Evaluation Metrics.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# <center><font color='MAROON'>Traffic Sign Recognition Classifier</font></center>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from PIL import Image\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.image as mpimg\n",
    "from tqdm import tqdm\n",
    "import seaborn as sns\n",
    "import numpy as np\n",
    "import os\n",
    "import math\n",
    "import keras\n",
    "import wandb"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <font color='crimson'>Importing GTSRB - German Traffic Sign Recognition Benchmark Datasets</font>\n",
    "\n",
    "\n",
    "<font color='maroon'>Dataset for this project is available at:</font>\n",
    "\n",
    "https://www.kaggle.com/meowmeowmeowmeowmeow/gtsrb-german-traffic-sign"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "C:\\Users\\junth\\Traffic-Signs-Recognition-System\n"
     ]
    }
   ],
   "source": [
    "current_path = os.getcwd()\n",
    "print(current_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "classes = 43\n",
    "classes_name = ['Speed limit (20km/h)',\n",
    "                'Speed limit (30km/h)', \n",
    "                'Speed limit (50km/h)', \n",
    "                'Speed limit (60km/h)', \n",
    "                'Speed limit (70km/h)', \n",
    "                'Speed limit (80km/h)', \n",
    "                'End of speed limit (80km/h)', \n",
    "                'Speed limit (100km/h)', \n",
    "                'Speed limit (120km/h)', \n",
    "                'No passing', \n",
    "                'No passing veh over 3.5 tons', \n",
    "                'Right-of-way at intersection', \n",
    "                'Priority road', \n",
    "                'Yield', \n",
    "                'Stop', \n",
    "                'No vehicles', \n",
    "                'Veh > 3.5 tons prohibited', \n",
    "                'No entry', \n",
    "                'General caution', \n",
    "                'Dangerous curve left', \n",
    "                'Dangerous curve right', \n",
    "                'Double curve', \n",
    "                'Bumpy road', \n",
    "                'Slippery road', \n",
    "                'Road narrows on the right', \n",
    "                'Road work', \n",
    "                'Traffic signals', \n",
    "                'Pedestrians', \n",
    "                'Children crossing', \n",
    "                'Bicycles crossing', \n",
    "                'Beware of ice/snow',\n",
    "                'Wild animals crossing', \n",
    "                'End speed + passing limits', \n",
    "                'Turn right ahead', \n",
    "                'Turn left ahead', \n",
    "                'Ahead only', \n",
    "                'Go straight or right', \n",
    "                'Go straight or left', \n",
    "                'Keep right', \n",
    "                'Keep left', \n",
    "                'Roundabout mandatory', \n",
    "                'End of no passing', \n",
    "                'End no passing veh > 3.5 tons' \n",
    "               ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def ImageReader(define_path):\n",
    "    data = []\n",
    "    path = os.path.join(current_path,'gtsrb-german-traffic-sign',define_path)\n",
    "    images = os.listdir(path)\n",
    "\n",
    "    for traffic_sign in tqdm(images):\n",
    "        try:\n",
    "            image = Image.open(path + '\\\\'+ traffic_sign)\n",
    "            image = image.resize((32,32))\n",
    "            image = np.array(image)\n",
    "\n",
    "            data.append(image)\n",
    "        except:\n",
    "            print(\"Error Loading Image!\")\n",
    "    return data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 12630/12630 [01:05<00:00, 193.57it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      X_test                      \n",
      "(12630, 32, 32, 3)                \n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "test_images = ImageReader('test')\n",
    "X_test = np.array(test_images)\n",
    "print(\"      X_test                      \\n{0}                \".format(X_test.shape))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <font color='crimson'>Contrast Limited Adaptive Histogram Equalization (CLAHE)</font>\n",
    "\n",
    "---\n",
    "\n",
