ResNet50RetinaNet-Error-Analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load necessary modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "# show images inline\n",
    "%matplotlib inline\n",
    "\n",
    "# automatically reload modules when they have changed\n",
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "\n",
    "# import keras\n",
    "import keras\n",
    "\n",
    "# import keras_retinanet\n",
    "from keras_retinanet import models\n",
    "from keras_retinanet.utils.image import read_image_bgr, preprocess_image, resize_image\n",
    "from keras_retinanet.utils.visualization import draw_box, draw_caption\n",
    "from keras_retinanet.utils.colors import label_color\n",
    "\n",
    "# import miscellaneous modules\n",
    "import matplotlib.pyplot as plt\n",
    "import cv2\n",
    "import os\n",
    "import numpy as np\n",
    "import time\n",
    "import csv\n",
    "# set tf backend to allow memory to grow, instead of claiming everything\n",
    "import tensorflow as tf\n",
    "\n",
    "def get_session():\n",
    "    config = tf.ConfigProto()\n",
    "    config.gpu_options.allow_growth = True\n",
    "    return tf.Session(config=config)\n",
    "\n",
    "# use this environment flag to change which GPU to use\n",
    "os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"0\"\n",
    "\n",
    "# set the modified tf session as backend in keras\n",
    "keras.backend.tensorflow_backend.set_session(get_session())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load RetinaNet model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/priya/.local/lib/python3.6/site-packages/keras/engine/saving.py:292: UserWarning: No training configuration found in save file: the model was *not* compiled. Compile it manually.\n",
      "  warnings.warn('No training configuration found in save file: '\n"
     ]
    }
   ],
   "source": [
    "# adjust this to point to your downloaded/trained model\n",
    "# models can be downloaded here: https://github.com/fizyr/keras-retinanet/releases\n",
    "model_path = os.path.join('snapshots', 'version8_resplit_test_train', 'resnet50_csv_12_inference.h5')\n",
    "\n",
    "# load retinanet model\n",
    "model = models.load_model(model_path, backbone_name='resnet50')\n",
    "\n",
    "# if the model is not converted to an inference model, use the line below\n",
    "# see: https://github.com/fizyr/keras-retinanet#converting-a-training-model-to-inference-model\n",
    "#model = models.convert_model(model)\n",
    "\n",
    "#print(model.summary())\n",
    "\n",
    "# load label to names mapping for visualization purposes\n",
    "labels_to_names = {0: 'Biker', 1: 'Car', 2: 'Bus', 3: 'Cart', 4: 'Skater', 5: 'Pedestrian'}\n",
    "# labels_to_names = {0: 'person', 1: 'bicycle', 2: 'car', 3: 'motorcycle', 4: 'airplane', 5: 'bus', 6: 'train', 7: 'truck', 8: 'boat', 9: 'traffic light', 10: 'fire hydrant', 11: 'stop sign', 12: 'parking meter', 13: 'bench', 14: 'bird', 15: 'cat', 16: 'dog', 17: 'horse', 18: 'sheep', 19: 'cow', 20: 'elephant', 21: 'bear', 22: 'zebra', 23: 'giraffe', 24: 'backpack', 25: 'umbrella', 26: 'handbag', 27: 'tie', 28: 'suitcase', 29: 'frisbee', 30: 'skis', 31: 'snowboard', 32: 'sports ball', 33: 'kite', 34: 'baseball bat', 35: 'baseball glove', 36: 'skateboard', 37: 'surfboard', 38: 'tennis racket', 39: 'bottle', 40: 'wine glass', 41: 'cup', 42: 'fork', 43: 'knife', 44: 'spoon', 45: 'bowl', 46: 'banana', 47: 'apple', 48: 'sandwich', 49: 'orange', 50: 'broccoli', 51: 'carrot', 52: 'hot dog', 53: 'pizza', 54: 'donut', 55: 'cake', 56: 'chair', 57: 'couch', 58: 'potted plant', 59: 'bed', 60: 'dining table', 61: 'toilet', 62: 'tv', 63: 'laptop', 64: 'mouse', 65: 'remote', 66: 'keyboard', 67: 'cell phone', 68: 'microwave', 69: 'oven', 70: 'toaster', 71: 'sink', 72: 'refrigerator', 73: 'book', 74: 'clock', 75: 'vase', 76: 'scissors', 77: 'teddy bear', 78: 'hair drier', 79: 'toothbrush'}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. Load CSV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "663\n"
     ]
    }
   ],
   "source": [
    "annotations_file = 'test_annotations.csv'\n",
    "cwd = os.getcwd()\n",
    "\n",
    "image_names = []\n",
    "\n",
    "with open (os.path.join(cwd, annotations_file)) as csvfile:\n",
    "    readCSV = csv.reader(csvfile, delimiter='\\n')\n",
    "    for row in readCSV:\n",
    "        vals = row[0].split(',')\n",
    "        this_filepath = vals[0]\n",
    "        image_names.append(this_filepath)\n",
    "        \n",
    "## remove duplicates by taking a set\n",
    "image_names = list(set(image_names))\n",
    "print(len(image_names))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['imgs/test/little_video1_7890.jpg', 'imgs/test/bookstore_video1_12390.jpg']\n"
     ]
    }
   ],
   "source": [
    "print(image_names[:2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "score_threshold_retinanet = 0.4\n",
    "acceptable_box_overlap = 0.3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. Extract Ground Truth Annotations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_gt_annotations(filepath):\n",
    "    gt_ann = []\n",
    "    with open (os.path.join(cwd, annotations_file)) as csvfile:\n",
    "        readCSV = csv.reader(csvfile, delimiter='\\n')\n",
    "        for row in readCSV:\n",
    "            vals = row[0].split(',')\n",
    "            this_filepath = vals[0]\n",
    "            \n",
    "            if this_filepath == filepath:\n",
    "                record = []\n",
    "                record.append(int(vals[1]))\n",
    "                record.append(int(vals[2]))\n",
    "                record.append(int(vals[3]))\n",
    "                record.append(int(vals[4]))\n",
    "                record.append(vals[5])\n",
    "                \n",
    "                gt_ann.append(record)\n",
    "    return gt_ann\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3. IOU Calculations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def bb_intersection_over_union(boxA, boxB):\n",
    "\t# determine the (x, y)-coordinates of the intersection rectangle\n",
    "\txA = max(int(boxA[0]), int(boxB[0]))\n",
    "\tyA = max(int(boxA[1]), int(boxB[1]))\n",
    "\txB = min(int(boxA[2]), int(boxB[2]))\n",
    "\tyB = min(int(boxA[3]), int(boxB[3]))\n",
    " \n",
    "\t# compute the area of intersection rectangle\n",
    "\tinterArea = max(0, xB - xA + 1) * max(0, yB - yA + 1)\n",
    " \n",
    "\t# compute the area of both the prediction and ground-truth\n",
    "\t# rectangles\n",
    "\tboxAArea = (int(boxA[2]) - int(boxA[0]) + 1) * (int(boxA[3]) - int(boxA[1]) + 1)\n",
    "\tboxBArea = (int(boxB[2]) - int(boxB[0]) + 1) * (int(boxB[3]) - int(boxB[1]) + 1)\n",
    " \n",
    "\t# compute the intersection over union by taking the intersection\n",
    "\t# area and dividing it by the sum of prediction + ground-truth\n",
    "\t# areas - the interesection area\n",
    "\tiou = interArea / float(boxAArea + boxBArea - interArea)\n",
    " \n",
    "\t# return the intersection over union value\n",
    "\treturn iou"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def highest_iou(predicted_box, gt_ann):\n",
    "    \n",
    "    highest_iou = 0\n",
    "    best_match = []\n",
    "    for each_gt in gt_ann:\n",
    "        this_iou = bb_intersection_over_union(predicted_box[:-1], each_gt[:-1])\n",
    "#         print(\" For this box is: \", this_iou)\n",
    "        if this_iou > highest_iou:\n",
    "            highest_iou = this_iou\n",
    "            best_match = each_gt\n",
    "            \n",
    "    return highest_iou, best_match\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def accuracy(gt_ann, predicted_ann):\n",
    "    true_positive = []\n",
    "    class_mismatch = []\n",
    "    false_positive = []\n",
    "    false_negative = []\n",
    "    \n",
    "    predicted_ann_copy = predicted_ann.copy()\n",
    "    gt_ann_copy = gt_ann.copy()\n",
    "    \n",
    "    for each_pred in predicted_ann_copy:\n",
    "        # 1. Calculate the highest_iou with any gt_box\n",
    "        best_iou, best_gt_match = highest_iou(each_pred, gt_ann_copy)\n",
    "#         print(\"Best IOU is: \", each_pred, best_gt_match, best_iou)\n",
    "        \n",
    "        ## If this box has a match\n",
    "        if best_iou >= acceptable_box_overlap:\n",
    "            ## if class label matches\n",
    "            if best_gt_match[-1] == each_pred[-1]:\n",
    "                ## This is a true positive\n",
    "                true_positive.append(each_pred)\n",
    "                ## remove this from predicted ann and gt\n",
    "#                 print(\"Predicted Ann before:\", predicted_ann)\n",
    "                predicted_ann.remove(each_pred)\n",
    "#                 print(\"Predicted Ann after:\", predicted_ann)\n",
    "                if best_gt_match in gt_ann:\n",
    "                    gt_ann.remove(best_gt_match)\n",
    "            elif best_gt_match[-1] != each_pred[-1]:\n",
    "                ## this is a class mismatch\n",
    "                class_mismatch.append(each_pred)\n",
    "                ## remove this box\n",
    "                predicted_ann.remove(each_pred)\n",
    "                if best_gt_match in gt_ann:\n",
    "                    gt_ann.remove(best_gt_match)\n",
    "        \n",
    "    ## If IOU is less than 0.5, leave as is\n",
    "\n",
    "    ## Any predicted box is now false positive\n",
    "    for remain_pred in predicted_ann:\n",
    "        false_positive.append(remain_pred)\n",
    "\n",
    "    ## Any remaining gt box is false negative\n",
    "    for remain_gt in gt_ann:\n",
    "        if remain_gt[-1] in ['Biker', 'Pedestrian', 'Car', 'Bus']:\n",
    "            false_negative.append(remain_gt)\n",
    "\n",
    "    return true_positive, class_mismatch, false_positive, false_negative       "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3. Draw Predicted and GT Annotations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def run_detection_image(filepath):\n",
    "    image = read_image_bgr(filepath)\n",
    "\n",
    "    # copy to draw on\n",
    "    draw = image.copy()\n",
    "    draw = cv2.cvtColor(draw, cv2.COLOR_BGR2RGB)\n",
    "\n",
    "    # preprocess image for network\n",
    "    image = preprocess_image(image)\n",
    "    image, scale = resize_image(image)\n",
    "\n",
    "    # process image\n",
    "    start = time.time()\n",
    "    boxes, scores, labels = model.predict_on_batch(np.expand_dims(image, axis=0))\n",
    "    print(\"processing time: \", time.time() - start)\n",
    "\n",
    "    # correct for image scale\n",
    "    boxes /= scale\n",
    "    \n",
    "    gt_ann = get_gt_annotations(filepath)\n",
    "    num_gt_ann = len(gt_ann)\n",
    "    \n",
    "    predicted_ann = []\n",
    "\n",
    "    # visualize detections\n",
    "    for box, score, label in zip(boxes[0], scores[0], labels[0]):\n",
    "        # scores are sorted so we can break\n",
    "        if score < score_threshold_retinanet:\n",
    "            break\n",
    "        record = []\n",
    "        record.append(int(box[0]))\n",
    "        record.append(int(box[1]))\n",
    "        record.append(int(box[2]))\n",
    "        record.append(int(box[3]))\n",
    "        record.append(labels_to_names[label])\n",
    "        print(\"Record is: \", record)\n",
    "        predicted_ann.append(record)\n",
    "    \n",
    "    \n",
    "#     print(\"predicted ann are: \", predicted_ann)\n",
