendata.toronto.ca/transportation/tmc...   \n",
       "13    http://opendata.toronto.ca/transportation/tmc...   \n",
       "14    http://opendata.toronto.ca/transportation/tmc...   \n",
       "15    http://opendata.toronto.ca/transportation/tmc...   \n",
       "16    http://opendata.toronto.ca/transportation/tmc...   \n",
       "17    http://opendata.toronto.ca/transportation/tmc...   \n",
       "18    http://opendata.toronto.ca/transportation/tmc...   \n",
       "19    http://opendata.toronto.ca/transportation/tmc...   \n",
       "20    http://opendata.toronto.ca/transportation/tmc...   \n",
       "21    http://opendata.toronto.ca/transportation/tmc...   \n",
       "22    http://opendata.toronto.ca/transportation/tmc...   \n",
       "23    http://opendata.toronto.ca/transportation/tmc...   \n",
       "24    http://opendata.toronto.ca/transportation/tmc...   \n",
       "25    http://opendata.toronto.ca/transportation/tmc...   \n",
       "26    http://opendata.toronto.ca/transportation/tmc...   \n",
       "27    http://opendata.toronto.ca/transportation/tmc...   \n",
       "28    http://opendata.toronto.ca/transportation/tmc...   \n",
       "29    http://opendata.toronto.ca/transportation/tmc...   \n",
       "..                                                 ...   \n",
       "249   http://opendata.toronto.ca/transportation/tmc...   \n",
       "250   http://opendata.toronto.ca/transportation/tmc...   \n",
       "251   http://opendata.toronto.ca/transportation/tmc...   \n",
       "252   http://opendata.toronto.ca/transportation/tmc...   \n",
       "253   http://opendata.toronto.ca/transportation/tmc...   \n",
       "254   http://opendata.toronto.ca/transportation/tmc...   \n",
       "255   http://opendata.toronto.ca/transportation/tmc...   \n",
       "256   http://opendata.toronto.ca/transportation/tmc...   \n",
       "257                                                      \n",
       "258   http://opendata.toronto.ca/transportation/tmc...   \n",
       "259   http://opendata.toronto.ca/transportation/tmc...   \n",
       "260   http://opendata.toronto.ca/transportation/tmc...   \n",
       "261   http://opendata.toronto.ca/transportation/tmc...   \n",
       "262   http://opendata.toronto.ca/transportation/tmc...   \n",
       "263   http://opendata.toronto.ca/transportation/tmc...   \n",
       "264   http://opendata.toronto.ca/transportation/tmc...   \n",
       "265   http://opendata.toronto.ca/transportation/tmc...   \n",
       "266   http://opendata.toronto.ca/transportation/tmc...   \n",
       "267   http://opendata.toronto.ca/transportation/tmc...   \n",
       "268   http://opendata.toronto.ca/transportation/tmc...   \n",
       "269   http://opendata.toronto.ca/transportation/tmc...   \n",
       "270                                                      \n",
       "271   http://opendata.toronto.ca/transportation/tmc...   \n",
       "272   http://opendata.toronto.ca/transportation/tmc...   \n",
       "273   http://opendata.toronto.ca/transportation/tmc...   \n",
       "274   http://opendata.toronto.ca/transportation/tmc...   \n",
       "275   http://opendata.toronto.ca/transportation/tmc...   \n",
       "276                                                      \n",
       "277                                                      \n",
       "278   http://opendata.toronto.ca/transportation/tmc...   \n",
       "\n",
       "                           West Reference Static Image  \n",
       "0     http://opendata.toronto.ca/transportation/tmc...  \n",
       "1     http://opendata.toronto.ca/transportation/tmc...  \n",
       "2     http://opendata.toronto.ca/transportation/tmc...  \n",
       "3     http://opendata.toronto.ca/transportation/tmc...  \n",
       "4     http://opendata.toronto.ca/transportation/tmc...  \n",
       "5     http://opendata.toronto.ca/transportation/tmc...  \n",
       "6     http://opendata.toronto.ca/transportation/tmc...  \n",
       "7                                                  NaN  \n",
       "8     http://opendata.toronto.ca/transportation/tmc...  \n",
       "9     http://opendata.toronto.ca/transportation/tmc...  \n",
       "10    http://opendata.toronto.ca/transportation/tmc...  \n",
       "11    http://opendata.toronto.ca/transportation/tmc...  \n",
       "12    http://opendata.toronto.ca/transportation/tmc...  \n",
       "13    http://opendata.toronto.ca/transportation/tmc...  \n",
       "14    http://opendata.toronto.ca/transportation/tmc...  \n",
       "15    http://opendata.toronto.ca/transportation/tmc...  \n",
       "16    http://opendata.toronto.ca/transportation/tmc...  \n",
       "17    http://opendata.toronto.ca/transportation/tmc...  \n",
       "18    http://opendata.toronto.ca/transportation/tmc...  \n",
       "19    http://opendata.toronto.ca/transportation/tmc...  \n",
       "20    http://opendata.toronto.ca/transportation/tmc...  \n",
       "21    http://opendata.toronto.ca/transportation/tmc...  \n",
       "22    http://opendata.toronto.ca/transportation/tmc...  \n",
       "23    http://opendata.toronto.ca/transportation/tmc...  \n",
       "24    http://opendata.toronto.ca/transportation/tmc...  \n",
       "25    http://opendata.toronto.ca/transportation/tmc...  \n",
       "26    http://opendata.toronto.ca/transportation/tmc...  \n",
       "27    http://opendata.toronto.ca/transportation/tmc...  \n",
       "28    http://opendata.toronto.ca/transportation/tmc...  \n",
       "29    http://opendata.toronto.ca/transportation/tmc...  \n",
       "..                                                 ...  \n",
       "249   http://opendata.toronto.ca/transportation/tmc...  \n",
       "250   http://opendata.toronto.ca/transportation/tmc...  \n",
       "251   http://opendata.toronto.ca/transportation/tmc...  \n",
       "252   http://opendata.toronto.ca/transportation/tmc...  \n",
       "253   http://opendata.toronto.ca/transportation/tmc...  \n",
       "254   http://opendata.toronto.ca/transportation/tmc...  \n",
       "255   http://opendata.toronto.ca/transportation/tmc...  \n",
       "256                                                NaN  \n",
       "257   http://opendata.toronto.ca/transportation/tmc...  \n",
       "258   http://opendata.toronto.ca/transportation/tmc...  \n",
       "259   http://opendata.toronto.ca/transportation/tmc...  \n",
       "260   http://opendata.toronto.ca/transportation/tmc...  \n",
       "261   http://opendata.toronto.ca/transportation/tmc...  \n",
       "262   http://opendata.toronto.ca/transportation/tmc...  \n",
       "263   http://opendata.toronto.ca/transportation/tmc...  \n",
       "264   http://opendata.toronto.ca/transportation/tmc...  \n",
       "265   http://opendata.toronto.ca/transportation/tmc...  \n",
       "266   http://opendata.toronto.ca/transportation/tmc...  \n",
       "267   http://opendata.toronto.ca/transportation/tmc...  \n",
       "268   http://opendata.toronto.ca/transportation/tmc...  \n",
       "269   http://opendata.toronto.ca/transportation/tmc...  \n",
       "270                                                NaN  \n",
       "271   http://opendata.toronto.ca/transportation/tmc...  \n",
       "272   http://opendata.toronto.ca/transportation/tmc...  \n",
       "273   http://opendata.toronto.ca/transportation/tmc...  \n",
       "274   http://opendata.toronto.ca/transportation/tmc...  \n",
       "275   http://opendata.toronto.ca/transportation/tmc...  \n",
       "276                                                NaN  \n",
       "277                                                NaN  \n",
       "278   http://opendata.toronto.ca/transportation/tmc...  \n",
       "\n",
       "[279 rows x 11 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Toronto Open Data Traffic Camera Source\n",
    "source_csv = r\"http://opendata.toronto.ca/transportation/tmc/rescucameraimages/Data/tmcearthcameras.csv\"\n",
    "df = pd.read_csv(source_csv)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "ename": "URLError",