    "<font color='maroon'>An algorithm for local contrast enhancement, that uses histograms computed over different tile regions of the image. Local details can therefore be enhanced even in regions that are darker or lighter than most of the image.</font>\n",
    "\n",
    "https://scikit-image.org/docs/dev/api/skimage.exposure.html#skimage.exposure.equalize_adapthist\n",
    "\n",
    "<font color='maroon'>Clipping limit, normalized between 0 and 1 (higher values give more contrast).</font>\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from skimage import data, img_as_float\n",
    "from skimage import exposure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Function that applies normalization and local contrast enhancement\n",
    "\n",
    "def normalize(image_data):\n",
    "    \n",
    "    \"\"\"An algorithm for local contrast enhancement, that uses histograms computed over \n",
    "    different tile regions of the image. Local details can therefore be enhanced even in \n",
    "    regions that are darker or lighter than most of the image.\"\"\"\n",
    "    \n",
    "    norm = np.array([exposure.equalize_adapthist(image, clip_limit=0.1) for image in tqdm(image_data)])\n",
    "    return norm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/12630 [00:00<?, ?it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Normalizing Test Images...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\junth\\Anaconda3\\envs\\Traffic Sign Recognition System\\lib\\site-packages\\skimage\\util\\dtype.py:135: UserWarning: Possible precision loss when converting from float64 to uint16\n",
      "  .format(dtypeobj_in, dtypeobj_out))\n",
      "100%|██████████| 12630/12630 [03:39<00:00, 57.51it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Normaliztion Complete.\n"
     ]
    }
   ],
   "source": [
    "# Run the normalization process\n",
    "\n",
    "print('\\nNormalizing Test Images...')\n",
    "X_test_norm = normalize(X_test)\n",
    "\n",
    "print('\\nNormaliztion Complete.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# <center><font color='MAROON'>Model Architecture</font></center>\n",
    "---\n",
    "\n",
    "## <font color='DARKMAGENTA'>1. LeNet-5</font>\n",
    "\n",
    "https://app.wandb.ai/junth/traffic-sign-recognition-classifier/runs/sfserq93?workspace=user-junth\n",
    "\n",
    "## <font color='DARKMAGENTA'>2. LeNet-5 + Contrast Enhancement</font>\n",
    "\n",
    "https://app.wandb.ai/junth/traffic-sign-recognition-classifier/runs/kcebxhfe?workspace=user-junth\n",
    "\n",
    "## <font color='DARKMAGENTA'>3. LeNet-5 + Contrast Enhancement + Augmentation(3000)</font>\n",
    "\n",
    "https://app.wandb.ai/junth/traffic-sign-recognition-classifier/runs/qc0c461b?workspace=user-junth\n",
    "\n",
    "## <font color='DARKMAGENTA'>4. Deep LeNet-5 + Contrast Enhancement + Augmentation(3000)</font>\n",
    "\n",
    "https://app.wandb.ai/junth/traffic-sign-recognition-classifier/runs/zllcbd7m?workspace=user-junth\n",
    "\n",
    "## <font color='DARKMAGENTA'>5. Deep LeNet-5 + Contrast Enhancement + Augmentation(4500) + Regularization</font>\n",
    "\n",
    "https://app.wandb.ai/junth/traffic-sign-recognition-classifier/runs/2atxo1cf?workspace=user-junth\n",
    "\n",
    "---\n",
    "\n",
    "<font color='maroon'>Saved model is also available at:</font>\n",
    "\n",
    "https://github.com/Junth19/Traffic-Signs-Recognition-System\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <font color='crimson'>Loading (Deep LeNet-5 + Contrast Enhancement + Augmentation(4500) + Regularization) saved model</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential_1\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "conv2d_1 (Conv2D)            (None, 28, 28, 32)        2432      \n",
      "_________________________________________________________________\n",
      "conv2d_2 (Conv2D)            (None, 24, 24, 32)        25632     \n",
      "_________________________________________________________________\n",
      "max_pooling2d_1 (MaxPooling2 (None, 12, 12, 32)        0         \n",
      "_________________________________________________________________\n",
      "conv2d_3 (Conv2D)            (None, 8, 8, 64)          51264     \n",
      "_________________________________________________________________\n",
      "conv2d_4 (Conv2D)            (None, 4, 4, 64)          102464    \n",
      "_________________________________________________________________\n",