    "    ## Calculate boxes\n",
    "    true_positive, class_mismatch, false_positive, false_negative = accuracy(gt_ann, predicted_ann)\n",
    "    print(len(true_positive), len(class_mismatch), len(false_positive), len(false_negative))\n",
    "    \n",
    "    font = cv2.FONT_HERSHEY_SIMPLEX\n",
    "    ## Draw theses on the image\n",
    "    ## Draw true positive in green\n",
    "    if len(true_positive) > 0:\n",
    "        for each_true in true_positive:\n",
    "            cv2.rectangle(draw,(each_true[0],each_true[1]),(each_true[2],each_true[3]),(0,255,0),3) #green\n",
    "            cv2.putText(draw, each_true[-1], (each_true[0]-2, each_true[1]-2),font, 0.5,\n",
    "                        (0,0,0),1,cv2.LINE_AA) # text in black\n",
    "        \n",
    "    ## Draw class mismatch in light blue   \n",
    "    if len(class_mismatch) > 0:\n",
    "        for each_mismatch in class_mismatch:\n",
    "            cv2.rectangle(draw,(each_mismatch[0],each_mismatch[1]),(each_mismatch[2],each_mismatch[3]),(255,255,0),3) #green\n",
    "            cv2.putText(draw, each_mismatch[-1], (each_mismatch[0]-2, each_mismatch[1]-2),font, 0.5,\n",
    "                        (0,0,0),1,cv2.LINE_AA) # text in black\n",
    "        \n",
    "    \n",
    "     ## Draw false positive  in blue \n",
    "    if len(false_positive) > 0:\n",
    "        for each_fp in false_positive:\n",
    "            cv2.rectangle(draw,(each_fp[0],each_fp[1]),(each_fp[2],each_fp[3]),(255,0,0),3) #green\n",
    "            cv2.putText(draw, each_fp[-1], (each_fp[0]-2, each_fp[1]-2),font, 0.5,\n",
    "                        (0,0,0),1,cv2.LINE_AA) # text in black\n",
    "    \n",
    "    \n",
    "     ## Draw false negative in red \n",
    "    if len(false_negative) > 0:\n",
    "        for each_fn in false_negative:\n",
    "            cv2.rectangle(draw,(each_fn[0],each_fn[1]),(each_fn[2],each_fn[3]),(0,0,255),3) #green\n",
    "            cv2.putText(draw, each_fn[-1], (each_fn[0]-2, each_fn[1]-2),font, 0.5,\n",
    "                        (0,0,0),1,cv2.LINE_AA) # text in black\n",
    "            \n",
    "            \n",
    "    ## Add key to the image\n",
    "    cv2.putText(draw, \"True Positive\", (1200, 20),font, 0.8, (0,255,0),1,cv2.LINE_AA) \n",
    "    cv2.putText(draw, \"Class Mismatch\", (1200, 50),font, 0.8, (255,255,0),1,cv2.LINE_AA)\n",
    "    cv2.putText(draw, \"False Positive\", (1200, 80),font, 0.8, (255,0,0),1,cv2.LINE_AA)\n",
    "    cv2.putText(draw, \"False Negtaive\", (1200, 110),font, 0.8, (0,0,2550),1,cv2.LINE_AA)\n",
    "    \n",
    "    ### Save this image\n",
    "    \n",
    "    file, ext = os.path.splitext(filepath)\n",
    "    image_name = file.split('/')[-1] + ext\n",
    "    output_path = os.path.join('examples/results_test/', image_name)\n",
    "    \n",
    "    draw_conv = cv2.cvtColor(draw, cv2.COLOR_BGR2RGB)\n",
    "    cv2.imwrite(output_path, draw_conv)\n",
    "    \n",
    "    return len(true_positive), len(class_mismatch), len(false_positive), len(false_negative), num_gt_ann\n",
    "\n",
    "#         color = label_color(label)\n",
    "\n",
    "#         b = box.astype(int)\n",
    "#         draw_box(draw, b, color=color)\n",
    "\n",
    "#         caption = \"{} {:.3f}\".format(labels_to_names[label], score)\n",
    "#         draw_caption(draw, b, caption)\n",
    "\n",
    "#     plt.figure(figsize=(15, 15))\n",
    "#     plt.axis('off')\n",
    "#     plt.imshow(draw)\n",
    "#     plt.show()\n",
    "    \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "total_true_positive = 0\n",
    "total_class_mismatch = 0\n",
    "total_false_positive = 0\n",
    "total_false_negative = 0\n",
    "total_gt = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "processing time:  1.293830394744873\n",
      "Record is:  [804, 829, 860, 914, 'Biker']\n",
      "Record is:  [1057, 1720, 1125, 1817, 'Biker']\n",
      "Record is:  [1041, 1706, 1115, 1814, 'Pedestrian']\n",
      "Record is:  [974, 872, 1039, 962, 'Biker']\n",
      "Record is:  [981, 893, 1014, 959, 'Biker']\n",
      "Record is:  [929, 1767, 1001, 1851, 'Biker']\n",
      "Record is:  [72, 877, 124, 948, 'Biker']\n",
      "4 1 2 1\n",
      "Ground Truth:  5\n",
      "processing time:  0.31607723236083984\n",
      "Record is:  [1375, 202, 1409, 246, 'Pedestrian']\n",
      "Record is:  [992, 561, 1035, 597, 'Pedestrian']\n",
      "Record is:  [642, 347, 684, 398, 'Pedestrian']\n",
      "Record is:  [740, 266, 794, 316, 'Pedestrian']\n",
      "Record is:  [306, 792, 349, 846, 'Biker']\n",
      "Record is:  [1309, 945, 1356, 992, 'Biker']\n",
      "Record is:  [1232, 689, 1277, 739, 'Pedestrian']\n",
      "Record is:  [294, 869, 323, 916, 'Pedestrian']\n",
      "Record is:  [693, 688, 725, 743, 'Pedestrian']\n",
      "5 1 3 8\n",
      "Ground Truth:  14\n",
      "processing time:  0.05529141426086426\n",
      "Record is:  [384, 859, 454, 950, 'Biker']\n",
      "Record is:  [901, 827, 962, 918, 'Biker']\n",
      "2 0 0 0\n",
      "Ground Truth:  2\n",
      "processing time:  0.05298900604248047\n",
      "Record is:  [737, 265, 792, 312, 'Pedestrian']\n",
      "Record is:  [668, 327, 709, 385, 'Pedestrian']\n",
      "Record is:  [1380, 202, 1411, 246, 'Pedestrian']\n",
      "Record is:  [1281, 959, 1328, 1002, 'Biker']\n",
      "Record is:  [242, 86, 295, 137, 'Pedestrian']\n",
      "Record is:  [335, 685, 375, 727, 'Biker']\n",
      "Record is:  [1306, 964, 1349, 1009, 'Pedestrian']\n",
      "Record is:  [198, 619, 226, 669, 'Pedestrian']\n",
      "Record is:  [303, 195, 329, 241, 'Pedestrian']\n",
      "Record is:  [343, 500, 386, 555, 'Pedestrian']\n",
      "Record is:  [693, 690, 726, 738, 'Pedestrian']\n",
      "Record is:  [1283, 960, 1327, 1001, 'Pedestrian']\n",
      "Record is:  [1024, 1027, 1073, 1067, 'Biker']\n",
      "Record is:  [17, 413, 84, 463, 'Pedestrian']\n",
      "Record is:  [1303, 962, 1345, 1007, 'Biker']\n",
      "Record is:  [207, 491, 246, 535, 'Pedestrian']\n",
      "Record is:  [296, 647, 325, 708, 'Biker']\n",
      "Record is:  [241, 497, 265, 538, 'Pedestrian']\n",
      "Record is:  [1264, 962, 1305, 999, 'Pedestrian']\n",
      "12 4 3 5\n",
      "Ground Truth:  18\n",
      "processing time:  0.059927940368652344\n",
      "Record is:  [812, 680, 871, 766, 'Pedestrian']\n",
      "Record is:  [2, 656, 75, 746, 'Pedestrian']\n",
      "1 0 1 1\n",
      "Ground Truth:  2\n",
      "processing time:  0.06349420547485352\n",
      "Record is:  [616, 820, 678, 924, 'Biker']\n",
      "Record is:  [801, 861, 871, 963, 'Biker']\n",
      "Record is:  [985, 1729, 1050, 1826, 'Biker']\n",
      "Record is:  [1096, 1716, 1156, 1812, 'Biker']\n",
      "3 1 0 0\n",
      "Ground Truth:  4\n",
      "processing time:  0.3268094062805176\n",
      "Record is:  [635, 543, 703, 640, 'Biker']\n",
      "Record is:  [215, 953, 258, 1040, 'Pedestrian']\n",
      "Record is:  [558, 990, 658, 1110, 'Biker']\n",
      "Record is:  [422, 256, 492, 339, 'Biker']\n",
      "Record is:  [394, 339, 469, 436, 'Pedestrian']\n",
      "Record is:  [1341, 1080, 1383, 1158, 'Pedestrian']\n",
      "Record is:  [117, 1281, 195, 1388, 'Biker']\n",
      "Record is:  [1037, 1402, 1091, 1504, 'Biker']\n",
      "Record is:  [632, 739, 706, 856, 'Biker']\n",
      "Record is:  [1313, 1060, 1393, 1156, 'Pedestrian']\n",
      "Record is:  [950, 1305, 1025, 1402, 'Biker']\n",
      "Record is:  [922, 1422, 1001, 1525, 'Biker']\n",
      "Record is:  [105, 1482, 158, 1562, 'Pedestrian']\n",
      "Record is:  [837, 1606, 896, 1685, 'Biker']\n",
      "14 0 0 1\n",
      "Ground Truth:  14\n",
      "processing time:  0.056559085845947266\n",
      "Record is:  [383, 819, 451, 906, 'Biker']\n",
      "Record is:  [1138, 992, 1245, 1088, 'Biker']\n",
      "Record is:  [432, 1041, 479, 1147, 'Pedestrian']\n",
      "Record is:  [239, 1118, 286, 1209, 'Pedestrian']\n",
      "4 0 0 0\n",
      "Ground Truth:  4\n",
      "processing time:  0.05559206008911133\n",
      "Record is:  [1023, 1059, 1087, 1135, 'Pedestrian']\n",
      "Record is:  [1230, 986, 1322, 1097, 'Pedestrian']\n",
      "Record is:  [11, 676, 77, 766, 'Pedestrian']\n",
      "Record is:  [677, 746, 724, 841, 'Pedestrian']\n",
      "Record is:  [65, 655, 136, 741, 'Pedestrian']\n",
      "2 0 3 1\n",
      "Ground Truth:  3\n",
      "processing time:  0.052336692810058594\n",
      "Record is:  [1376, 196, 1408, 249, 'Pedestrian']\n",
      "Record is:  [1194, 994, 1259, 1042, 'Biker']\n",
      "Record is:  [711, 345, 762, 397, 'Pedestrian']\n",
      "Record is:  [842, 987, 890, 1037, 'Biker']\n",
      "Record is:  [541, 473, 582, 515, 'Pedestrian']\n",
      "Record is:  [730, 266, 787, 321, 'Pedestrian']\n",
      "Record is:  [830, 463, 883, 511, 'Biker']\n",
      "Record is:  [267, 960, 304, 1004, 'Pedestrian']\n",
      "Record is:  [1269, 965, 1304, 1003, 'Pedestrian']\n",
      "6 1 2 9\n",
      "Ground Truth:  16\n",
      "processing time:  0.05831742286682129\n",
      "Record is:  [1261, 1666, 1316, 1763, 'Pedestrian']\n",
      "Record is:  [71, 1157, 135, 1244, 'Pedestrian']\n",
      "Record is:  [769, 712, 823, 804, 'Pedestrian']\n",
      "3 0 0 0\n",
      "Ground Truth:  3\n",
      "processing time:  0.05534696578979492\n",
      "Record is:  [411, 822, 464, 888, 'Biker']\n",
      "Record is:  [1086, 1115, 1137, 1155, 'Pedestrian']\n",
      "Record is:  [1079, 1142, 1129, 1194, 'Pedestrian']\n",
      "3 0 0 0\n",
      "Ground Truth:  3\n",
      "processing time:  0.3475499153137207\n",
      "Record is:  [1325, 142, 1374, 184, 'Pedestrian']\n",
      "Record is:  [1276, 153, 1333, 194, 'Pedestrian']\n",
      "Record is:  [1598, 896, 1702, 974, 'Pedestrian']\n",
      "Record is:  [1279, 117, 1328, 158, 'Pedestrian']\n",
      "Record is:  [1272, 49, 1333, 95, 'Pedestrian']\n",
      "Record is:  [1407, 150, 1461, 201, 'Pedestrian']\n",
      "Record is:  [1333, 112, 1375, 152, 'Pedestrian']\n",
      "Record is:  [1572, 755, 1671, 838, 'Pedestrian']\n",
      "Record is:  [1471, 266, 1553, 316, 'Pedestrian']\n",
      "Record is:  [1198, 750, 1310, 810, 'Pedestrian']\n",
      "Record is:  [578, 339, 668, 410, 'Pedestrian']\n",
      "Record is:  [1441, 123, 1489, 163, 'Pedestrian']\n",
      "Record is:  [407, 350, 502, 422, 'Pedestrian']\n",
      "Record is:  [1403, 132, 1459, 186, 'Pedestrian']\n",
      "Record is:  [1117, 414, 1172, 458, 'Pedestrian']\n",
      "Record is:  [1092, 378, 1152, 439, 'Pedestrian']\n",
      "16 0 0 1\n",
      "Ground Truth:  17\n",
      "processing time:  0.05170130729675293\n",
      "Record is:  [1195, 318, 1239, 367, 'Pedestrian']\n",
      "Record is:  [1371, 202, 1408, 246, 'Pedestrian']\n",
      "Record is:  [307, 798, 350, 850, 'Biker']\n",
      "Record is:  [1041, 734, 1093, 790, 'Biker']\n",
      "Record is:  [699, 336, 742, 388, 'Pedestrian']\n",
      "Record is:  [1256, 965, 1307, 1009, 'Biker']\n",
      "5 1 0 8\n",
      "Ground Truth:  14\n",
      "processing time:  0.061643362045288086\n",
      "Record is:  [1286, 151, 1331, 190, 'Pedestrian']\n",
      "Record is:  [1328, 110, 1375, 150, 'Pedestrian']\n",
      "Record is:  [1325, 144, 1375, 182, 'Pedestrian']\n",
      "Record is:  [1409, 147, 1465, 200, 'Pedestrian']\n",
      "Record is:  [1432, 65, 1488, 106, 'Pedestrian']\n",
      "Record is:  [1274, 52, 1325, 99, 'Pedestrian']\n",
      "Record is:  [576, 341, 671, 413, 'Pedestrian']\n",
      "Record is:  [404, 354, 486, 417, 'Pedestrian']\n",