     "evalue": "<urlopen error [WinError 10060] A connection attempt failed because the connected party did not properly respond after a period of time, or established connection failed because connected host has failed to respond>",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mTimeoutError\u001b[0m                              Traceback (most recent call last)",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\urllib\\request.py\u001b[0m in \u001b[0;36mdo_open\u001b[1;34m(self, http_class, req, **http_conn_args)\u001b[0m\n\u001b[0;32m   1317\u001b[0m                 h.request(req.get_method(), req.selector, req.data, headers,\n\u001b[1;32m-> 1318\u001b[1;33m                           encode_chunked=req.has_header('Transfer-encoding'))\n\u001b[0m\u001b[0;32m   1319\u001b[0m             \u001b[1;32mexcept\u001b[0m \u001b[0mOSError\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;31m# timeout error\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\http\\client.py\u001b[0m in \u001b[0;36mrequest\u001b[1;34m(self, method, url, body, headers, encode_chunked)\u001b[0m\n\u001b[0;32m   1238\u001b[0m         \u001b[1;34m\"\"\"Send a complete request to the server.\"\"\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1239\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_send_request\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmethod\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0murl\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mbody\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mheaders\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mencode_chunked\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1240\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\http\\client.py\u001b[0m in \u001b[0;36m_send_request\u001b[1;34m(self, method, url, body, headers, encode_chunked)\u001b[0m\n\u001b[0;32m   1284\u001b[0m             \u001b[0mbody\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0m_encode\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mbody\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'body'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1285\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mendheaders\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mbody\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mencode_chunked\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mencode_chunked\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1286\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\http\\client.py\u001b[0m in \u001b[0;36mendheaders\u001b[1;34m(self, message_body, encode_chunked)\u001b[0m\n\u001b[0;32m   1233\u001b[0m             \u001b[1;32mraise\u001b[0m \u001b[0mCannotSendHeader\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1234\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_send_output\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmessage_body\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mencode_chunked\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mencode_chunked\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1235\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\http\\client.py\u001b[0m in \u001b[0;36m_send_output\u001b[1;34m(self, message_body, encode_chunked)\u001b[0m\n\u001b[0;32m   1025\u001b[0m         \u001b[1;32mdel\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_buffer\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1026\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmsg\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1027\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\http\\client.py\u001b[0m in \u001b[0;36msend\u001b[1;34m(self, data)\u001b[0m\n\u001b[0;32m    963\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mauto_open\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 964\u001b[1;33m                 \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mconnect\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    965\u001b[0m             \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\http\\client.py\u001b[0m in \u001b[0;36mconnect\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    935\u001b[0m         self.sock = self._create_connection(\n\u001b[1;32m--> 936\u001b[1;33m             (self.host,self.port), self.timeout, self.source_address)\n\u001b[0m\u001b[0;32m    937\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msock\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msetsockopt\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msocket\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mIPPROTO_TCP\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msocket\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mTCP_NODELAY\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\socket.py\u001b[0m in \u001b[0;36mcreate_connection\u001b[1;34m(address, timeout, source_address)\u001b[0m\n\u001b[0;32m    721\u001b[0m     \u001b[1;32mif\u001b[0m \u001b[0merr\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 722\u001b[1;33m         \u001b[1;32mraise\u001b[0m \u001b[0merr\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    723\u001b[0m     \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\socket.py\u001b[0m in \u001b[0;36mcreate_connection\u001b[1;34m(address, timeout, source_address)\u001b[0m\n\u001b[0;32m    712\u001b[0m                 \u001b[0msock\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mbind\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msource_address\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 713\u001b[1;33m             \u001b[0msock\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mconnect\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msa\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    714\u001b[0m             \u001b[1;32mreturn\u001b[0m \u001b[0msock\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mTimeoutError\u001b[0m: [WinError 10060] A connection attempt failed because the connected party did not properly respond after a period of time, or established connection failed because connected host has failed to respond",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[1;31mURLError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-11-922d102e7021>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;31m# TrafficLand API source JSON\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[0msource_json\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34mr\"http://api.trafficland.com/v1.5/json/video_feeds?system=ddot&key=1594c8892d7fbd18181a8a6a44958b28\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0mdf\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread_json\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msource_json\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      4\u001b[0m \u001b[0mddot_df\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mdf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mdf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mprovider\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;34m'DDOT'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;31m# Edit the ddot_df to make a feature service using the API\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\pandas\\io\\json\\json.py\u001b[0m in \u001b[0;36mread_json\u001b[1;34m(path_or_buf, orient, typ, dtype, convert_axes, convert_dates, keep_default_dates, numpy, precise_float, date_unit, encoding, lines)\u001b[0m\n\u001b[0;32m    320\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    321\u001b[0m     filepath_or_buffer, _, _ = get_filepath_or_buffer(path_or_buf,\n\u001b[1;32m--> 322\u001b[1;33m                                                       encoding=encoding)\n\u001b[0m\u001b[0;32m    323\u001b[0m     \u001b[1;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcompat\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstring_types\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    324\u001b[0m         \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\pandas\\io\\common.py\u001b[0m in \u001b[0;36mget_filepath_or_buffer\u001b[1;34m(filepath_or_buffer, encoding, compression)\u001b[0m\n\u001b[0;32m    184\u001b[0m     \u001b[1;32mif\u001b[0m \u001b[0m_is_url\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    185\u001b[0m         \u001b[0murl\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mstr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 186\u001b[1;33m         \u001b[0mreq\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0m_urlopen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0murl\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    187\u001b[0m         \u001b[0mcontent_encoding\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mreq\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mheaders\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'Content-Encoding'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    188\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mcontent_encoding\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;34m'gzip'\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\urllib\\request.py\u001b[0m in \u001b[0;36murlopen\u001b[1;34m(url, data, timeout, cafile, capath, cadefault, context)\u001b[0m\n\u001b[0;32m    221\u001b[0m     \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    222\u001b[0m         \u001b[0mopener\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0m_opener\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 223\u001b[1;33m     \u001b[1;32mreturn\u001b[0m \u001b[0mopener\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mopen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0murl\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtimeout\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    224\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    225\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0minstall_opener\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mopener\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\urllib\\request.py\u001b[0m in \u001b[0;36mopen\u001b[1;34m(self, fullurl, data, timeout)\u001b[0m\n\u001b[0;32m    524\u001b[0m             \u001b[0mreq\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mmeth\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mreq\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    525\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 526\u001b[1;33m         \u001b[0mresponse\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_open\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mreq\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    527\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    528\u001b[0m         \u001b[1;31m# post-process response\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\urllib\\request.py\u001b[0m in \u001b[0;36m_open\u001b[1;34m(self, req, data)\u001b[0m\n\u001b[0;32m    542\u001b[0m         \u001b[0mprotocol\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mreq\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtype\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    543\u001b[0m         result = self._call_chain(self.handle_open, protocol, protocol +\n\u001b[1;32m--> 544\u001b[1;33m                                   '_open', req)\n\u001b[0m\u001b[0;32m    545\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mresult\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    546\u001b[0m             \u001b[1;32mreturn\u001b[0m \u001b[0mresult\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\urllib\\request.py\u001b[0m in \u001b[0;36m_call_chain\u001b[1;34m(self, chain, kind, meth_name, *args)\u001b[0m\n\u001b[0;32m    502\u001b[0m         \u001b[1;32mfor\u001b[0m \u001b[0mhandler\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mhandlers\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    503\u001b[0m             \u001b[0mfunc\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mhandler\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmeth_name\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 504\u001b[1;33m             \u001b[0mresult\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mfunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    505\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mresult\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    506\u001b[0m                 \u001b[1;32mreturn\u001b[0m \u001b[0mresult\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\urllib\\request.py\u001b[0m in \u001b[0;36mhttp_open\u001b[1;34m(self, req)\u001b[0m\n\u001b[0;32m   1344\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1345\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mhttp_open\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mreq\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1346\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdo_open\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mhttp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mclient\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mHTTPConnection\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mreq\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1347\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1348\u001b[0m     \u001b[0mhttp_request\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mAbstractHTTPHandler\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdo_request_\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\urllib\\request.py\u001b[0m in \u001b[0;36mdo_open\u001b[1;34m(self, http_class, req, **http_conn_args)\u001b[0m\n\u001b[0;32m   1318\u001b[0m                           encode_chunked=req.has_header('Transfer-encoding'))\n\u001b[0;32m   1319\u001b[0m             \u001b[1;32mexcept\u001b[0m \u001b[0mOSError\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;31m# timeout error\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1320\u001b[1;33m                 \u001b[1;32mraise\u001b[0m \u001b[0mURLError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0merr\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1321\u001b[0m             \u001b[0mr\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mh\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mgetresponse\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1322\u001b[0m         \u001b[1;32mexcept\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mURLError\u001b[0m: <urlopen error [WinError 10060] A connection attempt failed because the connected party did not properly respond after a period of time, or established connection failed because connected host has failed to respond>"
     ]
    }
   ],
   "source": [
    "# TrafficLand API source JSON\n",
    "source_json = r\"http://api.trafficland.com/v1.5/json/video_feeds?system=ddot&key=1594c8892d7fbd18181a8a6a44958b28\"\n",
    "df = pd.read_json(source_json)\n",
    "ddot_df = df.loc[df.provider == 'DDOT']\n",
    "# Edit the ddot_df to make a feature service using the API\n",
    "ddot_df['latitude'] = ddot_df.apply(lambda row: return_lat(row), axis=1)\n",
    "ddot_df['longitude'] = ddot_df.apply(lambda row: return_lon(row), axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Multiple Camera Iteration Prototyping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Size, in inches, of the output images.\n",
    "IMAGE_SIZE = (12, 8)\n",
    "jpeg_size = \"halfJpeg\" # Other Options: halfJpeg; fullJpeg; hugeJpeg"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## P1: Use existing feature service and send model outputs as updates"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "OPS Service"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "                       <a href='https://esrifederal.maps.arcgis.com/home/item.html?id=cbe1f0e312994a21ae16ad8f841caf8d' target='_blank'>\n",
       "                        <img 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' width='200' height='133' class=\"itemThumbnail\">\n",
       "                       </a>\n",
       "                    </div>\n",
       "\n",
       "                    <div class=\"item_right\"     style=\"float: none; width: auto; overflow: hidden;\">\n",
       "                        <a href='https://esrifederal.maps.arcgis.com/home/item.html?id=cbe1f0e312994a21ae16ad8f841caf8d' target='_blank'><b>DDOT Traffic Cameras (Firefly)</b>\n",
       "                        </a>\n",
       "                        <br/><img src='https://esrifederal.maps.arcgis.com/home/js/jsapi/esri/css/images/item_type_icons/featureshosted16.png' style=\"vertical-align:middle;\">Feature Layer Collection by albe9057@esri.com_esrifederal\n",
       "                        <br/>Last Modified: March 02, 2018\n",