      "max_pooling2d_2 (MaxPooling2 (None, 2, 2, 64)          0         \n",
      "_________________________________________________________________\n",
      "flatten_1 (Flatten)          (None, 256)               0         \n",
      "_________________________________________________________________\n",
      "dropout_1 (Dropout)          (None, 256)               0         \n",
      "_________________________________________________________________\n",
      "dense_1 (Dense)              (None, 1024)              263168    \n",
      "_________________________________________________________________\n",
      "dropout_2 (Dropout)          (None, 1024)              0         \n",
      "_________________________________________________________________\n",
      "dense_2 (Dense)              (None, 512)               524800    \n",
      "_________________________________________________________________\n",
      "dropout_3 (Dropout)          (None, 512)               0         \n",
      "_________________________________________________________________\n",
      "dense_3 (Dense)              (None, 43)                22059     \n",
      "=================================================================\n",
      "Total params: 991,819\n",
      "Trainable params: 991,819\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "from keras.models import load_model\n",
    "\n",
    "model = load_model('./Models/(5) Deep LeNet-5 + Contrast Enhancement + Augmentation(4500) + Regularization/DeepLeNet-5_CLAHE_AUG(v2).h5')\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <font color='crimson'>Calculating Test Accuracy</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "from keras.utils import to_categorical\n",
    "\n",
    "path = os.path.join(current_path,'gtsrb-german-traffic-sign','Test.csv')\n",
    "data = pd.read_csv(path)\n",
    "X_test = X_test_norm.astype('float32')\n",
    "y_test = to_categorical(data['ClassId'].values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "12630/12630 [==============================] - 20s 2ms/step\n",
      "0.9712588787078857\n"
     ]
    }
   ],
   "source": [
    "test_loss, test_acc = model.evaluate(X_test, y_test)\n",
    "print(test_acc)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <font color='crimson'>Make predictions and explore </font>\n",
    "<font color='maroon'>With the model trained, we can use it to make predictions about some images.</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(12630, 43)\n"
     ]
    }
   ],
   "source": [
    "test_images = X_test\n",
    "a = y_test\n",
    "test_labels = [np.where(r==1)[0][0] for r in a]\n",
    "predictions = model.predict(test_images)\n",
    "print(predictions.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <font color='crimson'>Precision, Recall and F1-Score</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                               precision    recall  f1-score   support\n",
      "\n",
      "         Speed limit (20km/h)       0.92      1.00      0.96        60\n",
      "         Speed limit (30km/h)       0.95      0.99      0.97       720\n",
      "         Speed limit (50km/h)       0.98      0.98      0.98       750\n",
      "         Speed limit (60km/h)       0.96      0.92      0.94       450\n",
      "         Speed limit (70km/h)       1.00      0.97      0.98       660\n",
      "         Speed limit (80km/h)       0.94      0.94      0.94       630\n",
      "  End of speed limit (80km/h)       0.98      0.96      0.97       150\n",
      "        Speed limit (100km/h)       0.95      0.99      0.97       450\n",
      "        Speed limit (120km/h)       0.99      0.96      0.97       450\n",
      "                   No passing       1.00      0.99      0.99       480\n",
      " No passing veh over 3.5 tons       1.00      1.00      1.00       660\n",
      " Right-of-way at intersection       0.99      0.93      0.96       420\n",
      "                Priority road       1.00      0.98      0.99       690\n",
      "                        Yield       1.00      1.00      1.00       720\n",
      "                         Stop       1.00      1.00      1.00       270\n",
      "                  No vehicles       0.95      0.98      0.96       210\n",
      "    Veh > 3.5 tons prohibited       0.98      1.00      0.99       150\n",
      "                     No entry       1.00      1.00      1.00       360\n",