      "Record is:  [1412, 68, 1469, 110, 'Pedestrian']\n",
      "Record is:  [1440, 118, 1503, 165, 'Pedestrian']\n",
      "Record is:  [1292, 110, 1328, 151, 'Pedestrian']\n",
      "Record is:  [1455, 252, 1522, 310, 'Pedestrian']\n",
      "Record is:  [867, 935, 928, 1003, 'Pedestrian']\n",
      "Record is:  [1164, 432, 1254, 520, 'Biker']\n",
      "Record is:  [1407, 79, 1457, 120, 'Pedestrian']\n",
      "Record is:  [87, 743, 179, 821, 'Pedestrian']\n",
      "16 0 0 0\n",
      "Ground Truth:  14\n",
      "processing time:  0.05378317832946777\n",
      "Record is:  [1031, 1456, 1098, 1578, 'Biker']\n",
      "Record is:  [1196, 1070, 1229, 1148, 'Pedestrian']\n",
      "Record is:  [389, 464, 446, 562, 'Pedestrian']\n",
      "Record is:  [883, 1085, 974, 1199, 'Biker']\n",
      "Record is:  [781, 1249, 845, 1351, 'Biker']\n",
      "Record is:  [981, 1370, 1046, 1458, 'Biker']\n",
      "Record is:  [313, 715, 382, 820, 'Biker']\n",
      "Record is:  [209, 954, 256, 1052, 'Pedestrian']\n",
      "Record is:  [126, 1282, 180, 1366, 'Biker']\n",
      "Record is:  [247, 1488, 291, 1571, 'Pedestrian']\n",
      "Record is:  [1034, 1259, 1109, 1361, 'Biker']\n",
      "Record is:  [795, 1098, 875, 1198, 'Biker']\n",
      "Record is:  [1054, 1107, 1130, 1196, 'Biker']\n",
      "Record is:  [218, 1542, 261, 1621, 'Pedestrian']\n",
      "Record is:  [998, 1386, 1043, 1448, 'Biker']\n",
      "15 0 0 0\n",
      "Ground Truth:  14\n",
      "processing time:  0.051976919174194336\n",
      "Record is:  [613, 755, 656, 811, 'Pedestrian']\n",
      "Record is:  [686, 272, 722, 329, 'Pedestrian']\n",
      "Record is:  [576, 890, 615, 938, 'Pedestrian']\n",
      "Record is:  [465, 578, 512, 630, 'Pedestrian']\n",
      "Record is:  [681, 419, 708, 462, 'Pedestrian']\n",
      "Record is:  [1300, 869, 1361, 913, 'Biker']\n",
      "Record is:  [578, 869, 612, 919, 'Pedestrian']\n",
      "Record is:  [564, 855, 605, 905, 'Pedestrian']\n",
      "Record is:  [579, 851, 614, 905, 'Pedestrian']\n",
      "Record is:  [404, 389, 440, 442, 'Pedestrian']\n",
      "Record is:  [693, 421, 722, 464, 'Pedestrian']\n",
      "Record is:  [716, 332, 747, 374, 'Pedestrian']\n",
      "Record is:  [225, 489, 257, 533, 'Pedestrian']\n",
      "9 2 2 0\n",
      "Ground Truth:  10\n",
      "processing time:  0.054189443588256836\n",
      "Record is:  [1367, 526, 1403, 574, 'Pedestrian']\n",
      "Record is:  [698, 339, 743, 386, 'Pedestrian']\n",
      "Record is:  [1373, 458, 1406, 499, 'Pedestrian']\n",
      "Record is:  [888, 986, 917, 1020, 'Pedestrian']\n",
      "Record is:  [267, 574, 307, 623, 'Pedestrian']\n",
      "Record is:  [12, 922, 68, 966, 'Pedestrian']\n",
      "Record is:  [169, 592, 199, 635, 'Pedestrian']\n",
      "Record is:  [325, 386, 375, 450, 'Biker']\n",
      "Record is:  [109, 1027, 155, 1067, 'Pedestrian']\n",
      "Record is:  [465, 358, 509, 414, 'Pedestrian']\n",
      "Record is:  [875, 957, 919, 1008, 'Pedestrian']\n",
      "Record is:  [959, 23, 997, 57, 'Pedestrian']\n",
      "Record is:  [1328, 857, 1373, 917, 'Pedestrian']\n",
      "Record is:  [1310, 926, 1355, 980, 'Pedestrian']\n",
      "9 2 3 4\n",
      "Ground Truth:  14\n",
      "processing time:  0.05617237091064453\n",
      "Record is:  [896, 955, 1319, 1139, 'Bus']\n",
      "Record is:  [660, 679, 722, 760, 'Pedestrian']\n",
      "Record is:  [45, 690, 102, 763, 'Pedestrian']\n",
      "Record is:  [721, 649, 802, 724, 'Pedestrian']\n",
      "Record is:  [0, 732, 27, 797, 'Pedestrian']\n",
      "Record is:  [716, 623, 798, 705, 'Pedestrian']\n",
      "2 0 4 1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ground Truth:  3\n",
      "processing time:  0.05207991600036621\n",
      "Record is:  [1377, 199, 1411, 249, 'Pedestrian']\n",
      "Record is:  [1166, 333, 1210, 385, 'Pedestrian']\n",
      "Record is:  [965, 738, 1022, 790, 'Pedestrian']\n",
      "Record is:  [702, 336, 744, 390, 'Pedestrian']\n",
      "Record is:  [310, 799, 346, 848, 'Biker']\n",
      "Record is:  [315, 103, 352, 155, 'Biker']\n",
      "Record is:  [748, 274, 793, 317, 'Pedestrian']\n",
      "Record is:  [1337, 927, 1389, 988, 'Biker']\n",
      "Record is:  [53, 383, 89, 427, 'Pedestrian']\n",
      "Record is:  [966, 739, 1024, 789, 'Biker']\n",
      "8 2 0 6\n",
      "Ground Truth:  15\n",
      "processing time:  0.05224347114562988\n",
      "Record is:  [1345, 965, 1377, 1000, 'Pedestrian']\n",
      "Record is:  [1338, 922, 1382, 960, 'Biker']\n",
      "Record is:  [700, 562, 741, 612, 'Pedestrian']\n",
      "Record is:  [400, 753, 435, 792, 'Pedestrian']\n",
      "Record is:  [1314, 947, 1350, 986, 'Biker']\n",
      "Record is:  [706, 348, 751, 395, 'Pedestrian']\n",
      "Record is:  [979, 927, 1028, 974, 'Pedestrian']\n",
      "Record is:  [1373, 204, 1404, 246, 'Pedestrian']\n",
      "Record is:  [691, 694, 728, 739, 'Pedestrian']\n",
      "Record is:  [100, 1022, 149, 1067, 'Pedestrian']\n",
      "Record is:  [399, 633, 432, 675, 'Pedestrian']\n",
      "Record is:  [275, 947, 310, 979, 'Pedestrian']\n",
      "Record is:  [301, 196, 332, 234, 'Pedestrian']\n",
      "Record is:  [752, 855, 791, 901, 'Pedestrian']\n",
      "Record is:  [785, 294, 818, 332, 'Pedestrian']\n",
      "7 4 4 5\n",
      "Ground Truth:  16\n",
      "processing time:  0.05651974678039551\n",
      "Record is:  [1324, 136, 1373, 174, 'Pedestrian']\n",
      "Record is:  [1330, 107, 1385, 149, 'Pedestrian']\n",
      "Record is:  [1271, 143, 1330, 187, 'Pedestrian']\n",
      "Record is:  [1291, 111, 1338, 151, 'Pedestrian']\n",
      "Record is:  [1284, 86, 1330, 126, 'Pedestrian']\n",
      "Record is:  [1403, 149, 1468, 203, 'Pedestrian']\n",
      "Record is:  [1436, 112, 1500, 163, 'Pedestrian']\n",
      "Record is:  [1351, 912, 1438, 962, 'Pedestrian']\n",
      "Record is:  [1269, 45, 1334, 94, 'Pedestrian']\n",
      "Record is:  [1441, 794, 1516, 847, 'Pedestrian']\n",
      "Record is:  [1339, 954, 1422, 1008, 'Pedestrian']\n",
      "Record is:  [1448, 734, 1508, 779, 'Pedestrian']\n",
      "Record is:  [1202, 71, 1260, 120, 'Pedestrian']\n",
      "Record is:  [982, 199, 1032, 266, 'Pedestrian']\n",
      "13 0 1 0\n",
      "Ground Truth:  13\n",
      "processing time:  0.05222320556640625\n",
      "Record is:  [831, 896, 874, 931, 'Pedestrian']\n",
      "Record is:  [1329, 945, 1374, 986, 'Pedestrian']\n",
      "Record is:  [967, 411, 998, 471, 'Pedestrian']\n",
      "Record is:  [830, 876, 872, 919, 'Pedestrian']\n",
      "Record is:  [827, 856, 862, 897, 'Pedestrian']\n",
      "Record is:  [418, 914, 452, 958, 'Pedestrian']\n",
      "Record is:  [708, 338, 746, 396, 'Pedestrian']\n",
      "Record is:  [843, 864, 880, 904, 'Pedestrian']\n",
      "Record is:  [415, 918, 464, 973, 'Pedestrian']\n",
      "Record is:  [476, 947, 524, 1011, 'Pedestrian']\n",
      "Record is:  [888, 1023, 954, 1071, 'Biker']\n",
      "Record is:  [1328, 941, 1370, 987, 'Biker']\n",
      "Record is:  [390, 352, 415, 397, 'Biker']\n",
      "8 2 3 2\n",
      "Ground Truth:  10\n",
      "processing time:  0.05335593223571777\n",
      "Record is:  [1367, 637, 1395, 680, 'Pedestrian']\n",
      "Record is:  [736, 271, 785, 318, 'Pedestrian']\n",
      "Record is:  [389, 530, 438, 575, 'Biker']\n",
      "Record is:  [652, 453, 706, 509, 'Pedestrian']\n",
      "Record is:  [708, 339, 750, 383, 'Pedestrian']\n",
      "Record is:  [691, 689, 722, 739, 'Pedestrian']\n",
      "Record is:  [783, 283, 828, 333, 'Pedestrian']\n",
      "Record is:  [375, 4, 409, 40, 'Pedestrian']\n",
      "Record is:  [998, 991, 1029, 1029, 'Pedestrian']\n",
      "Record is:  [1384, 635, 1411, 676, 'Pedestrian']\n",
      "Record is:  [1186, 944, 1220, 980, 'Pedestrian']\n",
      "Record is:  [1372, 633, 1407, 684, 'Pedestrian']\n",
      "6 1 5 6\n",
      "Ground Truth:  13\n",
      "processing time:  0.05162405967712402\n",
      "Record is:  [1267, 674, 1304, 731, 'Pedestrian']\n",
      "Record is:  [1077, 525, 1113, 562, 'Pedestrian']\n",
      "Record is:  [800, 472, 856, 511, 'Pedestrian']\n",
      "Record is:  [334, 936, 371, 982, 'Biker']\n",
      "Record is:  [763, 281, 809, 333, 'Pedestrian']\n",
      "Record is:  [694, 339, 738, 385, 'Pedestrian']\n",
      "Record is:  [876, 749, 922, 804, 'Pedestrian']\n",
      "Record is:  [439, 416, 477, 475, 'Biker']\n",
      "Record is:  [1080, 443, 1111, 485, 'Pedestrian']\n",
      "Record is:  [744, 273, 790, 322, 'Pedestrian']\n",
      "Record is:  [1371, 206, 1411, 250, 'Pedestrian']\n",
      "Record is:  [1272, 822, 1308, 851, 'Pedestrian']\n",
      "Record is:  [391, 933, 433, 990, 'Biker']\n",
      "Record is:  [715, 270, 770, 316, 'Pedestrian']\n",
      "Record is:  [442, 417, 477, 464, 'Pedestrian']\n",
      "Record is:  [302, 192, 333, 238, 'Pedestrian']\n",
      "Record is:  [1257, 819, 1311, 864, 'Pedestrian']\n",
      "10 3 4 7\n",
      "Ground Truth:  17\n",
      "processing time:  0.05586433410644531\n",
      "Record is:  [321, 848, 405, 938, 'Biker']\n",
      "Record is:  [123, 716, 184, 794, 'Pedestrian']\n",
      "Record is:  [733, 1152, 784, 1228, 'Pedestrian']\n",
      "3 0 0 0\n",
      "Ground Truth:  3\n",
      "processing time:  0.054075002670288086\n",
      "Record is:  [738, 274, 789, 318, 'Pedestrian']\n",
      "Record is:  [1339, 939, 1379, 984, 'Pedestrian']\n",
      "Record is:  [653, 317, 696, 373, 'Pedestrian']\n",
      "Record is:  [871, 1018, 912, 1069, 'Pedestrian']\n",
      "Record is:  [1371, 204, 1408, 249, 'Pedestrian']\n",
      "Record is:  [262, 607, 287, 652, 'Pedestrian']\n",
      "Record is:  [693, 690, 728, 739, 'Pedestrian']\n",
      "Record is:  [353, 834, 389, 881, 'Biker']\n",
      "Record is:  [1356, 943, 1399, 987, 'Pedestrian']\n",
      "Record is:  [484, 352, 521, 406, 'Pedestrian']\n",
      "Record is:  [279, 694, 306, 741, 'Pedestrian']\n",
      "Record is:  [296, 184, 334, 247, 'Pedestrian']\n",
      "Record is:  [785, 284, 831, 329, 'Pedestrian']\n",
      "Record is:  [351, 585, 380, 626, 'Biker']\n",
      "Record is:  [344, 824, 405, 892, 'Biker']\n",
      "Record is:  [470, 353, 509, 405, 'Pedestrian']\n",
      "Record is:  [347, 583, 395, 635, 'Biker']\n",
      "9 3 5 8\n",
      "Ground Truth:  18\n",
      "processing time:  0.05578136444091797\n",
      "Record is:  [966, 901, 1026, 979, 'Biker']\n",
      "Record is:  [724, 1114, 796, 1169, 'Pedestrian']\n",
      "Record is:  [732, 1148, 794, 1204, 'Pedestrian']\n",
      "3 0 0 0\n",
      "Ground Truth:  3\n",
      "processing time:  0.056120872497558594\n",
      "Record is:  [1181, 1728, 1268, 1827, 'Pedestrian']\n",
      "Record is:  [1088, 722, 1135, 819, 'Pedestrian']\n",
      "2 0 0 0\n",
      "Ground Truth:  2\n",
      "processing time:  0.05221414566040039\n",
      "Record is:  [696, 467, 756, 513, 'Pedestrian']\n",
      "Record is:  [1376, 201, 1405, 249, 'Pedestrian']\n",
      "Record is:  [687, 335, 728, 386, 'Pedestrian']\n",
      "Record is:  [982, 460, 1027, 513, 'Pedestrian']\n",
      "Record is:  [1208, 846, 1237, 888, 'Pedestrian']\n",
      "Record is:  [1329, 612, 1376, 661, 'Pedestrian']\n",
      "Record is:  [762, 293, 808, 337, 'Pedestrian']\n",
      "Record is:  [342, 1007, 387, 1038, 'Biker']\n",
      "Record is:  [1259, 631, 1309, 682, 'Biker']\n",
      "Record is:  [461, 354, 498, 408, 'Pedestrian']\n",
      "8 1 1 8\n",
      "Ground Truth:  17\n",
      "processing time:  0.0577397346496582\n",