       "                        <br/>0 comments, 0 views\n",
       "                    </div>\n",
       "                </div>\n",
       "                "
      ],
      "text/plain": [
       "<Item title:\"DDOT Traffic Cameras (Firefly)\" type:Feature Layer Collection owner:albe9057@esri.com_esrifederal>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "object_point_srvc = gis.content.search(\"DDOT Traffic Cameras\", item_type=\"feature service\")[1]\n",
    "object_point_srvc"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "DEV Service"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div class=\"item_container\" style=\"height: auto; overflow: hidden; border: 1px solid #cfcfcf; border-radius: 2px; background: #f6fafa; line-height: 1.21429em; padding: 10px;\">\n",
       "                    <div class=\"item_left\" style=\"width: 210px; float: left;\">\n",
       "                       <a href='https://esrifederal.maps.arcgis.com/home/item.html?id=b07c936bd07a4e9ba05ee63cc726ecb5' target='_blank'>\n",
       "                        <img src='data:image/png;base64,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' width='200' height='133' class=\"itemThumbnail\">\n",
       "                       </a>\n",
       "                    </div>\n",
       "\n",
       "                    <div class=\"item_right\"     style=\"float: none; width: auto; overflow: hidden;\">\n",
       "                        <a href='https://esrifederal.maps.arcgis.com/home/item.html?id=b07c936bd07a4e9ba05ee63cc726ecb5' target='_blank'><b>DDOT_TrafficCameras_CityNetwork</b>\n",
       "                        </a>\n",
       "                        <br/><img src='https://esrifederal.maps.arcgis.com/home/js/jsapi/esri/css/images/item_type_icons/featureshosted16.png' style=\"vertical-align:middle;\">Feature Layer Collection by albe9057@esri.com_esrifederal\n",
       "                        <br/>Last Modified: March 03, 2018\n",
       "                        <br/>0 comments, 8 views\n",
       "                    </div>\n",
       "                </div>\n",
       "                "
      ],
      "text/plain": [
       "<Item title:\"DDOT_TrafficCameras_CityNetwork\" type:Feature Layer Collection owner:albe9057@esri.com_esrifederal>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "object_point_srvc = gis.content.search(\"DDOT_TrafficCameras_CityNetwork\", item_type=\"feature service\")[0]\n",
    "object_point_srvc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Convert our existing service into a pandas dataframe\n",
    "object_point_lyr = object_point_srvc.layers[0]\n",
    "obj_fset = object_point_lyr.query()  #querying without any conditions returns all the features\n",
    "obj_df = obj_fset.df\n",
    "all_features = obj_fset.features\n",
    "original_feature = all_features[1]\n",
    "feature_to_be_updated = deepcopy(original_feature)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Reset Routine"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "https://esrifederal.maps.arcgis.com/home/webmap/viewer.html?webmap=255196da558749209dc63c07ffb38ae6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Restting values for camera 1 of 100...\n",
      "Restting values for camera 2 of 100...\n",
      "Restting values for camera 3 of 100...\n",
      "Restting values for camera 4 of 100...\n",
      "Restting values for camera 5 of 100...\n",
      "Restting values for camera 6 of 100...\n",
      "Restting values for camera 7 of 100...\n",
      "Restting values for camera 8 of 100...\n",
      "Restting values for camera 9 of 100...\n",
      "Restting values for camera 10 of 100...\n",
      "Restting values for camera 11 of 100...\n",
      "Restting values for camera 12 of 100...\n",
      "Restting values for camera 13 of 100...\n",
      "Restting values for camera 14 of 100...\n",
      "Restting values for camera 15 of 100...\n",
      "Restting values for camera 16 of 100...\n",
      "Restting values for camera 17 of 100...\n",
      "Restting values for camera 18 of 100...\n",
      "Restting values for camera 19 of 100...\n",
      "Restting values for camera 20 of 100...\n",
      "Restting values for camera 21 of 100...\n",
      "Restting values for camera 22 of 100...\n",
      "Restting values for camera 23 of 100...\n",
      "Restting values for camera 24 of 100...\n",
      "Restting values for camera 25 of 100...\n",
      "Restting values for camera 26 of 100...\n",
      "Restting values for camera 27 of 100...\n",
      "Restting values for camera 28 of 100...\n",
      "Restting values for camera 29 of 100...\n",
      "Restting values for camera 30 of 100...\n",
      "Restting values for camera 31 of 100...\n",
      "Restting values for camera 32 of 100...\n",
      "Restting values for camera 33 of 100...\n",
      "Restting values for camera 34 of 100...\n",
      "Restting values for camera 35 of 100...\n",
      "Restting values for camera 36 of 100...\n",
      "Restting values for camera 37 of 100...\n",
      "Restting values for camera 38 of 100...\n",
      "Restting values for camera 39 of 100...\n",
      "Restting values for camera 40 of 100...\n",
      "Restting values for camera 41 of 100...\n",
      "Restting values for camera 42 of 100...\n",
      "Restting values for camera 43 of 100...\n",
      "Restting values for camera 44 of 100...\n",
      "Restting values for camera 45 of 100...\n",
      "Restting values for camera 46 of 100...\n",
      "Restting values for camera 47 of 100...\n",
      "Restting values for camera 48 of 100...\n",
      "Restting values for camera 49 of 100...\n",
      "Restting values for camera 50 of 100...\n",
      "Restting values for camera 51 of 100...\n",
      "Restting values for camera 52 of 100...\n",
      "Restting values for camera 53 of 100...\n",
      "Restting values for camera 54 of 100...\n",
      "Restting values for camera 55 of 100...\n",
      "Restting values for camera 56 of 100...\n",
      "Restting values for camera 57 of 100...\n",
      "Restting values for camera 58 of 100...\n",
      "Restting values for camera 59 of 100...\n",
      "Restting values for camera 60 of 100...\n",
      "Restting values for camera 61 of 100...\n",
      "Restting values for camera 62 of 100...\n",
      "Restting values for camera 63 of 100...\n",
      "Restting values for camera 64 of 100...\n",
      "Restting values for camera 65 of 100...\n",
      "Restting values for camera 66 of 100...\n",
      "Restting values for camera 67 of 100...\n",
      "Restting values for camera 68 of 100...\n",
      "Restting values for camera 69 of 100...\n",
      "Restting values for camera 70 of 100...\n",
      "Restting values for camera 71 of 100...\n",
      "Restting values for camera 72 of 100...\n",
      "Restting values for camera 73 of 100...\n",
      "Restting values for camera 74 of 100...\n",
      "Restting values for camera 75 of 100...\n",
      "Restting values for camera 76 of 100...\n",
      "Restting values for camera 77 of 100...\n",
      "Restting values for camera 78 of 100...\n",
      "Restting values for camera 79 of 100...\n",
      "Restting values for camera 80 of 100...\n",
      "Restting values for camera 81 of 100...\n",
      "Restting values for camera 82 of 100...\n",
      "Restting values for camera 83 of 100...\n",
      "Restting values for camera 84 of 100...\n",
      "Restting values for camera 85 of 100...\n",
      "Restting values for camera 86 of 100...\n",
      "Restting values for camera 87 of 100...\n",
      "Restting values for camera 88 of 100...\n",
      "Restting values for camera 89 of 100...\n",
      "Restting values for camera 90 of 100...\n",
      "Restting values for camera 91 of 100...\n",
      "Restting values for camera 92 of 100...\n",
      "Restting values for camera 93 of 100...\n",
      "Restting values for camera 94 of 100...\n",
      "Restting values for camera 95 of 100...\n",
      "Restting values for camera 96 of 100...\n",
      "Restting values for camera 97 of 100...\n",
      "Restting values for camera 98 of 100...\n",
      "Restting values for camera 99 of 100...\n"
     ]
    }
   ],
   "source": [
    "for iteration in range(1):\n",
    "    \n",
    "    features_for_update = []\n",