      "              General caution       0.99      0.85      0.91       390\n",
      "         Dangerous curve left       0.98      0.95      0.97        60\n",
      "        Dangerous curve right       0.97      1.00      0.98        90\n",
      "                 Double curve       0.84      0.99      0.91        90\n",
      "                   Bumpy road       0.96      0.89      0.93       120\n",
      "                Slippery road       0.82      0.99      0.89       150\n",
      "    Road narrows on the right       0.92      0.99      0.95        90\n",
      "                    Road work       0.97      0.98      0.98       480\n",
      "              Traffic signals       0.90      0.98      0.94       180\n",
      "                  Pedestrians       0.69      0.87      0.77        60\n",
      "            Children crossing       0.98      0.99      0.99       150\n",
      "            Bicycles crossing       0.91      1.00      0.95        90\n",
      "           Beware of ice/snow       0.86      0.77      0.81       150\n",
      "        Wild animals crossing       0.98      1.00      0.99       270\n",
      "   End speed + passing limits       0.92      1.00      0.96        60\n",
      "             Turn right ahead       1.00      1.00      1.00       210\n",
      "              Turn left ahead       1.00      1.00      1.00       120\n",
      "                   Ahead only       1.00      0.96      0.98       390\n",
      "         Go straight or right       0.94      1.00      0.97       120\n",
      "          Go straight or left       0.91      1.00      0.95        60\n",
      "                   Keep right       1.00      1.00      1.00       690\n",
      "                    Keep left       1.00      1.00      1.00        90\n",
      "         Roundabout mandatory       0.97      0.97      0.97        90\n",
      "            End of no passing       0.91      1.00      0.95        60\n",
      "End no passing veh > 3.5 tons       0.99      0.91      0.95        90\n",
      "\n",
      "                     accuracy                           0.97     12630\n",
      "                    macro avg       0.95      0.97      0.96     12630\n",
      "                 weighted avg       0.97      0.97      0.97     12630\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import classification_report\n",
    "y_pred = []\n",
    "y_true = test_labels\n",
    "for i in range(len(X_test)):\n",
    "    y_pred.append(np.argmax(predictions[i]))\n",
    "print(classification_report(y_true, y_pred, target_names=classes_name))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <font color='crimson'>Confusion Matrix </font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.metrics import confusion_matrix\n",
    "import matplotlib.pyplot as plt\n",
    "fig, ax = plt.subplots(figsize=(20, 20))\n",
    "\n",
    "def plot_confusion_matrix(cm, classes,\n",
    "                          normalize=False,\n",
    "                          title='Confusion matrix',\n",
    "                          cmap=plt.cm.hot):\n",
    "    ax.imshow(cm, interpolation='nearest', cmap=cmap)\n",
    "    plt.title(title)\n",
    "    tick_marks = np.arange(len(classes))\n",
    "    plt.xticks(tick_marks, classes, rotation=90)\n",
    "    plt.yticks(tick_marks, classes)\n",
    "    plt.ylabel('True label')\n",
    "    plt.xlabel('Predicted label')\n",
    "    plt.savefig('ConfusionMatrix.png', dpi = 300)\n",
    "\n",
    "confusionMatrix = confusion_matrix(y_true, y_pred)\n",
    "\n",
    "plot_confusion_matrix(confusionMatrix, classes=classes_name,\n",
    "                      title='Confusion Matrix')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color='maroon'>Here, the model has predicted the label for each image in the testing set. Let's take a look at the first prediction:</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[5.53347113e-23 2.25632895e-24 1.87222466e-25 9.91451331e-21\n",
      " 7.06093698e-24 1.73483569e-19 3.34171611e-25 1.29416843e-14\n",
      " 3.36282177e-14 6.92636270e-12 6.68180795e-20 2.20045792e-23\n",
      " 3.40702204e-21 9.43295660e-30 1.93325006e-23 3.08632277e-14\n",
      " 1.00000000e+00 1.02493296e-16 5.17179646e-28 1.67891713e-25\n",
      " 2.17810965e-23 2.98830122e-35 4.32103401e-35 1.87172291e-27\n",
      " 1.75476087e-37 2.45436388e-33 8.27349231e-29 7.77186460e-31\n",