      "Record is:  [1327, 144, 1376, 184, 'Pedestrian']\n",
      "Record is:  [1293, 152, 1332, 187, 'Pedestrian']\n",
      "Record is:  [1436, 121, 1490, 164, 'Pedestrian']\n",
      "Record is:  [1412, 145, 1467, 194, 'Pedestrian']\n",
      "Record is:  [1331, 111, 1381, 152, 'Pedestrian']\n",
      "Record is:  [578, 344, 663, 410, 'Pedestrian']\n",
      "Record is:  [406, 358, 479, 418, 'Pedestrian']\n",
      "Record is:  [1406, 186, 1466, 233, 'Pedestrian']\n",
      "Record is:  [1295, 105, 1331, 153, 'Pedestrian']\n",
      "Record is:  [1276, 51, 1333, 103, 'Pedestrian']\n",
      "Record is:  [783, 931, 846, 983, 'Pedestrian']\n",
      "Record is:  [1362, 68, 1410, 123, 'Pedestrian']\n",
      "Record is:  [220, 719, 294, 774, 'Pedestrian']\n",
      "Record is:  [1031, 449, 1119, 519, 'Biker']\n",
      "Record is:  [1453, 437, 1513, 494, 'Pedestrian']\n",
      "Record is:  [1332, 125, 1380, 168, 'Pedestrian']\n",
      "Record is:  [1341, 76, 1385, 123, 'Pedestrian']\n",
      "17 0 0 0\n",
      "Ground Truth:  15\n",
      "processing time:  0.05745053291320801\n",
      "Record is:  [715, 857, 780, 940, 'Biker']\n",
      "Record is:  [1262, 826, 1315, 907, 'Biker']\n",
      "1 0 1 0\n",
      "Ground Truth:  1\n",
      "processing time:  0.05736589431762695\n",
      "Record is:  [919, 983, 1004, 1087, 'Biker']\n",
      "Record is:  [1074, 1044, 1182, 1130, 'Biker']\n",
      "Record is:  [990, 820, 1038, 913, 'Biker']\n",
      "Record is:  [1056, 1038, 1141, 1133, 'Biker']\n",
      "2 1 1 1\n",
      "Ground Truth:  3\n",
      "processing time:  0.05230283737182617\n",
      "Record is:  [1380, 207, 1405, 246, 'Pedestrian']\n",
      "Record is:  [1372, 924, 1411, 962, 'Pedestrian']\n",
      "Record is:  [923, 691, 966, 748, 'Pedestrian']\n",
      "Record is:  [1314, 941, 1358, 981, 'Pedestrian']\n",
      "Record is:  [1221, 915, 1265, 963, 'Biker']\n",
      "Record is:  [684, 343, 733, 395, 'Pedestrian']\n",
      "Record is:  [442, 912, 485, 974, 'Pedestrian']\n",
      "Record is:  [223, 336, 246, 373, 'Pedestrian']\n",
      "Record is:  [464, 352, 505, 413, 'Pedestrian']\n",
      "6 1 2 5\n",
      "Ground Truth:  12\n",
      "processing time:  0.053069353103637695\n",
      "Record is:  [1327, 1183, 1360, 1245, 'Skater']\n",
      "Record is:  [195, 1590, 242, 1687, 'Biker']\n",
      "Record is:  [804, 1024, 880, 1113, 'Skater']\n",
      "Record is:  [783, 1011, 878, 1118, 'Biker']\n",
      "Record is:  [1311, 1173, 1366, 1239, 'Skater']\n",
      "4 1 0 0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ground Truth:  3\n",
      "processing time:  0.05251336097717285\n",
      "Record is:  [694, 335, 736, 387, 'Pedestrian']\n",
      "Record is:  [1009, 915, 1047, 957, 'Pedestrian']\n",
      "Record is:  [273, 575, 303, 623, 'Pedestrian']\n",
      "Record is:  [10, 951, 38, 998, 'Pedestrian']\n",
      "Record is:  [681, 974, 726, 1033, 'Biker']\n",
      "Record is:  [204, 698, 235, 753, 'Pedestrian']\n",
      "Record is:  [98, 1019, 153, 1072, 'Pedestrian']\n",
      "Record is:  [104, 818, 142, 872, 'Pedestrian']\n",
      "5 2 1 8\n",
      "Ground Truth:  15\n",
      "processing time:  0.05601024627685547\n",
      "Record is:  [279, 680, 336, 769, 'Pedestrian']\n",
      "Record is:  [1216, 823, 1270, 918, 'Pedestrian']\n",
      "Record is:  [289, 760, 344, 844, 'Pedestrian']\n",
      "3 0 0 0\n",
      "Ground Truth:  3\n",
      "processing time:  0.05608534812927246\n",
      "Record is:  [936, 854, 997, 923, 'Biker']\n",
      "Record is:  [438, 984, 510, 1082, 'Biker']\n",
      "Record is:  [0, 1143, 30, 1223, 'Pedestrian']\n",
      "Record is:  [715, 849, 768, 920, 'Biker']\n",
      "4 0 0 0\n",
      "Ground Truth:  4\n",
      "processing time:  0.05590200424194336\n",
      "Record is:  [1047, 843, 1097, 922, 'Biker']\n",
      "Record is:  [85, 979, 148, 1074, 'Biker']\n",
      "Record is:  [1269, 1135, 1297, 1180, 'Pedestrian']\n",
      "Record is:  [1271, 1108, 1311, 1149, 'Pedestrian']\n",
      "Record is:  [1296, 845, 1321, 915, 'Biker']\n",
      "5 0 0 0\n",
      "Ground Truth:  5\n",
      "processing time:  0.05176663398742676\n",
      "Record is:  [691, 688, 726, 742, 'Pedestrian']\n",
      "Record is:  [459, 358, 508, 418, 'Pedestrian']\n",
      "Record is:  [97, 740, 129, 771, 'Pedestrian']\n",
      "Record is:  [1025, 700, 1067, 750, 'Biker']\n",
      "Record is:  [269, 942, 309, 977, 'Pedestrian']\n",
      "1 0 4 9\n",
      "Ground Truth:  10\n",
      "processing time:  0.05184125900268555\n",
      "Record is:  [1208, 722, 1246, 754, 'Pedestrian']\n",
      "Record is:  [1374, 203, 1409, 246, 'Pedestrian']\n",
      "Record is:  [733, 872, 777, 923, 'Pedestrian']\n",
      "Record is:  [636, 346, 680, 403, 'Pedestrian']\n",
      "Record is:  [309, 792, 349, 853, 'Biker']\n",
      "Record is:  [1030, 539, 1073, 586, 'Pedestrian']\n",
      "Record is:  [696, 688, 732, 737, 'Pedestrian']\n",
      "Record is:  [734, 266, 787, 313, 'Pedestrian']\n",
      "5 1 2 8\n",
      "Ground Truth:  14\n",
      "processing time:  0.0576176643371582\n",
      "Record is:  [1290, 151, 1332, 189, 'Pedestrian']\n",
      "Record is:  [1330, 143, 1376, 184, 'Pedestrian']\n",
      "Record is:  [1402, 135, 1462, 185, 'Pedestrian']\n",
      "Record is:  [1273, 51, 1332, 104, 'Pedestrian']\n",
      "Record is:  [737, 933, 808, 989, 'Pedestrian']\n",
      "Record is:  [581, 344, 668, 412, 'Pedestrian']\n",
      "Record is:  [404, 354, 483, 417, 'Pedestrian']\n",
      "Record is:  [1333, 110, 1376, 150, 'Pedestrian']\n",
      "Record is:  [1324, 81, 1371, 121, 'Pedestrian']\n",
      "Record is:  [1435, 120, 1500, 163, 'Pedestrian']\n",
      "Record is:  [1386, 456, 1480, 530, 'Pedestrian']\n",
      "Record is:  [291, 708, 359, 785, 'Pedestrian']\n",
      "Record is:  [977, 446, 1045, 522, 'Pedestrian']\n",
      "Record is:  [1295, 108, 1330, 149, 'Pedestrian']\n",
      "13 1 0 1\n",
      "Ground Truth:  15\n",
      "processing time:  0.058287620544433594\n",
      "Record is:  [1324, 141, 1372, 182, 'Pedestrian']\n",
      "Record is:  [1288, 144, 1341, 183, 'Pedestrian']\n",
      "Record is:  [1291, 120, 1336, 154, 'Pedestrian']\n",
      "Record is:  [1252, 254, 1300, 287, 'Pedestrian']\n",
      "Record is:  [1333, 112, 1372, 149, 'Pedestrian']\n",
      "Record is:  [1432, 112, 1496, 158, 'Pedestrian']\n",
      "Record is:  [1413, 148, 1468, 195, 'Pedestrian']\n",
      "Record is:  [1274, 84, 1334, 123, 'Pedestrian']\n",
      "Record is:  [1203, 69, 1265, 120, 'Pedestrian']\n",
      "Record is:  [1240, 219, 1291, 265, 'Pedestrian']\n",
      "Record is:  [1553, 890, 1607, 921, 'Pedestrian']\n",
      "Record is:  [1293, 803, 1381, 848, 'Pedestrian']\n",
      "Record is:  [423, 923, 509, 1007, 'Pedestrian']\n",
      "Record is:  [1278, 42, 1332, 93, 'Pedestrian']\n",
      "Record is:  [1227, 227, 1278, 266, 'Pedestrian']\n",
      "Record is:  [1231, 933, 1333, 978, 'Biker']\n",
      "Record is:  [1269, 805, 1365, 863, 'Pedestrian']\n",
      "Record is:  [1456, 741, 1513, 777, 'Pedestrian']\n",
      "17 0 1 0\n",
      "Ground Truth:  15\n",
      "processing time:  0.05663633346557617\n",
      "Record is:  [1286, 149, 1336, 192, 'Pedestrian']\n",
      "Record is:  [1331, 113, 1374, 149, 'Pedestrian']\n",
      "Record is:  [1329, 146, 1374, 181, 'Pedestrian']\n",
      "Record is:  [1278, 54, 1329, 94, 'Pedestrian']\n",
      "Record is:  [1288, 115, 1331, 153, 'Pedestrian']\n",
      "Record is:  [1443, 108, 1515, 161, 'Pedestrian']\n",
      "Record is:  [587, 364, 639, 409, 'Pedestrian']\n",
      "Record is:  [1215, 894, 1281, 933, 'Pedestrian']\n",
      "Record is:  [1411, 143, 1460, 194, 'Pedestrian']\n",
      "Record is:  [1222, 852, 1291, 896, 'Pedestrian']\n",
      "Record is:  [1463, 736, 1518, 776, 'Pedestrian']\n",
      "Record is:  [1286, 90, 1329, 125, 'Pedestrian']\n",
      "11 0 1 0\n",
      "Ground Truth:  11\n",
      "processing time:  0.0602874755859375\n",
      "Record is:  [1323, 139, 1378, 179, 'Pedestrian']\n",
      "Record is:  [1335, 108, 1381, 149, 'Pedestrian']\n",
      "Record is:  [1289, 114, 1334, 152, 'Pedestrian']\n",
      "Record is:  [1280, 142, 1340, 183, 'Pedestrian']\n",
      "Record is:  [1273, 85, 1336, 121, 'Pedestrian']\n",
      "Record is:  [1285, 38, 1343, 94, 'Pedestrian']\n",
      "Record is:  [693, 816, 771, 867, 'Pedestrian']\n",
      "Record is:  [1205, 69, 1264, 121, 'Pedestrian']\n",
      "Record is:  [1452, 53, 1505, 103, 'Pedestrian']\n",
      "Record is:  [703, 916, 801, 963, 'Biker']\n",
      "Record is:  [1465, 93, 1515, 131, 'Pedestrian']\n",
      "Record is:  [1901, 931, 1974, 963, 'Pedestrian']\n",
      "Record is:  [1432, 111, 1497, 164, 'Pedestrian']\n",
      "Record is:  [1443, 733, 1503, 778, 'Pedestrian']\n",
      "Record is:  [1914, 965, 1975, 1002, 'Pedestrian']\n",
      "Record is:  [1403, 131, 1486, 188, 'Pedestrian']\n",
      "Record is:  [1409, 140, 1478, 202, 'Biker']\n",
      "Record is:  [1580, 799, 1674, 848, 'Pedestrian']\n",
      "Record is:  [1433, 112, 1495, 163, 'Biker']\n",
      "16 2 1 0\n",
      "Ground Truth:  16\n",
      "processing time:  0.055108070373535156\n",
      "Record is:  [705, 338, 746, 392, 'Pedestrian']\n",
      "Record is:  [888, 864, 937, 919, 'Pedestrian']\n",
      "Record is:  [1289, 1008, 1340, 1055, 'Pedestrian']\n",
      "Record is:  [891, 852, 930, 895, 'Pedestrian']\n",
      "Record is:  [387, 548, 437, 601, 'Biker']\n",
      "Record is:  [1029, 401, 1069, 461, 'Pedestrian']\n",
      "Record is:  [736, 270, 787, 314, 'Pedestrian']\n",
      "Record is:  [890, 897, 931, 934, 'Pedestrian']\n",
      "Record is:  [364, 966, 408, 1005, 'Pedestrian']\n",
      "Record is:  [358, 965, 414, 1015, 'Biker']\n",
      "6 2 2 3\n",
      "Ground Truth:  10\n",
      "processing time:  0.0614621639251709\n",
      "Record is:  [1280, 150, 1331, 193, 'Pedestrian']\n",
      "Record is:  [1328, 108, 1375, 151, 'Pedestrian']\n",
      "Record is:  [1321, 145, 1376, 185, 'Pedestrian']\n",
      "Record is:  [1268, 48, 1332, 98, 'Pedestrian']\n",
      "Record is:  [1425, 118, 1491, 160, 'Pedestrian']\n",
      "Record is:  [1409, 151, 1464, 197, 'Pedestrian']\n",
      "Record is:  [1286, 111, 1328, 155, 'Pedestrian']\n",
      "Record is:  [1120, 799, 1192, 850, 'Biker']\n",
      "Record is:  [575, 356, 646, 413, 'Pedestrian']\n",
      "Record is:  [414, 357, 493, 416, 'Pedestrian']\n",
      "Record is:  [1404, 81, 1468, 127, 'Pedestrian']\n",
      "Record is:  [577, 938, 644, 992, 'Biker']\n",
      "Record is:  [1098, 783, 1196, 862, 'Biker']\n",
      "Record is:  [1400, 69, 1464, 112, 'Pedestrian']\n",
      "14 0 0 0\n",
      "Ground Truth:  13\n",
      "processing time:  0.059848785400390625\n",
      "Record is:  [1329, 145, 1375, 183, 'Pedestrian']\n",
      "Record is:  [1286, 151, 1329, 187, 'Pedestrian']\n",
      "Record is:  [1330, 111, 1376, 150, 'Pedestrian']\n",
      "Record is:  [1411, 146, 1465, 195, 'Pedestrian']\n",
      "Record is:  [1436, 116, 1494, 163, 'Pedestrian']\n",
      "Record is:  [1276, 55, 1327, 98, 'Pedestrian']\n",
      "Record is:  [1293, 111, 1328, 151, 'Pedestrian']\n",
      "Record is:  [671, 960, 722, 1005, 'Pedestrian']\n",
      "Record is:  [1320, 88, 1374, 131, 'Pedestrian']\n",
      "Record is:  [1416, 8, 1463, 76, 'Pedestrian']\n",
      "Record is:  [402, 361, 488, 429, 'Pedestrian']\n",
      "Record is:  [579, 349, 658, 412, 'Pedestrian']\n",
      "Record is:  [1334, 506, 1390, 557, 'Pedestrian']\n",