    "            \n",
    "    for ix in range(1,100):\n",
    "        print(\"Restting values for camera {0} of 100...\".format(str(ix)))\n",
    "\n",
    "        # Retrieve camera information\n",
    "        camera_name = ddot_df.iloc[ix]['name']\n",
    "\n",
    "        # Retrieve the feature from the feature layer to update\n",
    "        obj_fset = object_point_lyr.query(where=\"\"\"name = '\"\"\"+camera_name+\"\"\"'\"\"\", return_geometry=False)  \n",
    "        all_features = obj_fset.features\n",
    "        original_feature = all_features[0]\n",
    "        feature_to_be_updated = deepcopy(original_feature)\n",
    "\n",
    "        \n",
    "        feature_to_be_updated.attributes['rt_object_count'] = 0\n",
    "        feature_to_be_updated.attributes['rt_vehicle_count'] = 0\n",
    "        feature_to_be_updated.attributes['rt_car_count'] = 0\n",
    "        feature_to_be_updated.attributes['rt_bus_count'] = 0\n",
    "        feature_to_be_updated.attributes['rt_truck_count'] = 0\n",
    "        feature_to_be_updated.attributes['rt_motorcycle_count'] = 0\n",
    "        feature_to_be_updated.attributes['rt_pedestrian_count'] = 0\n",
    "        feature_to_be_updated.attributes['rt_bicycle_count'] = 0\n",
    "\n",
    "        features_for_update.append(feature_to_be_updated)\n",
    "        \n",
    "    object_point_lyr.edit_features(updates=features_for_update)   "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Model Update with Attachments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Processing camera 1 of 100...\n",
      "Processing camera 2 of 100...\n",
      "Processing camera 3 of 100...\n",
      "Processing camera 4 of 100...\n",
      "Processing camera 5 of 100...\n",
      "Processing camera 6 of 100...\n",
      "Processing camera 7 of 100...\n",
      "Processing camera 8 of 100...\n",
      "Processing camera 9 of 100...\n",
      "Processing camera 10 of 100...\n",
      "Processing camera 11 of 100...\n",
      "Processing camera 12 of 100...\n",
      "Processing camera 13 of 100...\n",
      "Processing camera 14 of 100...\n",
      "Processing camera 15 of 100...\n",
      "Processing camera 16 of 100...\n",
      "Processing camera 17 of 100...\n",
      "Processing camera 18 of 100...\n",
      "Processing camera 19 of 100...\n",
      "Processing camera 20 of 100...\n",
      "Processing camera 21 of 100...\n",
      "Processing camera 22 of 100...\n",
      "Processing camera 23 of 100...\n",
      "Processing camera 24 of 100...\n",
      "Processing camera 25 of 100...\n",
      "Processing camera 26 of 100...\n",
      "Processing camera 27 of 100...\n",
      "Processing camera 28 of 100...\n",
      "Processing camera 29 of 100...\n",
      "Processing camera 30 of 100...\n",
      "Processing camera 31 of 100...\n",
      "Processing camera 32 of 100...\n",
      "Processing camera 33 of 100...\n",
      "Processing camera 34 of 100...\n",
      "Processing camera 35 of 100...\n",
      "Processing camera 36 of 100...\n",
      "Processing camera 37 of 100...\n",
      "Processing camera 38 of 100...\n",
      "Processing camera 39 of 100...\n",
      "Processing camera 40 of 100...\n",
      "Processing camera 41 of 100...\n",
      "Processing camera 42 of 100...\n",
      "Processing camera 43 of 100...\n",
      "Processing camera 44 of 100...\n",
      "Processing camera 45 of 100...\n",
      "Processing camera 46 of 100...\n",
      "Processing camera 47 of 100...\n",
      "Processing camera 48 of 100...\n",
      "Processing camera 49 of 100...\n",
      "Processing camera 50 of 100...\n",
      "Processing camera 51 of 100...\n",
      "Processing camera 52 of 100...\n",
      "Processing camera 53 of 100...\n",
      "Processing camera 54 of 100...\n",
      "Processing camera 55 of 100...\n",
      "Processing camera 56 of 100...\n",
      "Processing camera 57 of 100...\n",
      "Processing camera 58 of 100...\n",
      "Processing camera 59 of 100...\n",
      "Processing camera 60 of 100...\n",
      "Processing camera 61 of 100...\n",
      "Processing camera 62 of 100...\n",
      "Processing camera 63 of 100...\n",
      "Processing camera 64 of 100...\n",
      "Processing camera 65 of 100...\n",
      "Processing camera 66 of 100...\n",
      "Processing camera 67 of 100...\n",
      "Processing camera 68 of 100...\n",
      "Processing camera 69 of 100...\n",
      "Processing camera 70 of 100...\n",
      "Processing camera 71 of 100...\n",
      "Processing camera 72 of 100...\n",
      "Processing camera 73 of 100...\n",
      "Processing camera 74 of 100...\n",
      "Processing camera 75 of 100...\n",
      "Processing camera 76 of 100...\n",
      "Processing camera 77 of 100...\n",
      "Processing camera 78 of 100...\n",
      "Processing camera 79 of 100...\n",
      "Processing camera 80 of 100...\n",
      "Processing camera 81 of 100...\n",
      "Processing camera 82 of 100...\n",
      "Processing camera 83 of 100...\n",
      "Processing camera 84 of 100...\n",
      "Processing camera 85 of 100...\n",
      "Processing camera 86 of 100...\n",
      "Processing camera 87 of 100...\n",
      "Processing camera 88 of 100...\n",
      "Processing camera 89 of 100...\n",
      "Processing camera 90 of 100...\n",
      "Processing camera 91 of 100...\n",
      "Processing camera 92 of 100...\n",
      "Processing camera 93 of 100...\n",
      "Processing camera 94 of 100...\n",
      "Processing camera 95 of 100...\n",
      "Processing camera 96 of 100...\n",
      "Processing camera 97 of 100...\n",
      "Processing camera 98 of 100...\n",
      "Processing camera 99 of 100...\n"
     ]
    }
   ],
   "source": [
    "overwrite_attachment = True\n",
    "\n",
    "with detection_graph.as_default():\n",
    "    \n",
    "    with tf.Session(graph=detection_graph) as sess:\n",
    "        \n",
    "        image_tensor = detection_graph.get_tensor_by_name('image_tensor:0')\n",
    "        detection_boxes = detection_graph.get_tensor_by_name('detection_boxes:0')\n",
    "        detection_scores = detection_graph.get_tensor_by_name('detection_scores:0')\n",
    "        detection_classes = detection_graph.get_tensor_by_name('detection_classes:0')\n",
    "        num_detections = detection_graph.get_tensor_by_name('num_detections:0')\n",
    "\n",
    "        for iteration in range(1):\n",
    "            # TrafficLand API source JSON\n",
    "            source_json = r\"http://api.trafficland.com/v1.5/json/video_feeds?system=ddot&key=1594c8892d7fbd18181a8a6a44958b28\"\n",
    "            df = pd.read_json(source_json)\n",
    "            ddot_df = df.loc[df.provider == 'DDOT']\n",
    "            \n",
    "            for ix in range(1,100):\n",
    "                print(\"Processing camera {0} of 100...\".format(str(ix)))\n",
    "\n",
    "                # Retrieve camera information\n",
    "                camera_jpeg_url = ddot_df.iloc[ix]['content']['hugeJpeg']\n",
    "                camera_name = ddot_df.iloc[ix]['name']\n",
    "                camera_id = ddot_df.iloc[ix]['publicId']\n",
    "                \n",
    "\n",
    "                # Retrieve the camera image\n",
    "                camera_response = requests.get(camera_jpeg_url)\n",
    "                \n",
    "#                 # Perform attachment of source image\n",
    "                streamed_response = requests.get(camera_jpeg_url, stream=True)\n",
    "                with open('source.jpg', 'wb') as out_file:\n",
    "                    shutil.copyfileobj(streamed_response.raw, out_file)\n",
    "#                 del response                \n",
    "\n",
    "                image = Image.open(BytesIO(camera_response.content))\n",
    "                image_np = load_image_into_numpy_array(image)\n",
    "                image_np_expanded = np.expand_dims(image_np, axis=0)\n",
    "\n",
    "                (boxes, scores, classes, num) = sess.run(\n",
    "                      [detection_boxes, detection_scores, detection_classes, num_detections],\n",
    "                      feed_dict={image_tensor: image_np_expanded})\n",
    "\n",
    "                vis_util.visualize_boxes_and_labels_on_image_array(\n",