      " 1.30555851e-25 3.56675635e-29 5.66223027e-23 1.09792030e-31\n",
      " 1.48616160e-18 1.81068843e-17 7.66892546e-18 2.18846348e-22\n",
      " 3.59798525e-20 1.06000669e-19 9.87950818e-22 1.95187933e-23\n",
      " 1.53011538e-14 2.11024243e-16 9.74331762e-21]\n"
     ]
    }
   ],
   "source": [
    "print(predictions[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color='maroon'>A prediction is an array of 43 numbers. These describe the \"confidence\" of the model that the image corresponds to each of the 43 different traffic road signs. We can see which label has the highest confidence value:</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "16"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.argmax(predictions[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color='maroon'>So the model is most confident that this image is a </font>`Veh > 3.5 tons prohibited`or `classes_name[16]`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "16"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_labels[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Veh > 3.5 tons prohibited'"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "classes_name[16]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <font color='crimson'>Plot several images with their predictions (Softmax Probability)</font>\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_image(i, predictions_array, true_labels, images):\n",
    "    predictions_array, true_label, img = predictions_array[i], true_labels[i], images[i]\n",
    "    plt.grid(False)\n",
    "    plt.xticks([])\n",
    "    plt.yticks([])\n",
    "\n",
    "    plt.imshow(img)\n",
    "\n",
    "    predicted_label = np.argmax(predictions_array)\n",
    "    if predicted_label == true_label:\n",
    "        color = 'blue'\n",
    "    else:\n",
    "        color = 'red'\n",
    "\n",
    "    plt.xlabel(\"{} {:2.0f}% ({})\".format(classes_name[predicted_label],\n",
    "                                100*np.max(predictions_array),\n",
    "                                classes_name[true_label]),\n",
    "                                color=color)\n",
    "\n",
    "def plot_value_array(i, predictions_array, true_label):\n",
    "    predictions_array, true_label = predictions_array[i], true_label[i]\n",
    "    plt.grid(False)\n",
    "    plt.xticks([])\n",
    "    plt.yticks([])\n",
    "    thisplot = plt.bar(range(43), predictions_array, color=\"#777777\")\n",
    "    plt.ylim([0, 1]) \n",
    "    predicted_label = np.argmax(predictions_array)\n",
    "  \n",
    "    thisplot[predicted_label].set_color('red')\n",
    "    thisplot[true_label].set_color('blue')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x216 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "i = 212\n",
    "plt.figure(figsize=(16,3))\n",
    "plt.subplot(1,2,1)\n",
    "plot_image(i, predictions, test_labels, test_images)\n",
    "plt.subplot(1,2,2)\n",
    "plot_value_array(i, predictions, test_labels)\n",
    "plt.savefig('PredictionHistogram10.png', dpi = 300)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x216 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "i = 1\n",
    "plt.figure(figsize=(16,3))\n",
    "plt.subplot(1,2,1)\n",
    "plot_image(i, predictions, test_labels, test_images)\n",
    "plt.subplot(1,2,2)\n",
    "plot_value_array(i, predictions, test_labels)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "<font color='maroon'>Let's plot several images with their predictions. Correct prediction labels are blue and incorrect prediction labels are red. The number gives the percent (out of 100) for the predicted label.</font>\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x3240 with 30 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "num_rows = 15\n",
    "num_cols = 1\n",
    "num_images = num_rows * num_cols\n",
    "plt.figure(figsize=(4 * 4 * num_cols, 3 * num_rows))\n",
    "for i in range(num_images):\n",
    "    plt.subplot(num_rows, 2 * num_cols, 2 * i + 1)\n",
    "    plot_image(i, predictions, test_labels, test_images)\n",
    "    plt.subplot(num_rows, 2 * num_cols, 2 * i + 2)\n",
    "    plot_value_array(i, predictions, test_labels)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.5"
  },
  "pycharm": {
   "stem_cell": {
    "cell_type": "raw",
    "metadata": {
     "collapsed": false
    },
    "source": []
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}