      "Record is:  [819, 455, 907, 546, 'Biker']\n",
      "14 0 0 1\n",
      "Ground Truth:  15\n",
      "processing time:  0.05950450897216797\n",
      "Record is:  [1264, 1623, 1299, 1704, 'Pedestrian']\n",
      "Record is:  [1122, 964, 1185, 1047, 'Biker']\n",
      "Record is:  [798, 871, 850, 948, 'Biker']\n",
      "Record is:  [933, 1009, 979, 1099, 'Pedestrian']\n",
      "4 0 0 0\n",
      "Ground Truth:  4\n",
      "processing time:  0.05510854721069336\n",
      "Record is:  [691, 688, 721, 738, 'Pedestrian']\n",
      "Record is:  [711, 316, 748, 366, 'Pedestrian']\n",
      "Record is:  [458, 357, 504, 414, 'Pedestrian']\n",
      "Record is:  [700, 326, 738, 375, 'Pedestrian']\n",
      "Record is:  [301, 197, 333, 237, 'Pedestrian']\n",
      "Record is:  [6, 439, 31, 481, 'Pedestrian']\n",
      "Record is:  [915, 1003, 964, 1062, 'Biker']\n",
      "4 0 3 5\n",
      "Ground Truth:  8\n",
      "processing time:  0.06333303451538086\n",
      "Record is:  [636, 353, 684, 406, 'Pedestrian']\n",
      "Record is:  [786, 292, 834, 337, 'Pedestrian']\n",
      "Record is:  [1095, 517, 1139, 565, 'Pedestrian']\n",
      "Record is:  [277, 110, 322, 159, 'Biker']\n",
      "Record is:  [308, 798, 345, 854, 'Biker']\n",
      "Record is:  [736, 269, 784, 315, 'Pedestrian']\n",
      "Record is:  [1376, 199, 1407, 250, 'Pedestrian']\n",
      "Record is:  [795, 834, 827, 874, 'Pedestrian']\n",
      "Record is:  [346, 960, 400, 1021, 'Biker']\n",
      "Record is:  [528, 993, 583, 1054, 'Biker']\n",
      "Record is:  [1166, 754, 1215, 811, 'Pedestrian']\n",
      "Record is:  [458, 357, 503, 411, 'Pedestrian']\n",
      "Record is:  [699, 684, 728, 737, 'Pedestrian']\n",
      "8 2 3 5\n",
      "Ground Truth:  15\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "processing time:  0.06256246566772461\n",
      "Record is:  [1320, 144, 1378, 185, 'Pedestrian']\n",
      "Record is:  [1273, 150, 1329, 192, 'Pedestrian']\n",
      "Record is:  [1432, 119, 1491, 162, 'Pedestrian']\n",
      "Record is:  [1329, 108, 1374, 153, 'Pedestrian']\n",
      "Record is:  [1407, 145, 1462, 191, 'Pedestrian']\n",
      "Record is:  [1265, 47, 1335, 101, 'Pedestrian']\n",
      "Record is:  [400, 351, 488, 417, 'Pedestrian']\n",
      "Record is:  [1274, 115, 1320, 160, 'Pedestrian']\n",
      "Record is:  [578, 339, 675, 409, 'Pedestrian']\n",
      "Record is:  [578, 794, 640, 838, 'Biker']\n",
      "Record is:  [1355, 936, 1472, 1010, 'Biker']\n",
      "Record is:  [1274, 131, 1325, 178, 'Pedestrian']\n",
      "12 0 0 0\n",
      "Ground Truth:  11\n",
      "processing time:  0.06735086441040039\n",
      "Record is:  [1171, 809, 1239, 934, 'Biker']\n",
      "Record is:  [504, 837, 599, 935, 'Biker']\n",
      "Record is:  [85, 827, 167, 946, 'Biker']\n",
      "3 0 0 0\n",
      "Ground Truth:  3\n",
      "processing time:  0.06448650360107422\n",
      "Record is:  [1376, 204, 1413, 249, 'Pedestrian']\n",
      "Record is:  [661, 327, 700, 377, 'Pedestrian']\n",
      "Record is:  [1137, 902, 1173, 943, 'Pedestrian']\n",
      "Record is:  [73, 638, 113, 691, 'Pedestrian']\n",
      "Record is:  [742, 269, 795, 318, 'Pedestrian']\n",
      "Record is:  [170, 762, 209, 809, 'Pedestrian']\n",
      "Record is:  [277, 224, 309, 267, 'Biker']\n",
      "Record is:  [306, 340, 338, 402, 'Biker']\n",
      "Record is:  [277, 577, 306, 617, 'Pedestrian']\n",
      "Record is:  [1169, 1029, 1213, 1065, 'Pedestrian']\n",
      "Record is:  [462, 342, 497, 398, 'Pedestrian']\n",
      "Record is:  [102, 1023, 149, 1072, 'Pedestrian']\n",
      "Record is:  [453, 545, 483, 589, 'Pedestrian']\n",
      "9 1 3 8\n",
      "Ground Truth:  18\n",
      "processing time:  0.06203508377075195\n",
      "Record is:  [511, 912, 561, 993, 'Pedestrian']\n",
      "Record is:  [377, 1128, 422, 1208, 'Pedestrian']\n",
      "2 0 0 0\n",
      "Ground Truth:  2\n",
      "processing time:  0.055420875549316406\n",
      "Record is:  [1102, 844, 1135, 878, 'Pedestrian']\n",
      "Record is:  [1224, 311, 1270, 364, 'Pedestrian']\n",
      "Record is:  [1098, 871, 1129, 902, 'Pedestrian']\n",
      "Record is:  [1103, 900, 1137, 932, 'Pedestrian']\n",
      "Record is:  [186, 1025, 226, 1062, 'Pedestrian']\n",
      "Record is:  [677, 290, 715, 344, 'Pedestrian']\n",
      "Record is:  [1099, 886, 1133, 919, 'Pedestrian']\n",
      "Record is:  [1090, 845, 1125, 880, 'Pedestrian']\n",
      "Record is:  [38, 990, 88, 1030, 'Pedestrian']\n",
      "Record is:  [691, 684, 724, 734, 'Pedestrian']\n",
      "Record is:  [711, 337, 744, 385, 'Pedestrian']\n",
      "8 1 2 1\n",
      "Ground Truth:  9\n",
      "processing time:  0.057447195053100586\n",
      "Record is:  [207, 952, 259, 1056, 'Pedestrian']\n",
      "Record is:  [1377, 1066, 1411, 1147, 'Pedestrian']\n",
      "Record is:  [425, 1002, 529, 1118, 'Biker']\n",
      "Record is:  [403, 321, 461, 414, 'Pedestrian']\n",
      "Record is:  [970, 1343, 1063, 1448, 'Biker']\n",
      "Record is:  [755, 1611, 817, 1719, 'Biker']\n",
      "Record is:  [721, 1575, 815, 1723, 'Biker']\n",
      "Record is:  [462, 1036, 520, 1116, 'Biker']\n",
      "Record is:  [1363, 1049, 1420, 1139, 'Pedestrian']\n",
      "Record is:  [120, 1279, 198, 1390, 'Biker']\n",
      "10 0 0 7\n",
      "Ground Truth:  14\n",
      "processing time:  0.05964183807373047\n",
      "Record is:  [1106, 1187, 1151, 1263, 'Pedestrian']\n",
      "Record is:  [869, 691, 943, 776, 'Biker']\n",
      "Record is:  [1245, 808, 1307, 903, 'Biker']\n",
      "Record is:  [1215, 1126, 1247, 1208, 'Pedestrian']\n",
      "Record is:  [1227, 819, 1274, 908, 'Biker']\n",
      "Record is:  [870, 1832, 921, 1903, 'Biker']\n",
      "Record is:  [1232, 1148, 1265, 1223, 'Pedestrian']\n",
      "Record is:  [1221, 1149, 1254, 1223, 'Pedestrian']\n",
      "5 1 2 0\n",
      "Ground Truth:  4\n",
      "processing time:  0.060141801834106445\n",
      "Record is:  [1327, 143, 1364, 180, 'Pedestrian']\n",
      "Record is:  [1328, 114, 1371, 148, 'Pedestrian']\n",
      "Record is:  [1438, 113, 1490, 156, 'Pedestrian']\n",
      "Record is:  [1293, 125, 1334, 154, 'Pedestrian']\n",
      "Record is:  [1290, 149, 1340, 182, 'Pedestrian']\n",
      "Record is:  [1413, 152, 1457, 192, 'Pedestrian']\n",
      "Record is:  [1276, 85, 1332, 127, 'Pedestrian']\n",
      "Record is:  [1271, 48, 1332, 94, 'Pedestrian']\n",
      "Record is:  [1207, 68, 1272, 116, 'Pedestrian']\n",
      "Record is:  [1052, 829, 1155, 883, 'Pedestrian']\n",
      "Record is:  [200, 1031, 271, 1086, 'Pedestrian']\n",
      "Record is:  [1285, 116, 1335, 147, 'Pedestrian']\n",
      "Record is:  [1066, 374, 1120, 415, 'Pedestrian']\n",
      "Record is:  [1449, 742, 1502, 777, 'Pedestrian']\n",
      "Record is:  [1080, 414, 1121, 448, 'Pedestrian']\n",
      "Record is:  [1720, 935, 1807, 976, 'Biker']\n",
      "15 0 1 0\n",
      "Ground Truth:  14\n",
      "processing time:  0.0649569034576416\n",
      "Record is:  [204, 806, 275, 925, 'Biker']\n",
      "Record is:  [293, 1107, 375, 1163, 'Pedestrian']\n",
      "Record is:  [313, 1144, 378, 1190, 'Pedestrian']\n",
      "3 0 0 0\n",
      "Ground Truth:  3\n",
      "processing time:  0.055989980697631836\n",
      "Record is:  [461, 361, 500, 407, 'Pedestrian']\n",
      "Record is:  [695, 335, 738, 383, 'Pedestrian']\n",
      "Record is:  [1377, 205, 1411, 249, 'Pedestrian']\n",
      "Record is:  [454, 541, 489, 582, 'Pedestrian']\n",
      "Record is:  [1060, 870, 1087, 911, 'Pedestrian']\n",
      "Record is:  [728, 979, 772, 1032, 'Biker']\n",
      "Record is:  [263, 955, 304, 1006, 'Pedestrian']\n",
      "Record is:  [208, 486, 258, 536, 'Pedestrian']\n",
      "Record is:  [321, 567, 358, 613, 'Pedestrian']\n",
      "Record is:  [1072, 871, 1100, 910, 'Pedestrian']\n",
      "Record is:  [1060, 863, 1103, 917, 'Pedestrian']\n",
      "Record is:  [463, 657, 529, 721, 'Bus']\n",
      "5 1 6 8\n",
      "Ground Truth:  14\n",
      "processing time:  0.05637621879577637\n",
      "Record is:  [1295, 721, 1327, 763, 'Pedestrian']\n",
      "Record is:  [1295, 1032, 1344, 1069, 'Pedestrian']\n",
      "Record is:  [1374, 203, 1409, 246, 'Pedestrian']\n",
      "Record is:  [212, 489, 247, 530, 'Pedestrian']\n",
      "Record is:  [696, 688, 730, 738, 'Pedestrian']\n",
      "Record is:  [297, 471, 336, 534, 'Biker']\n",
      "Record is:  [669, 345, 710, 384, 'Pedestrian']\n",
      "Record is:  [282, 462, 306, 511, 'Pedestrian']\n",
      "Record is:  [267, 168, 296, 202, 'Pedestrian']\n",
      "Record is:  [743, 259, 796, 324, 'Pedestrian']\n",
      "Record is:  [310, 429, 345, 481, 'Biker']\n",
      "6 3 2 5\n",
      "Ground Truth:  14\n",
      "processing time:  0.05502510070800781\n",
      "Record is:  [730, 471, 786, 513, 'Pedestrian']\n",
      "Record is:  [1375, 198, 1406, 251, 'Pedestrian']\n",
      "Record is:  [337, 981, 381, 1029, 'Biker']\n",
      "Record is:  [1308, 635, 1345, 677, 'Pedestrian']\n",
      "Record is:  [685, 334, 722, 379, 'Pedestrian']\n",
      "Record is:  [1215, 833, 1263, 882, 'Pedestrian']\n",
      "Record is:  [673, 914, 724, 972, 'Pedestrian']\n",
      "Record is:  [436, 357, 471, 404, 'Pedestrian']\n",
      "Record is:  [1014, 451, 1061, 503, 'Pedestrian']\n",
      "Record is:  [699, 931, 742, 981, 'Pedestrian']\n",
      "Record is:  [458, 361, 506, 415, 'Pedestrian']\n",
      "Record is:  [721, 272, 770, 315, 'Pedestrian']\n",
      "Record is:  [1351, 575, 1392, 623, 'Pedestrian']\n",
      "Record is:  [444, 358, 486, 412, 'Pedestrian']\n",
      "8 3 3 7\n",
      "Ground Truth:  18\n",
      "processing time:  0.054170846939086914\n",
      "Record is:  [681, 328, 721, 382, 'Pedestrian']\n",
      "Record is:  [416, 331, 449, 371, 'Pedestrian']\n",
      "Record is:  [1394, 401, 1420, 456, 'Pedestrian']\n",
      "Record is:  [380, 36, 424, 84, 'Pedestrian']\n",
      "Record is:  [1374, 206, 1408, 251, 'Pedestrian']\n",
      "Record is:  [692, 690, 726, 734, 'Pedestrian']\n",
      "Record is:  [283, 316, 324, 353, 'Biker']\n",
      "2 2 3 6\n",
      "Ground Truth:  12\n",
      "processing time:  0.05660128593444824\n",
      "Record is:  [310, 798, 350, 854, 'Biker']\n",
      "Record is:  [631, 349, 677, 409, 'Pedestrian']\n",
      "Record is:  [1071, 529, 1110, 576, 'Biker']\n",
      "Record is:  [355, 873, 391, 923, 'Pedestrian']\n",
      "Record is:  [1187, 736, 1234, 791, 'Pedestrian']\n",
      "Record is:  [1375, 203, 1410, 246, 'Pedestrian']\n",
      "Record is:  [738, 270, 790, 317, 'Pedestrian']\n",
      "Record is:  [1185, 740, 1228, 785, 'Biker']\n",
      "Record is:  [767, 856, 802, 904, 'Pedestrian']\n",
      "Record is:  [1071, 529, 1110, 577, 'Pedestrian']\n",
      "Record is:  [227, 30, 278, 85, 'Pedestrian']\n",
      "6 4 1 6\n",
      "Ground Truth:  14\n",
      "processing time:  0.05528616905212402\n",
      "Record is:  [1015, 1084, 1076, 1179, 'Biker']\n",
      "Record is:  [463, 1055, 525, 1126, 'Biker']\n",
      "2 0 0 0\n",
      "Ground Truth:  2\n",
      "processing time:  0.05961966514587402\n",
      "Record is:  [1334, 108, 1384, 150, 'Pedestrian']\n",
      "Record is:  [1289, 114, 1335, 152, 'Pedestrian']\n",
      "Record is:  [1323, 137, 1377, 177, 'Pedestrian']\n",
      "Record is:  [1275, 87, 1338, 122, 'Pedestrian']\n",
      "Record is:  [1277, 142, 1337, 185, 'Pedestrian']\n",
      "Record is:  [1550, 790, 1659, 854, 'Pedestrian']\n",
      "Record is:  [1435, 106, 1498, 164, 'Pedestrian']\n",