    "                      image_np,\n",
    "                      np.squeeze(boxes),\n",
    "                      np.squeeze(classes).astype(np.int32),\n",
    "                      np.squeeze(scores),\n",
    "                      category_index,\n",
    "                      use_normalized_coordinates=True,\n",
    "                      line_thickness=8)\n",
    "                \n",
    "                car_count, people_count, bicycle_count, motorcycle_count, bus_count, truck_count = object_counter(np.squeeze(classes).astype(np.int32), np.squeeze(scores))\n",
    "                vehicle_count = car_count + motorcycle_count + bus_count + truck_count\n",
    "                total_count = vehicle_count + bicycle_count + people_count\n",
    "                \n",
    "                # Retrieve the feature from the feature layer to update\n",
    "                obj_fset = object_point_lyr.query(where=\"\"\"name = '\"\"\"+camera_name+\"\"\"'\"\"\", return_geometry=False)  \n",
    "                all_features = obj_fset.features\n",
    "                original_feature = all_features[0]\n",
    "                feature_to_be_updated = deepcopy(original_feature)\n",
    "                \n",
    "                features_for_update = []\n",
    "                feature_to_be_updated.attributes['rt_object_count'] = total_count\n",
    "                feature_to_be_updated.attributes['rt_vehicle_count'] = vehicle_count\n",
    "                feature_to_be_updated.attributes['rt_car_count'] = car_count\n",
    "                feature_to_be_updated.attributes['rt_bus_count'] = bus_count\n",
    "                feature_to_be_updated.attributes['rt_truck_count'] = truck_count\n",
    "                feature_to_be_updated.attributes['rt_motorcycle_count'] = motorcycle_count\n",
    "                feature_to_be_updated.attributes['rt_pedestrian_count'] = people_count\n",
    "                feature_to_be_updated.attributes['rt_bicycle_count'] = bicycle_count\n",
    "                \n",
    "                feature_to_be_updated.attributes['source_image'] = camera_jpeg_url\n",
    "\n",
    "    #             feature_to_be_updated.attributes['rt_car_count'] = car_count\n",
    "                features_for_update.append(feature_to_be_updated)\n",
    "                object_point_lyr.edit_features(updates=features_for_update)    \n",
    "        \n",
    "                # Perform attachment of detected image\n",
    "                scipy.misc.imsave('detected_objs.jpg', image_np)\n",
    "                obj_id = feature_to_be_updated.attributes['F__OBJECTID']\n",
    "                \n",
    "                if overwrite_attachment:\n",
    "                    for attachment in object_point_lyr.attachments.get_list(obj_id):\n",
    "                        object_point_lyr.attachments.delete(obj_id, attachment['id'])\n",
    "                                               \n",
    "                object_point_lyr.attachments.add(obj_id, 'source.jpg')\n",
    "                object_point_lyr.attachments.add(obj_id, 'detected_objs.jpg')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## P2: Perform Updates Along Constitution Avenue"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Perform run on subset along Constitution Ave."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "                       <a href='https://esrifederal.maps.arcgis.com/home/item.html?id=e1437573230c4664a51a6d1e8d8d7176' target='_blank'>\n",
       "                        <img src='data:image/png;base64,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' width='200' height='133' class=\"itemThumbnail\">\n",
       "                       </a>\n",
       "                    </div>\n",
       "\n",
       "                    <div class=\"item_right\"     style=\"float: none; width: auto; overflow: hidden;\">\n",
       "                        <a href='https://esrifederal.maps.arcgis.com/home/item.html?id=e1437573230c4664a51a6d1e8d8d7176' target='_blank'><b>DC_TrafficCameras_ConstitutionAve</b>\n",
       "                        </a>\n",
       "                        <br/><img src='https://esrifederal.maps.arcgis.com/home/js/jsapi/esri/css/images/item_type_icons/featureshosted16.png' style=\"vertical-align:middle;\">Feature Layer Collection by albe9057@esri.com_esrifederal\n",
       "                        <br/>Last Modified: February 26, 2018\n",
       "                        <br/>0 comments, 0 views\n",
       "                    </div>\n",
       "                </div>\n",
       "                "
      ],
      "text/plain": [
       "<Item title:\"DC_TrafficCameras_ConstitutionAve\" type:Feature Layer Collection owner:albe9057@esri.com_esrifederal>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "object_point_srvc_const_ave = gis.content.search(\"DC_TrafficCameras_ConstitutionAve\", item_type=\"feature service\")[0]\n",
    "object_point_srvc_const_ave"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Convert our existing service into a pandas dataframe\n",
    "object_point_lyr_const_ave = object_point_srvc_const_ave.layers[0]\n",
    "obj_fset_const_ave = object_point_lyr_const_ave.query()  #querying without any conditions returns all the features\n",
    "obj_df_const_ave = obj_fset_const_ave.df\n",
    "constitutionave_names_list = obj_df_const_ave.name.tolist()\n",
    "ddot_constitutionave_df = ddot_df[ddot_df.name.isin(constitutionave_names_list)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "https://esrifederal.maps.arcgis.com/home/webmap/viewer.html?webmap=e081b389ac8d4bdb817c34dbe78a5fc4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "overwrite_attachment = True\n",
    "\n",
    "with detection_graph.as_default():\n",
    "    \n",
    "    with tf.Session(graph=detection_graph) as sess:\n",
    "        \n",
    "        image_tensor = detection_graph.get_tensor_by_name('image_tensor:0')\n",
    "        detection_boxes = detection_graph.get_tensor_by_name('detection_boxes:0')\n",
    "        detection_scores = detection_graph.get_tensor_by_name('detection_scores:0')\n",
    "        detection_classes = detection_graph.get_tensor_by_name('detection_classes:0')\n",
    "        num_detections = detection_graph.get_tensor_by_name('num_detections:0')\n",
    "\n",
    "        for iteration in range(10):\n",
    "            print()\n",
    "            \n",
    "            for ix, row in enumerate(ddot_constitutionave_df.iterrows()):\n",
    "                print(\"Processing camera {0} of {1}...\".format(str(ix+1), str(ddot_constitutionave_df.shape[0])))\n",
    "\n",
    "                # Retrieve camera information\n",
    "                camera_jpeg_url = ddot_constitutionave_df.iloc[ix]['content']['hugeJpeg']\n",
    "                camera_lat = ddot_constitutionave_df.iloc[ix]['location']['latitude']\n",
    "                camera_lon = ddot_constitutionave_df.iloc[ix]['location']['longitude']\n",
    "                camera_name = ddot_constitutionave_df.iloc[ix]['name']\n",
    "                camera_id = ddot_constitutionave_df.iloc[ix]['publicId']\n",
    "                \n",
    "                # Retrieve the camera image\n",
    "                camera_response = requests.get(camera_jpeg_url)\n",
    "\n",
    "                image = Image.open(BytesIO(camera_response.content))\n",
    "                image_np = load_image_into_numpy_array(image)\n",
    "                image_np_expanded = np.expand_dims(image_np, axis=0)\n",
    "\n",
    "                (boxes, scores, classes, num) = sess.run(\n",
    "                      [detection_boxes, detection_scores, detection_classes, num_detections],\n",
    "                      feed_dict={image_tensor: image_np_expanded})\n",
    "\n",
    "                vis_util.visualize_boxes_and_labels_on_image_array(\n",
    "                      image_np,\n",
    "                      np.squeeze(boxes),\n",
    "                      np.squeeze(classes).astype(np.int32),\n",
    "                      np.squeeze(scores),\n",
    "                      category_index,\n",
    "                      use_normalized_coordinates=True,\n",
    "                      line_thickness=8)\n",
    "                \n",
    "                car_count, people_count, bicycle_count, motorcycle_count, bus_count, truck_count = object_counter(np.squeeze(classes).astype(np.int32), np.squeeze(scores))\n",
    "                vehicle_count = car_count + motorcycle_count + bus_count + truck_count\n",
    "                total_count = vehicle_count + bicycle_count + people_count\n",
    "                \n",
    "                # Retrieve the feature from the feature layer to update\n",
    "                obj_fset = object_point_lyr.query(where=\"\"\"name = '\"\"\"+camera_name+\"\"\"'\"\"\", return_geometry=False)  \n",
    "                all_features = obj_fset.features\n",
    "                original_feature = all_features[0]\n",
    "                feature_to_be_updated = deepcopy(original_feature)\n",
    "                \n",
    "                features_for_update = []\n",
    "                feature_to_be_updated.attributes['rt_object_count'] = total_count\n",
    "                feature_to_be_updated.attributes['rt_vehicle_count'] = vehicle_count\n",
    "                feature_to_be_updated.attributes['rt_car_count'] = car_count\n",
    "                feature_to_be_updated.attributes['rt_bus_count'] = bus_count\n",
    "                feature_to_be_updated.attributes['rt_truck_count'] = truck_count\n",
    "                feature_to_be_updated.attributes['rt_motorcycle_count'] = motorcycle_count\n",
    "                feature_to_be_updated.attributes['rt_pedestrian_count'] = people_count\n",
    "                feature_to_be_updated.attributes['rt_bicycle_count'] = bicycle_count\n",
    "\n",
    "    #             feature_to_be_updated.attributes['rt_car_count'] = car_count\n",
    "                features_for_update.append(feature_to_be_updated)\n",
    "                object_point_lyr.edit_features(updates=features_for_update)    \n",
    "            \n",
    "                # Perform attachment of detected image\n",
    "                scipy.misc.imsave('detected_objs.jpg', image_np)\n",
    "#                 scipy.misc.imsave('ML_{0}.jpg'.format(str(datetime.now().strftime(\"%m%d%y_%H%M%S\"))), image_np)\n",
    "                obj_id = feature_to_be_updated.attributes['F__OBJECTID']\n",
    "    \n",
    "                if overwrite_attachment:\n",
    "                    object_point_lyr.attachments.delete(obj_id, 1)\n",
    "                \n",
    "                object_point_lyr.attachments.add(obj_id, 'detected_objs.jpg')\n",
    "#                 object_point_lyr.attachments.add(obj_id, 'ML_{0}.jpg'.format(str(datetime.now().strftime(\"%m%d%y_%H%M%S\"))))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## P3: Trend-setter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "                       <a href='https://esrifederal.maps.arcgis.com/home/item.html?id=041de891040140a898950ae441631fd2' target='_blank'>\n",
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       "                       </a>\n",
       "                    </div>\n",
       "\n",
       "                    <div class=\"item_right\"     style=\"float: none; width: auto; overflow: hidden;\">\n",
       "                        <a href='https://esrifederal.maps.arcgis.com/home/item.html?id=041de891040140a898950ae441631fd2' target='_blank'><b>DC_TrafficCameras_HIST_ConstAve</b>\n",
       "                        </a>\n",
       "                        <br/><img src='https://esrifederal.maps.arcgis.com/home/js/jsapi/esri/css/images/item_type_icons/featureshosted16.png' style=\"vertical-align:middle;\">Feature Layer Collection by albe9057@esri.com_esrifederal\n",
       "                        <br/>Last Modified: February 27, 2018\n",
       "                        <br/>0 comments, 4 views\n",
       "                    </div>\n",
       "                </div>\n",
       "                "
      ],
      "text/plain": [
       "<Item title:\"DC_TrafficCameras_HIST_ConstAve\" type:Feature Layer Collection owner:albe9057@esri.com_esrifederal>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "object_point_srvc = gis.content.search(\"DC_TrafficCameras_HIST_ConstAve\", item_type=\"feature service\")[0]\n",
    "object_point_srvc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>F__OBJECTID</th>\n",
       "      <th>OBJECTID</th>\n",
       "      <th>attribute_0</th>\n",
       "      <th>content</th>\n",
       "      <th>createdAt</th>\n",
       "      <th>description</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>name</th>\n",
       "      <th>observation_time</th>\n",
       "      <th>...</th>\n",
       "      <th>recording_time</th>\n",
       "      <th>rt_bicycle_count</th>\n",
       "      <th>rt_bus_count</th>\n",
       "      <th>rt_car_count</th>\n",
       "      <th>rt_motorcycle_count</th>\n",
       "      <th>rt_object_count</th>\n",
       "      <th>rt_pedestrian_count</th>\n",
       "      <th>rt_truck_count</th>\n",
       "      <th>rt_vehicle_count</th>\n",
       "      <th>SHAPE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <td>1410450964690</td>\n",
       "      <td>None</td>\n",
       "      <td>38.892306</td>\n",
       "      <td>-77.028276</td>\n",
       "      <td>12th St @ Constitution Ave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>{'x': -8574748, 'y': 4706257}</td>\n",
       "    </tr>\n",
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       "      <th>1</th>\n",
       "      <td>2</td>\n",
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       "      <td>{'halfJpeg': 'http://ie.trafficland.com/v1.0/2...</td>\n",
       "      <td>1410450997585</td>\n",
       "      <td>None</td>\n",
       "      <td>38.892269</td>\n",
       "      <td>-77.024097</td>\n",
       "      <td>9th St @ Constitution Ave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>{'x': -8574283, 'y': 4706252}</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
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       "      <td>{'halfJpeg': 'http://ie.trafficland.com/v1.0/2...</td>\n",
       "      <td>1410451320851</td>\n",
       "      <td>None</td>\n",
       "      <td>38.892212</td>\n",
       "      <td>-77.033831</td>\n",
       "      <td>Constitution Ave @ 15th St</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>{'x': -8575367, 'y': 4706244}</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>None</td>\n",
       "      <td>{'halfJpeg': 'http://ie.trafficland.com/v1.0/2...</td>\n",
       "      <td>1410454639501</td>\n",
       "      <td>None</td>\n",
       "      <td>38.892221</td>\n",
       "      <td>-77.039654</td>\n",
       "      <td>Constitution Ave @ 17th St</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
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       "      <td>{'x': -8576015, 'y': 4706245}</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>None</td>\n",
       "      <td>{'halfJpeg': 'http://ie.trafficland.com/v1.0/2...</td>\n",
       "      <td>1410454655458</td>\n",
       "      <td>None</td>\n",
       "      <td>38.891985</td>\n",
       "      <td>-77.049949</td>\n",
       "      <td>Constitution Ave @ 23rd St</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>{'x': -8577161, 'y': 4706211}</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   F__OBJECTID  OBJECTID attribute_0  \\\n",
       "0            1         1        None   \n",
       "1            2         2        None   \n",
       "2            3         3        None   \n",
       "3            4         4        None   \n",
       "4            5         5        None   \n",
       "\n",
       "                                             content      createdAt  \\\n",
       "0  {'halfJpeg': 'http://ie.trafficland.com/v1.0/2...  1410450964690   \n",
       "1  {'halfJpeg': 'http://ie.trafficland.com/v1.0/2...  1410450997585   \n",
       "2  {'halfJpeg': 'http://ie.trafficland.com/v1.0/2...  1410451320851   \n",
       "3  {'halfJpeg': 'http://ie.trafficland.com/v1.0/2...  1410454639501   \n",
       "4  {'halfJpeg': 'http://ie.trafficland.com/v1.0/2...  1410454655458   \n",
       "\n",
       "  description   latitude  longitude                        name  \\\n",
       "0        None  38.892306 -77.028276  12th St @ Constitution Ave   \n",