      "Record is:  [1405, 143, 1473, 204, 'Pedestrian']\n",
      "Record is:  [1775, 956, 1859, 1019, 'Pedestrian']\n",
      "Record is:  [324, 928, 420, 1006, 'Biker']\n",
      "Record is:  [1359, 277, 1461, 329, 'Pedestrian']\n",
      "Record is:  [1283, 38, 1338, 94, 'Pedestrian']\n",
      "Record is:  [1204, 68, 1264, 118, 'Pedestrian']\n",
      "Record is:  [1447, 733, 1517, 780, 'Pedestrian']\n",
      "Record is:  [880, 789, 959, 872, 'Pedestrian']\n",
      "Record is:  [1767, 774, 1855, 842, 'Pedestrian']\n",
      "Record is:  [1393, 314, 1438, 355, 'Pedestrian']\n",
      "15 0 2 1\n",
      "Ground Truth:  16\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "processing time:  0.05893588066101074\n",
      "Record is:  [1289, 149, 1328, 188, 'Pedestrian']\n",
      "Record is:  [1326, 148, 1380, 185, 'Pedestrian']\n",
      "Record is:  [1427, 114, 1494, 165, 'Pedestrian']\n",
      "Record is:  [1333, 111, 1377, 149, 'Pedestrian']\n",
      "Record is:  [1282, 83, 1331, 124, 'Pedestrian']\n",
      "Record is:  [1286, 116, 1339, 156, 'Pedestrian']\n",
      "Record is:  [1407, 139, 1474, 197, 'Pedestrian']\n",
      "Record is:  [371, 770, 441, 816, 'Pedestrian']\n",
      "Record is:  [1270, 51, 1329, 94, 'Pedestrian']\n",
      "Record is:  [580, 352, 648, 418, 'Pedestrian']\n",
      "Record is:  [382, 821, 445, 868, 'Pedestrian']\n",
      "Record is:  [1557, 893, 1642, 980, 'Biker']\n",
      "Record is:  [1239, 814, 1323, 862, 'Pedestrian']\n",
      "Record is:  [417, 367, 479, 416, 'Pedestrian']\n",
      "Record is:  [926, 819, 1016, 882, 'Biker']\n",
      "Record is:  [1459, 738, 1510, 776, 'Pedestrian']\n",
      "Record is:  [1554, 894, 1642, 986, 'Pedestrian']\n",
      "15 1 1 0\n",
      "Ground Truth:  15\n",
      "processing time:  0.05468392372131348\n",
      "Record is:  [687, 348, 735, 400, 'Pedestrian']\n",
      "Record is:  [1155, 580, 1190, 622, 'Pedestrian']\n",
      "Record is:  [1374, 208, 1409, 249, 'Pedestrian']\n",
      "Record is:  [429, 642, 469, 685, 'Pedestrian']\n",
      "Record is:  [256, 137, 308, 184, 'Biker']\n",
      "Record is:  [1348, 972, 1391, 1017, 'Pedestrian']\n",
      "Record is:  [730, 266, 799, 317, 'Pedestrian']\n",
      "Record is:  [689, 1005, 747, 1065, 'Biker']\n",
      "Record is:  [300, 195, 331, 244, 'Pedestrian']\n",
      "Record is:  [224, 489, 256, 533, 'Pedestrian']\n",
      "Record is:  [426, 616, 463, 663, 'Pedestrian']\n",
      "Record is:  [692, 688, 728, 732, 'Pedestrian']\n",
      "Record is:  [305, 999, 349, 1031, 'Pedestrian']\n",
      "6 3 4 5\n",
      "Ground Truth:  13\n",
      "processing time:  0.05829262733459473\n",
      "Record is:  [268, 974, 336, 1064, 'Biker']\n",
      "Record is:  [886, 850, 936, 926, 'Biker']\n",
      "Record is:  [1122, 839, 1177, 919, 'Biker']\n",
      "3 0 0 0\n",
      "Ground Truth:  3\n",
      "processing time:  0.057975053787231445\n",
      "Record is:  [682, 1144, 732, 1242, 'Pedestrian']\n",
      "Record is:  [749, 735, 797, 846, 'Pedestrian']\n",
      "2 0 0 0\n",
      "Ground Truth:  2\n",
      "processing time:  0.0589902400970459\n",
      "Record is:  [1436, 120, 1493, 165, 'Pedestrian']\n",
      "Record is:  [1277, 110, 1325, 153, 'Pedestrian']\n",
      "Record is:  [1320, 144, 1375, 187, 'Pedestrian']\n",
      "Record is:  [1407, 148, 1465, 201, 'Pedestrian']\n",
      "Record is:  [1270, 148, 1329, 189, 'Pedestrian']\n",
      "Record is:  [1334, 109, 1377, 152, 'Pedestrian']\n",
      "Record is:  [1269, 47, 1333, 97, 'Pedestrian']\n",
      "Record is:  [1189, 745, 1309, 825, 'Pedestrian']\n",
      "Record is:  [408, 349, 508, 418, 'Pedestrian']\n",
      "Record is:  [1253, 295, 1320, 351, 'Pedestrian']\n",
      "Record is:  [575, 335, 674, 413, 'Pedestrian']\n",
      "Record is:  [1224, 267, 1287, 336, 'Pedestrian']\n",
      "Record is:  [1663, 329, 1714, 371, 'Pedestrian']\n",
      "Record is:  [1659, 315, 1707, 360, 'Pedestrian']\n",
      "12 0 2 0\n",
      "Ground Truth:  12\n",
      "processing time:  0.05935049057006836\n",
      "Record is:  [1329, 145, 1376, 184, 'Pedestrian']\n",
      "Record is:  [1293, 106, 1331, 156, 'Pedestrian']\n",
      "Record is:  [1434, 118, 1493, 164, 'Pedestrian']\n",
      "Record is:  [1336, 111, 1380, 151, 'Pedestrian']\n",
      "Record is:  [1415, 142, 1465, 198, 'Pedestrian']\n",
      "Record is:  [1294, 150, 1329, 185, 'Pedestrian']\n",
      "Record is:  [580, 345, 663, 411, 'Pedestrian']\n",
      "Record is:  [413, 359, 481, 418, 'Pedestrian']\n",
      "Record is:  [569, 938, 641, 996, 'Pedestrian']\n",
      "Record is:  [1278, 52, 1327, 101, 'Pedestrian']\n",
      "Record is:  [1326, 75, 1374, 124, 'Pedestrian']\n",
      "Record is:  [544, 634, 597, 716, 'Pedestrian']\n",
      "Record is:  [692, 486, 776, 573, 'Biker']\n",
      "Record is:  [1382, 979, 1433, 1019, 'Pedestrian']\n",
      "Record is:  [1292, 86, 1334, 132, 'Pedestrian']\n",
      "Record is:  [1248, 537, 1313, 596, 'Pedestrian']\n",
      "15 0 1 0\n",
      "Ground Truth:  14\n",
      "processing time:  0.056615352630615234\n",
      "Record is:  [671, 1051, 767, 1136, 'Biker']\n",
      "Record is:  [970, 1363, 1041, 1464, 'Biker']\n",
      "Record is:  [896, 1279, 978, 1389, 'Biker']\n",
      "Record is:  [208, 954, 256, 1056, 'Pedestrian']\n",
      "Record is:  [637, 722, 695, 821, 'Biker']\n",
      "Record is:  [1308, 1083, 1345, 1154, 'Pedestrian']\n",
      "Record is:  [1032, 1425, 1093, 1539, 'Biker']\n",
      "Record is:  [434, 359, 506, 452, 'Biker']\n",
      "Record is:  [159, 1436, 205, 1521, 'Pedestrian']\n",
      "Record is:  [127, 1280, 204, 1376, 'Biker']\n",
      "Record is:  [1289, 1052, 1354, 1153, 'Pedestrian']\n",
      "Record is:  [895, 1550, 957, 1627, 'Biker']\n",
      "Record is:  [415, 370, 481, 455, 'Biker']\n",
      "Record is:  [422, 397, 449, 447, 'Pedestrian']\n",
      "13 0 1 2\n",
      "Ground Truth:  13\n",
      "processing time:  0.05939960479736328\n",
      "Record is:  [1331, 110, 1373, 149, 'Pedestrian']\n",
      "Record is:  [1285, 149, 1331, 184, 'Pedestrian']\n",
      "Record is:  [1330, 137, 1366, 173, 'Pedestrian']\n",
      "Record is:  [1289, 114, 1328, 151, 'Pedestrian']\n",
      "Record is:  [1267, 65, 1321, 106, 'Pedestrian']\n",
      "Record is:  [1410, 145, 1464, 194, 'Pedestrian']\n",
      "Record is:  [1443, 114, 1505, 162, 'Pedestrian']\n",
      "Record is:  [584, 363, 638, 406, 'Pedestrian']\n",
      "Record is:  [1538, 723, 1598, 769, 'Pedestrian']\n",
      "Record is:  [1161, 563, 1224, 644, 'Pedestrian']\n",
      "Record is:  [301, 197, 361, 261, 'Pedestrian']\n",
      "Record is:  [0, 945, 34, 993, 'Pedestrian']\n",
      "Record is:  [0, 947, 35, 994, 'Skater']\n",
      "Record is:  [15, 934, 54, 986, 'Skater']\n",
      "13 1 0 0\n",
      "Ground Truth:  13\n",
      "processing time:  0.05648088455200195\n",
      "Record is:  [627, 390, 692, 524, 'Biker']\n",
      "Record is:  [412, 1667, 463, 1727, 'Biker']\n",
      "Record is:  [169, 1559, 218, 1654, 'Biker']\n",
      "Record is:  [413, 62, 461, 158, 'Pedestrian']\n",
      "4 0 0 0\n",
      "Ground Truth:  4\n",
      "processing time:  0.059538841247558594\n",
      "Record is:  [446, 809, 503, 917, 'Biker']\n",
      "Record is:  [634, 856, 692, 970, 'Biker']\n",
      "Record is:  [1021, 1712, 1097, 1813, 'Biker']\n",
      "Record is:  [1139, 1713, 1196, 1798, 'Pedestrian']\n",
      "Record is:  [1022, 1716, 1112, 1820, 'Pedestrian']\n",
      "Record is:  [642, 862, 682, 937, 'Biker']\n",
      "5 1 0 0\n",
      "Ground Truth:  4\n",
      "processing time:  0.05910849571228027\n",
      "Record is:  [1245, 1203, 1282, 1276, 'Pedestrian']\n",
      "Record is:  [1033, 693, 1104, 781, 'Pedestrian']\n",
      "Record is:  [1056, 1181, 1108, 1265, 'Pedestrian']\n",
      "Record is:  [1034, 693, 1105, 783, 'Biker']\n",
      "3 1 0 0\n",
      "Ground Truth:  3\n",
      "processing time:  0.05469179153442383\n",
      "Record is:  [703, 320, 735, 368, 'Pedestrian']\n",
      "Record is:  [1275, 888, 1328, 941, 'Biker']\n",
      "Record is:  [1334, 975, 1370, 1012, 'Pedestrian']\n",
      "Record is:  [1080, 522, 1114, 564, 'Pedestrian']\n",
      "Record is:  [309, 230, 340, 267, 'Pedestrian']\n",
      "Record is:  [91, 1026, 147, 1074, 'Pedestrian']\n",
      "4 0 2 3\n",
      "Ground Truth:  7\n",
      "processing time:  0.05498957633972168\n",
      "Record is:  [1375, 200, 1410, 250, 'Pedestrian']\n",
      "Record is:  [307, 801, 347, 848, 'Biker']\n",
      "Record is:  [373, 419, 411, 487, 'Biker']\n",
      "Record is:  [682, 352, 732, 402, 'Pedestrian']\n",
      "Record is:  [484, 932, 517, 966, 'Pedestrian']\n",
      "Record is:  [1119, 719, 1174, 770, 'Biker']\n",
      "Record is:  [430, 669, 465, 720, 'Pedestrian']\n",
      "Record is:  [209, 490, 248, 537, 'Pedestrian']\n",
      "Record is:  [478, 930, 526, 977, 'Pedestrian']\n",
      "Record is:  [900, 966, 929, 1009, 'Pedestrian']\n",
      "Record is:  [1159, 808, 1194, 844, 'Pedestrian']\n",
      "Record is:  [460, 352, 501, 404, 'Pedestrian']\n",
      "Record is:  [880, 958, 922, 1001, 'Pedestrian']\n",
      "Record is:  [225, 491, 255, 534, 'Pedestrian']\n",
      "10 2 2 4\n",
      "Ground Truth:  14\n",
      "processing time:  0.06086587905883789\n",
      "Record is:  [1320, 146, 1377, 187, 'Pedestrian']\n",
      "Record is:  [1274, 150, 1330, 194, 'Pedestrian']\n",
      "Record is:  [1431, 119, 1491, 163, 'Pedestrian']\n",
      "Record is:  [1264, 49, 1334, 102, 'Pedestrian']\n",
      "Record is:  [1478, 486, 1573, 557, 'Pedestrian']\n",
      "Record is:  [1330, 108, 1374, 152, 'Pedestrian']\n",
      "Record is:  [1402, 146, 1462, 189, 'Pedestrian']\n",
      "Record is:  [402, 353, 482, 415, 'Pedestrian']\n",
      "Record is:  [1273, 121, 1318, 163, 'Pedestrian']\n",
      "Record is:  [446, 794, 518, 838, 'Biker']\n",
      "Record is:  [577, 340, 674, 410, 'Pedestrian']\n",
      "Record is:  [1529, 938, 1635, 995, 'Biker']\n",
      "Record is:  [1517, 947, 1622, 1003, 'Pedestrian']\n",
      "Record is:  [577, 340, 674, 410, 'Biker']\n",
      "Record is:  [1288, 114, 1327, 159, 'Pedestrian']\n",
      "13 2 0 0\n",
      "Ground Truth:  12\n",
      "processing time:  0.05407238006591797\n",
      "Record is:  [640, 603, 675, 638, 'Pedestrian']\n",
      "Record is:  [1151, 1027, 1207, 1076, 'Biker']\n",
      "Record is:  [1070, 940, 1163, 1024, 'Car']\n",
      "Record is:  [648, 342, 695, 398, 'Pedestrian']\n",
      "Record is:  [1377, 204, 1409, 246, 'Pedestrian']\n",
      "Record is:  [317, 964, 360, 1007, 'Pedestrian']\n",
      "Record is:  [690, 689, 724, 737, 'Pedestrian']\n",
      "Record is:  [310, 795, 349, 843, 'Biker']\n",
      "Record is:  [1073, 948, 1173, 1023, 'Bus']\n",
      "Record is:  [251, 463, 277, 508, 'Pedestrian']\n",
      "Record is:  [400, 979, 430, 1018, 'Pedestrian']\n",
      "Record is:  [314, 962, 358, 1003, 'Biker']\n",
      "Record is:  [733, 269, 790, 316, 'Pedestrian']\n",
      "8 3 2 5\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ground Truth:  14\n",
      "processing time:  0.0583796501159668\n",
      "Record is:  [557, 911, 627, 985, 'Biker']\n",
      "Record is:  [301, 1160, 356, 1249, 'Pedestrian']\n",
      "Record is:  [559, 729, 614, 808, 'Pedestrian']\n",
      "Record is:  [99, 1063, 150, 1144, 'Biker']\n",
      "Record is:  [576, 708, 657, 810, 'Pedestrian']\n",
      "5 0 0 1\n",
      "Ground Truth:  5\n",
      "processing time:  0.059877634048461914\n",
      "Record is:  [689, 1330, 771, 1429, 'Biker']\n",
      "Record is:  [7, 1411, 79, 1524, 'Pedestrian']\n",
      "Record is:  [1072, 1191, 1141, 1290, 'Biker']\n",
      "Record is:  [117, 1101, 198, 1216, 'Biker']\n",
      "Record is:  [330, 1576, 374, 1657, 'Pedestrian']\n",
      "Record is:  [633, 1784, 705, 1881, 'Biker']\n",
      "Record is:  [1018, 1477, 1083, 1585, 'Biker']\n",
      "Record is:  [304, 1623, 352, 1709, 'Pedestrian']\n",
      "Record is:  [131, 612, 197, 711, 'Pedestrian']\n",
      "Record is:  [392, 587, 436, 680, 'Pedestrian']\n",
      "Record is:  [663, 136, 719, 259, 'Biker']\n",
      "Record is:  [200, 954, 257, 1055, 'Pedestrian']\n",
      "12 0 0 3\n",
      "Ground Truth:  15\n",
      "processing time:  0.0943000316619873\n",
      "Record is:  [1909, 620, 1935, 644, 'Pedestrian']\n",
      "Record is:  [1779, 793, 1819, 830, 'Pedestrian']\n",
      "Record is:  [1622, 705, 1665, 736, 'Pedestrian']\n",
      "Record is:  [1803, 676, 1830, 706, 'Pedestrian']\n",
      "Record is:  [826, 20, 876, 47, 'Pedestrian']\n",
      "Record is:  [1631, 655, 1659, 685, 'Pedestrian']\n",
      "Record is:  [1601, 839, 1663, 879, 'Pedestrian']\n",
      "Record is:  [1735, 706, 1764, 728, 'Pedestrian']\n",
      "Record is:  [1766, 806, 1821, 839, 'Pedestrian']\n",
      "Record is:  [1896, 651, 1923, 673, 'Pedestrian']\n",
      "Record is:  [1727, 692, 1756, 713, 'Pedestrian']\n",
      "Record is:  [1892, 659, 1920, 681, 'Pedestrian']\n",
      "Record is:  [1901, 622, 1929, 648, 'Pedestrian']\n",
      "Record is:  [1725, 688, 1752, 712, 'Biker']\n",
      "Record is:  [1944, 513, 1976, 553, 'Pedestrian']\n",
      "Record is:  [1908, 635, 1933, 657, 'Pedestrian']\n",
      "Record is:  [1766, 794, 1806, 830, 'Pedestrian']\n",
      "Record is:  [1905, 651, 1932, 672, 'Pedestrian']\n",
      "17 1 0 0\n",
      "Ground Truth:  13\n",
      "processing time:  0.05833721160888672\n",
      "Record is:  [574, 824, 628, 890, 'Biker']\n",
      "Record is:  [1043, 1117, 1090, 1159, 'Pedestrian']\n",
      "Record is:  [1034, 1142, 1082, 1193, 'Pedestrian']\n",
      "3 0 0 0\n",
      "Ground Truth:  3\n",
      "processing time:  0.06107950210571289\n",
      "Record is:  [1374, 202, 1407, 247, 'Pedestrian']\n",
      "Record is:  [381, 976, 432, 1035, 'Biker']\n",
      "Record is:  [651, 1021, 712, 1071, 'Biker']\n",
      "Record is:  [728, 861, 770, 913, 'Pedestrian']\n",
      "Record is:  [844, 1011, 891, 1056, 'Pedestrian']\n",
      "Record is:  [703, 340, 744, 380, 'Pedestrian']\n",
      "Record is:  [311, 971, 356, 1013, 'Biker']\n",
      "Record is:  [402, 574, 448, 622, 'Biker']\n",
      "Record is:  [309, 796, 346, 851, 'Biker']\n",
      "Record is:  [435, 382, 468, 427, 'Pedestrian']\n",
      "Record is:  [462, 806, 532, 876, 'Car']\n",
      "Record is:  [852, 1023, 896, 1067, 'Biker']\n",
      "Record is:  [836, 1004, 899, 1064, 'Biker']\n",
      "7 2 4 6\n",
      "Ground Truth:  15\n",
      "processing time:  0.05576324462890625\n",
      "Record is:  [884, 813, 945, 897, 'Biker']\n",
      "Record is:  [946, 1117, 1011, 1164, 'Pedestrian']\n",
      "Record is:  [952, 1148, 1009, 1203, 'Pedestrian']\n",
      "Record is:  [94, 902, 143, 965, 'Biker']\n",
      "Record is:  [115, 899, 164, 965, 'Biker']\n",
      "5 0 0 0\n",
      "Ground Truth:  4\n",
      "processing time:  0.057601213455200195\n",
      "Record is:  [1326, 146, 1377, 185, 'Pedestrian']\n",
      "Record is:  [1291, 109, 1330, 154, 'Pedestrian']\n",
      "Record is:  [1288, 150, 1328, 186, 'Pedestrian']\n",
      "Record is:  [1333, 109, 1376, 151, 'Pedestrian']\n",
      "Record is:  [1435, 117, 1493, 162, 'Pedestrian']\n",
      "Record is:  [1407, 141, 1465, 193, 'Pedestrian']\n",
      "Record is:  [1269, 53, 1326, 99, 'Pedestrian']\n",
      "Record is:  [404, 352, 481, 419, 'Pedestrian']\n",
      "Record is:  [576, 346, 659, 414, 'Pedestrian']\n",
      "Record is:  [243, 978, 304, 1055, 'Pedestrian']\n",
      "Record is:  [60, 636, 159, 723, 'Biker']\n",
      "Record is:  [1428, 735, 1512, 802, 'Pedestrian']\n",
      "Record is:  [959, 803, 1023, 872, 'Pedestrian']\n",
      "Record is:  [87, 653, 154, 742, 'Biker']\n",
      "14 0 0 1\n",
      "Ground Truth:  14\n",
      "processing time:  0.06960916519165039\n",
      "Record is:  [526, 895, 576, 955, 'Pedestrian']\n",
      "Record is:  [1374, 208, 1408, 244, 'Pedestrian']\n",
      "Record is:  [839, 998, 887, 1048, 'Pedestrian']\n",
      "Record is:  [692, 349, 737, 397, 'Pedestrian']\n",
      "Record is:  [435, 592, 480, 651, 'Pedestrian']\n",
      "Record is:  [1262, 868, 1314, 920, 'Biker']\n",
      "Record is:  [314, 796, 347, 842, 'Biker']\n",
      "Record is:  [1342, 777, 1388, 823, 'Biker']\n",
      "Record is:  [1297, 880, 1351, 934, 'Biker']\n",
      "Record is:  [1234, 796, 1272, 839, 'Pedestrian']\n",
      "Record is:  [1301, 889, 1341, 928, 'Pedestrian']\n",
      "Record is:  [1247, 1031, 1294, 1071, 'Pedestrian']\n",
      "Record is:  [298, 190, 329, 239, 'Pedestrian']\n",
      "8 4 1 6\n",
      "Ground Truth:  17\n",
      "processing time:  0.053475379943847656\n",
      "Record is:  [695, 352, 739, 399, 'Pedestrian']\n",
      "Record is:  [1379, 208, 1408, 243, 'Pedestrian']\n",
      "Record is:  [611, 528, 655, 580, 'Pedestrian']\n",
      "Record is:  [493, 747, 526, 787, 'Pedestrian']\n",
      "Record is:  [1088, 858, 1134, 901, 'Pedestrian']\n",
      "Record is:  [375, 371, 420, 421, 'Biker']\n",
      "Record is:  [114, 1027, 147, 1058, 'Pedestrian']\n",
      "Record is:  [479, 900, 530, 964, 'Biker']\n",
      "Record is:  [700, 344, 739, 382, 'Pedestrian']\n",
      "Record is:  [1364, 922, 1405, 956, 'Biker']\n",
      "9 1 0 4\n",
      "Ground Truth:  13\n",
      "processing time:  0.056852102279663086\n",
      "Record is:  [628, 971, 723, 1068, 'Biker']\n",
      "Record is:  [453, 782, 546, 913, 'Biker']\n",
      "Record is:  [864, 1028, 944, 1105, 'Biker']\n",
      "3 0 0 0\n",
      "Ground Truth:  3\n",
      "processing time:  0.05881452560424805\n",
      "Record is:  [1330, 110, 1373, 149, 'Pedestrian']\n",
      "Record is:  [1286, 149, 1331, 185, 'Pedestrian']\n",
      "Record is:  [1290, 113, 1325, 150, 'Pedestrian']\n",
      "Record is:  [1269, 62, 1325, 105, 'Pedestrian']\n",
      "Record is:  [1411, 145, 1466, 193, 'Pedestrian']\n",
      "Record is:  [1330, 139, 1365, 170, 'Pedestrian']\n",
      "Record is:  [1445, 113, 1504, 162, 'Pedestrian']\n",
      "Record is:  [585, 364, 640, 406, 'Pedestrian']\n",
      "Record is:  [327, 245, 384, 307, 'Pedestrian']\n",
      "Record is:  [1122, 592, 1194, 668, 'Pedestrian']\n",
      "Record is:  [1547, 779, 1602, 824, 'Pedestrian']\n",
      "Record is:  [1878, 865, 1980, 939, 'Biker']\n",
      "Record is:  [0, 958, 17, 1001, 'Pedestrian']\n",
      "12 1 0 0\n",
      "Ground Truth:  13\n",
      "processing time:  0.056242942810058594\n",
      "Record is:  [687, 844, 730, 939, 'Biker']\n",
      "Record is:  [819, 1043, 864, 1113, 'Biker']\n",
      "Record is:  [169, 886, 202, 960, 'Biker']\n",
      "Record is:  [406, 1216, 449, 1285, 'Pedestrian']\n",
      "Record is:  [219, 1140, 253, 1222, 'Pedestrian']\n",
      "Record is:  [391, 1221, 439, 1296, 'Pedestrian']\n",
      "Record is:  [981, 851, 1038, 931, 'Biker']\n",
      "7 0 0 0\n",
      "Ground Truth:  6\n",
      "processing time:  0.05967116355895996\n",
      "Record is:  [1290, 151, 1331, 189, 'Pedestrian']\n",
      "Record is:  [1330, 142, 1368, 174, 'Pedestrian']\n",
      "Record is:  [1332, 111, 1373, 148, 'Pedestrian']\n",
      "Record is:  [1282, 56, 1328, 92, 'Pedestrian']\n",
      "Record is:  [1289, 116, 1330, 152, 'Pedestrian']\n",
      "Record is:  [1413, 148, 1466, 201, 'Pedestrian']\n",
      "Record is:  [1437, 114, 1501, 161, 'Pedestrian']\n",
      "Record is:  [1634, 922, 1712, 961, 'Pedestrian']\n",
      "Record is:  [849, 998, 912, 1054, 'Pedestrian']\n",
      "Record is:  [1284, 87, 1328, 122, 'Pedestrian']\n",
      "Record is:  [596, 866, 714, 954, 'Biker']\n",
      "Record is:  [1467, 733, 1517, 773, 'Pedestrian']\n",
      "Record is:  [582, 350, 651, 412, 'Pedestrian']\n",
      "Record is:  [1732, 672, 1838, 740, 'Pedestrian']\n",
      "10 0 4 2\n",
      "Ground Truth:  12\n",
      "processing time:  0.06174802780151367\n",
      "Record is:  [897, 454, 942, 508, 'Pedestrian']\n",
      "Record is:  [1370, 205, 1408, 249, 'Pedestrian']\n",
      "Record is:  [598, 469, 643, 513, 'Pedestrian']\n",
      "Record is:  [708, 348, 750, 395, 'Pedestrian']\n",
      "Record is:  [1155, 884, 1180, 934, 'Pedestrian']\n",
      "Record is:  [1044, 880, 1073, 923, 'Pedestrian']\n",
      "Record is:  [997, 1028, 1062, 1069, 'Biker']\n",
      "Record is:  [463, 351, 496, 401, 'Pedestrian']\n",
      "Record is:  [1032, 871, 1069, 918, 'Pedestrian']\n",
      "Record is:  [1276, 964, 1328, 1007, 'Biker']\n",
      "Record is:  [741, 273, 790, 314, 'Pedestrian']\n",
      "8 1 2 7\n",
      "Ground Truth:  16\n",
      "processing time:  0.07993078231811523\n",
      "Record is:  [1283, 149, 1331, 187, 'Pedestrian']\n",
      "Record is:  [1290, 115, 1333, 153, 'Pedestrian']\n",
      "Record is:  [1333, 144, 1368, 178, 'Pedestrian']\n",
      "Record is:  [1332, 108, 1376, 148, 'Pedestrian']\n",
      "Record is:  [1279, 84, 1328, 121, 'Pedestrian']\n",
      "Record is:  [1409, 147, 1466, 204, 'Pedestrian']\n",
      "Record is:  [1435, 110, 1500, 161, 'Pedestrian']\n",
      "Record is:  [586, 363, 638, 408, 'Pedestrian']\n",
      "Record is:  [1271, 59, 1324, 100, 'Pedestrian']\n",
      "Record is:  [252, 922, 303, 958, 'Pedestrian']\n",
      "Record is:  [1298, 309, 1376, 391, 'Pedestrian']\n",
      "Record is:  [1449, 738, 1510, 777, 'Pedestrian']\n",
      "Record is:  [215, 947, 272, 986, 'Pedestrian']\n",
      "Record is:  [1382, 670, 1437, 718, 'Pedestrian']\n",
      "10 2 2 0\n",
      "Ground Truth:  11\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "processing time:  0.3062257766723633\n",
      "Record is:  [1153, 1122, 1201, 1193, 'Pedestrian']\n",
      "Record is:  [776, 254, 824, 347, 'Biker']\n",
      "Record is:  [487, 471, 529, 570, 'Biker']\n",
      "Record is:  [546, 1817, 589, 1902, 'Biker']\n",
      "Record is:  [609, 1179, 654, 1268, 'Biker']\n",
      "Record is:  [384, 665, 439, 755, 'Biker']\n",
      "Record is:  [769, 183, 806, 255, 'Biker']\n",
      "Record is:  [743, 47, 791, 134, 'Biker']\n",
      "Record is:  [772, 1025, 829, 1094, 'Biker']\n",
      "Record is:  [613, 1467, 647, 1536, 'Biker']\n",
      "Record is:  [795, 889, 843, 987, 'Biker']\n",
      "Record is:  [776, 1065, 814, 1138, 'Biker']\n",
      "Record is:  [522, 566, 575, 662, 'Biker']\n",
      "Record is:  [684, 1113, 740, 1184, 'Biker']\n",
      "Record is:  [744, 470, 790, 548, 'Biker']\n",
      "Record is:  [744, 470, 790, 550, 'Cart']\n",
      "Record is:  [702, 1840, 736, 1909, 'Pedestrian']\n",
      "Record is:  [720, 168, 757, 273, 'Biker']\n",
      "Record is:  [315, 1054, 356, 1109, 'Biker']\n",
      "Record is:  [660, 1827, 697, 1911, 'Pedestrian']\n",
      "Record is:  [717, 694, 754, 770, 'Cart']\n",
      "Record is:  [500, 756, 548, 827, 'Biker']\n",
      "Record is:  [547, 1819, 590, 1902, 'Pedestrian']\n",
      "Record is:  [847, 1020, 883, 1085, 'Biker']\n",
      "Record is:  [438, 411, 468, 484, 'Pedestrian']\n",
      "Record is:  [1265, 942, 1299, 1001, 'Biker']\n",
      "Record is:  [250, 1032, 285, 1085, 'Biker']\n",