       "1        None  38.892269 -77.024097   9th St @ Constitution Ave   \n",
       "2        None  38.892212 -77.033831  Constitution Ave @ 15th St   \n",
       "3        None  38.892221 -77.039654  Constitution Ave @ 17th St   \n",
       "4        None  38.891985 -77.049949  Constitution Ave @ 23rd St   \n",
       "\n",
       "   observation_time              ...               recording_time  \\\n",
       "0               NaN              ...                         None   \n",
       "1               NaN              ...                         None   \n",
       "2               NaN              ...                         None   \n",
       "3               NaN              ...                         None   \n",
       "4               NaN              ...                         None   \n",
       "\n",
       "  rt_bicycle_count rt_bus_count rt_car_count  rt_motorcycle_count  \\\n",
       "0                0            0            0                    0   \n",
       "1                0            0            0                    0   \n",
       "2                0            0            0                    0   \n",
       "3                0            0            0                    0   \n",
       "4                0            0            0                    0   \n",
       "\n",
       "  rt_object_count rt_pedestrian_count  rt_truck_count  rt_vehicle_count  \\\n",
       "0               0                   0               0                 0   \n",
       "1               0                   0               0                 0   \n",
       "2               0                   0               0                 0   \n",
       "3               0                   0               0                 0   \n",
       "4               0                   0               0                 0   \n",
       "\n",
       "                           SHAPE  \n",
       "0  {'x': -8574748, 'y': 4706257}  \n",
       "1  {'x': -8574283, 'y': 4706252}  \n",
       "2  {'x': -8575367, 'y': 4706244}  \n",
       "3  {'x': -8576015, 'y': 4706245}  \n",
       "4  {'x': -8577161, 'y': 4706211}  \n",
       "\n",
       "[5 rows x 26 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Convert our existing service into a pandas dataframe\n",
    "object_point_lyr = object_point_srvc.layers[0]\n",
    "obj_fset = object_point_lyr.query()  #querying without any conditions returns all the features\n",
    "obj_df = obj_fset.df\n",
    "obj_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "https://esrifederal.maps.arcgis.com/home/webmap/viewer.html?webmap=b99df66a66d64538995aecc98547dc40"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "With auto-refresh of source JSON"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Refresh iteration 0...\n",
      "Iteration: 0 of 100\n",
      "Iteration: 1 of 100\n",
      "Iteration: 2 of 100\n",
      "Iteration: 3 of 100\n",
      "Iteration: 4 of 100\n",
      "Iteration: 5 of 100\n",
      "Iteration: 6 of 100\n",
      "Iteration: 7 of 100\n",
      "Iteration: 8 of 100\n",
      "Iteration: 9 of 100\n"
     ]
    }
   ],
   "source": [
    "with detection_graph.as_default():\n",
    "    \n",
    "    with tf.Session(graph=detection_graph) as sess:\n",
    "        \n",
    "        image_tensor = detection_graph.get_tensor_by_name('image_tensor:0')\n",
    "        detection_boxes = detection_graph.get_tensor_by_name('detection_boxes:0')\n",
    "        detection_scores = detection_graph.get_tensor_by_name('detection_scores:0')\n",
    "        detection_classes = detection_graph.get_tensor_by_name('detection_classes:0')\n",
    "        num_detections = detection_graph.get_tensor_by_name('num_detections:0')\n",
    "        \n",
    "        for refresh_iteration in range(1):\n",
    "            print(\"Refresh iteration {0}...\".format(str(refresh_iteration)))\n",
    "            \n",
    "            # TrafficLand API source JSON\n",
    "            source_json = r\"http://api.trafficland.com/v1.5/json/video_feeds?system=ddot&key=1594c8892d7fbd18181a8a6a44958b28\"\n",
    "            df = pd.read_json(source_json)\n",
    "            ddot_df = df.loc[df.provider == 'DDOT']\n",
    "            ddot_constitutionave_df = ddot_df[ddot_df.name.isin(constitutionave_names_list)]\n",
    "            \n",
    "            for iteration in range(100):\n",
    "                print(\"Iteration: {0} of {1}\".format(str(iteration), str(100)))\n",
    "\n",
    "                for ix, row in enumerate(ddot_constitutionave_df.iterrows()):\n",
    "\n",
    "                    # Retrieve camera information\n",
    "                    camera_jpeg_url = ddot_constitutionave_df.iloc[ix]['content']['hugeJpeg']\n",
    "                    camera_name = ddot_constitutionave_df.iloc[ix]['name']\n",
    "                    camera_id = ddot_constitutionave_df.iloc[ix]['publicId']\n",
    "\n",
    "                    # Retrieve the camera image\n",
    "                    camera_response = requests.get(camera_jpeg_url)\n",
    "\n",
    "                    image = Image.open(BytesIO(camera_response.content))\n",
    "                    image_np = load_image_into_numpy_array(image)\n",
    "                    image_np_expanded = np.expand_dims(image_np, axis=0)\n",
    "\n",
    "                    (boxes, scores, classes, num) = sess.run(\n",
    "                          [detection_boxes, detection_scores, detection_classes, num_detections],\n",
    "                          feed_dict={image_tensor: image_np_expanded})\n",
    "\n",
    "                    vis_util.visualize_boxes_and_labels_on_image_array(\n",
    "                          image_np,\n",
    "                          np.squeeze(boxes),\n",
    "                          np.squeeze(classes).astype(np.int32),\n",
    "                          np.squeeze(scores),\n",
    "                          category_index,\n",
    "                          use_normalized_coordinates=True,\n",
    "                          line_thickness=8)\n",
    "\n",
    "                    car_count, people_count, bicycle_count, motorcycle_count, bus_count, truck_count = object_counter(np.squeeze(classes).astype(np.int32), np.squeeze(scores))\n",
    "                    vehicle_count = car_count + motorcycle_count + bus_count + truck_count\n",
    "                    total_count = vehicle_count + bicycle_count + people_count\n",
    "\n",
    "                    # Retrieve the feature from the feature layer to update\n",
    "                    obj_fset = object_point_lyr.query(where=\"\"\"name = '\"\"\"+camera_name+\"\"\"'\"\"\")  \n",
    "                    all_features = obj_fset.features\n",
    "                    original_feature = all_features[0]\n",
    "\n",
    "                    features_to_be_added = []\n",
    "                    new_feature = deepcopy(original_feature)\n",
    "\n",
    "                    new_feature.attributes['rt_object_count'] = total_count\n",
    "                    new_feature.attributes['rt_vehicle_count'] = vehicle_count\n",
    "                    new_feature.attributes['rt_car_count'] = car_count\n",
    "                    new_feature.attributes['rt_bus_count'] = bus_count\n",
    "                    new_feature.attributes['rt_truck_count'] = truck_count\n",
    "                    new_feature.attributes['rt_motorcycle_count'] = motorcycle_count\n",
    "                    new_feature.attributes['rt_pedestrian_count'] = people_count\n",
    "                    new_feature.attributes['rt_bicycle_count'] = bicycle_count\n",
    "                    new_feature.attributes['recording_id'] = \"Cam{0}_{1}\".format(str(ix),\n",
    "                                                                                 str(datetime.now().strftime(\"%m%d%y_%H%M%S\")))\n",
    "                    new_feature.attributes['observation_time'] = datetime.now().strftime(\"%m/%d/%y %H:%M:%S\")\n",
    "\n",
    "                    #add this to the list of features to be updated\n",
    "                    features_to_be_added.append(new_feature)\n",
    "\n",
    "                    object_point_lyr.edit_features(adds = features_to_be_added) "
   ]
  }
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