      "Record is:  [429, 1079, 493, 1147, 'Biker']\n",
      "Record is:  [712, 697, 754, 768, 'Biker']\n",
      "Record is:  [440, 403, 469, 491, 'Biker']\n",
      "Record is:  [1218, 890, 1255, 936, 'Pedestrian']\n",
      "Record is:  [1254, 939, 1286, 999, 'Biker']\n",
      "Record is:  [657, 1451, 686, 1515, 'Biker']\n",
      "Record is:  [567, 1096, 618, 1178, 'Biker']\n",
      "Record is:  [803, 1107, 839, 1181, 'Biker']\n",
      "Record is:  [153, 719, 210, 773, 'Pedestrian']\n",
      "Record is:  [745, 470, 790, 548, 'Skater']\n",
      "Record is:  [813, 820, 843, 872, 'Pedestrian']\n",
      "17 10 11 7\n",
      "Ground Truth:  31\n",
      "processing time:  0.05908775329589844\n",
      "Record is:  [1027, 838, 1057, 921, 'Pedestrian']\n",
      "Record is:  [152, 830, 221, 902, 'Biker']\n",
      "Record is:  [845, 864, 884, 928, 'Biker']\n",
      "Record is:  [1260, 1754, 1299, 1815, 'Biker']\n",
      "Record is:  [890, 852, 929, 912, 'Biker']\n",
      "4 0 1 0\n",
      "Ground Truth:  4\n",
      "processing time:  0.06230330467224121\n",
      "Record is:  [1266, 1619, 1300, 1707, 'Pedestrian']\n",
      "Record is:  [510, 862, 565, 955, 'Biker']\n",
      "Record is:  [908, 890, 944, 962, 'Pedestrian']\n",
      "3 0 0 1\n",
      "Ground Truth:  4\n",
      "processing time:  0.05801701545715332\n",
      "Record is:  [718, 689, 751, 743, 'Pedestrian']\n",
      "1 0 0 0\n",
      "Ground Truth:  1\n",
      "processing time:  0.0559086799621582\n",
      "Record is:  [1290, 150, 1332, 188, 'Pedestrian']\n",
      "Record is:  [1331, 112, 1372, 148, 'Pedestrian']\n",
      "Record is:  [1328, 141, 1369, 174, 'Pedestrian']\n",
      "Record is:  [1278, 54, 1330, 93, 'Pedestrian']\n",
      "Record is:  [1291, 114, 1332, 151, 'Pedestrian']\n",
      "Record is:  [1446, 110, 1505, 160, 'Pedestrian']\n",
      "Record is:  [1415, 144, 1462, 190, 'Pedestrian']\n",
      "Record is:  [585, 361, 642, 409, 'Pedestrian']\n",
      "Record is:  [1450, 913, 1518, 948, 'Pedestrian']\n",
      "Record is:  [1457, 878, 1523, 918, 'Pedestrian']\n",
      "Record is:  [1466, 734, 1512, 775, 'Pedestrian']\n",
      "Record is:  [1287, 86, 1327, 123, 'Pedestrian']\n",
      "Record is:  [101, 900, 164, 935, 'Biker']\n",
      "Record is:  [1280, 68, 1327, 108, 'Pedestrian']\n",
      "13 0 1 0\n",
      "Ground Truth:  12\n",
      "processing time:  0.05707359313964844\n",
      "Record is:  [1321, 139, 1375, 180, 'Pedestrian']\n",
      "Record is:  [1331, 108, 1383, 151, 'Pedestrian']\n",
      "Record is:  [1286, 113, 1335, 151, 'Pedestrian']\n",
      "Record is:  [1230, 790, 1310, 856, 'Pedestrian']\n",
      "Record is:  [1277, 141, 1336, 186, 'Pedestrian']\n",
      "Record is:  [1277, 84, 1333, 126, 'Pedestrian']\n",
      "Record is:  [1486, 953, 1575, 1013, 'Pedestrian']\n",
      "Record is:  [1437, 111, 1498, 160, 'Pedestrian']\n",
      "Record is:  [1274, 41, 1335, 94, 'Pedestrian']\n",
      "Record is:  [1105, 245, 1200, 311, 'Pedestrian']\n",
      "Record is:  [1499, 918, 1587, 966, 'Pedestrian']\n",
      "Record is:  [1203, 70, 1262, 120, 'Pedestrian']\n",
      "Record is:  [1408, 147, 1468, 203, 'Pedestrian']\n",
      "Record is:  [1443, 732, 1518, 782, 'Pedestrian']\n",
      "Record is:  [1408, 147, 1468, 202, 'Biker']\n",
      "13 1 1 0\n",
      "Ground Truth:  13\n",
      "processing time:  0.05578303337097168\n",
      "Record is:  [766, 1111, 832, 1171, 'Pedestrian']\n",
      "Record is:  [762, 1146, 821, 1204, 'Pedestrian']\n",
      "Record is:  [793, 901, 841, 987, 'Biker']\n",
      "Record is:  [69, 1050, 111, 1126, 'Biker']\n",
      "4 0 0 0\n",
      "Ground Truth:  4\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-12-d1e68199da07>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mfilepath\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mimage_names\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m     \u001b[0mnum_tp\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnum_cm\u001b[0m \u001b[0;34m,\u001b[0m \u001b[0mnum_fp\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnum_fn\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnum_gt\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrun_detection_image\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      3\u001b[0m     \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Ground Truth: \"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnum_gt\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m     \u001b[0mtotal_true_positive\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0mnum_tp\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m     \u001b[0mtotal_class_mismatch\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0mnum_cm\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m<ipython-input-10-9c90428ccd9c>\u001b[0m in \u001b[0;36mrun_detection_image\u001b[0;34m(filepath)\u001b[0m\n\u001b[1;32m     12\u001b[0m     \u001b[0;31m# process image\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     13\u001b[0m     \u001b[0mstart\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 14\u001b[0;31m     \u001b[0mboxes\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mscores\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabels\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpredict_on_batch\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexpand_dims\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mimage\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     15\u001b[0m     \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"processing time: \"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mstart\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     16\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.local/lib/python3.6/site-packages/keras/engine/training.py\u001b[0m in \u001b[0;36mpredict_on_batch\u001b[0;34m(self, x)\u001b[0m\n\u001b[1;32m   1272\u001b[0m             \u001b[0mins\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1273\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_make_predict_function\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1274\u001b[0;31m         \u001b[0moutputs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpredict_function\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mins\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1275\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0munpack_singleton\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0moutputs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1276\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.local/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, inputs)\u001b[0m\n\u001b[1;32m   2713\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_legacy_call\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minputs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2714\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2715\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_call\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minputs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2716\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2717\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mpy_any\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mis_tensor\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mx\u001b[0m \u001b[0;32min\u001b[0m \u001b[0minputs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.local/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py\u001b[0m in \u001b[0;36m_call\u001b[0;34m(self, inputs)\u001b[0m\n\u001b[1;32m   2673\u001b[0m             \u001b[0mfetched\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_callable_fn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0marray_vals\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrun_metadata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun_metadata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2674\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2675\u001b[0;31m             \u001b[0mfetched\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_callable_fn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0marray_vals\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2676\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mfetched\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moutputs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2677\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/tf_latest/lib/python3.6/site-packages/tensorflow/python/client/session.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m   1437\u001b[0m           ret = tf_session.TF_SessionRunCallable(\n\u001b[1;32m   1438\u001b[0m               \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_session\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_session\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_handle\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstatus\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1439\u001b[0;31m               run_metadata_ptr)\n\u001b[0m\u001b[1;32m   1440\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mrun_metadata\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1441\u001b[0m           \u001b[0mproto_data\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtf_session\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTF_GetBuffer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrun_metadata_ptr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "for filepath in image_names:\n",
    "    num_tp, num_cm , num_fp, num_fn, num_gt = run_detection_image(filepath)\n",
    "    print(\"Ground Truth: \", num_gt)\n",
    "    total_true_positive += num_tp\n",
    "    total_class_mismatch += num_cm\n",
    "    total_false_positive += num_fp\n",
    "    total_false_negative += num_fn\n",
    "    total_gt += num_gt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5198 551 812 1531 6867\n"
     ]
    }
   ],
   "source": [
    "print(total_true_positive, total_class_mismatch, total_false_positive, total_false_negative, total_gt)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "gt_ann = get_gt_annotations(filepath)\n",
    "print(gt_ann)\n",
    "im = cv2.imread(filepath)\n",
    "for each_ann in gt_ann:\n",
    "    cv2.rectangle(im, (each_ann[0],each_ann[1]),(each_ann[2],each_ann[3]),(0,0,255),3)\n",
    "cv2.imwrite('examples/results_test/pred_gt.jpg', im)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "predicted_ann = run_detection_image(filepath)\n",
    "print(predicted_ann)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "true_positive, class_mismatch, false_positive, false_negative = accuracy(gt_ann, predicted_ann)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.7922572778539857 0.7724773368999851 0.782242287434161\n"
     ]
    }
   ],
   "source": [
    "# 4763 687 2192 1067 5854\n",
    "\n",
    "precision = total_true_positive/(total_true_positive+total_false_positive+total_class_mismatch)\n",
    "recall = total_true_positive/(total_true_positive+ total_false_negative)\n",
    "f1_score = 2*(precision * recall)/(precision + recall)\n",
    "\n",
    "print(precision, recall, f1_score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 0.8605186114596404 0.6314255025318398 0.7283830427471458 at 0.5\n",
    "# 0.6608789366542929 0.8296752856283824 0.7357195227621142 at 0.3\n",
    "#0.7766865239091933 0.7453646477132262 0.7607033036347867 at 0.4"
   ]
  }
 ],
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