UC3MAL101_Uberg_A3.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using plaidml.keras.backend backend.\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "os.environ[\"KERAS_BACKEND\"] = \"plaidml.keras.backend\"\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import cv2\n",
    "import csv\n",
    "import time\n",
    "import gc\n",
    "\n",
    "from keras.models import Sequential, Model, load_model\n",
    "from keras.layers import Dense, Conv2D, MaxPooling2D, Flatten, Dropout, ZeroPadding2D, BatchNormalization, Activation, MaxPool2D, GlobalAveragePooling2D, SeparableConv2D\n",
    "from keras import Input\n",
    "from keras.optimizers import Adam, Nadam\n",
    "from keras.utils import to_categorical, plot_model\n",
    "from keras.callbacks import ModelCheckpoint, EarlyStopping, ReduceLROnPlateau\n",
    "from keras.preprocessing.image import img_to_array, load_img\n",
    "\n",
    "from keras_sequential_ascii import keras2ascii\n",
    "\n",
    "from ann_visualizer.visualize import ann_viz\n",
    "\n",
    "from IPython.display import Image \n",
    "\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "from albumentations import (\n",
    "    HorizontalFlip, IAAPerspective, ShiftScaleRotate, CLAHE, RandomRotate90,\n",
    "    Transpose, ShiftScaleRotate, Blur, OpticalDistortion, GridDistortion, HueSaturationValue,\n",
    "    IAAAdditiveGaussianNoise, GaussNoise, MotionBlur, MedianBlur, IAAPiecewiseAffine,\n",
    "    IAASharpen, IAAEmboss, RandomBrightnessContrast, Flip, OneOf, Compose\n",
    ")\n",
    "\n",
    "#np.set_printoptions(suppress=True)\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "code_folding": [
     0
    ],
    "run_control": {
     "marked": false
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   "outputs": [],
   "source": [
    "def csv_reader_parser(filepath):\n",
    "    df = pd.read_csv(filepath, dtype=str, header=None)\n",
    "    df.columns = [\"image_path\"]\n",
    "    \n",
    "    df[\"label\"] = df[\"image_path\"].map(lambda x:1 if \"positive\" in x else 0)\n",
    "    df[\"category\"]  = df[\"image_path\"].apply(lambda x: x.split(\"/\")[2])\n",
    "    df[\"patient_id\"]  = df[\"image_path\"].apply(lambda x: x.split(\"/\")[3].replace(\"patient\",\"\"))\n",
    "    \n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "code_folding": [
     0
    ]
   },
   "outputs": [],
   "source": [
    "def augmentor(p=0.5):\n",
    "    return Compose([\n",
    "        RandomRotate90(),\n",
    "        Flip(),\n",
    "        Transpose(),\n",
    "        OneOf([\n",
    "            IAAAdditiveGaussianNoise(),\n",
    "            GaussNoise(),\n",
    "        ], p=0.2),\n",
    "        OneOf([\n",
    "            MotionBlur(p=0.2),\n",
    "            MedianBlur(blur_limit=3, p=0.1),\n",
    "            Blur(blur_limit=3, p=0.1),\n",
    "        ], p=0.2),\n",
    "        ShiftScaleRotate(shift_limit=0.0625, scale_limit=0.2, rotate_limit=45, p=0.2),\n",
    "        OneOf([\n",
    "            OpticalDistortion(p=0.3),\n",
    "            GridDistortion(p=0.1),\n",
    "            IAAPiecewiseAffine(p=0.3),\n",
    "        ], p=0.2),\n",
    "        OneOf([\n",
    "            CLAHE(clip_limit=2),\n",
    "            IAASharpen(),\n",
    "            IAAEmboss(),\n",
    "            RandomBrightnessContrast(),\n",
    "        ], p=0.3),\n",
    "        HueSaturationValue(p=0),\n",
    "    ], p=p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "code_folding": [
     0
    ],
    "run_control": {
     "marked": false
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   },
   "outputs": [],
   "source": [
    "def image_processor(dir_name, path_csv, shape=(128, 128), colour=0, scale=False, augment=False):\n",
    "\n",
    "    data = []\n",
    "    transform = augmentor()\n",
    "\n",
    "    # open the csv file containing the image paths\n",
    "    with open(path_csv, \"r\") as path:\n",
    "        # read all the paths from the CSV file\n",
    "        imagepaths = csv.reader(path)\n",
    "        # loop over the images paths\n",
    "        for imagepath in imagepaths:\n",
    "            # create a complete path for an image based on it location on my pc\n",
    "            imagepath = os.path.join(dir_name, imagepath[0])\n",
    "            # read the image as grayscale image, 0=grayscale, 1=colour image, -1=unchanged\n",
    "            image = cv2.imread(imagepath, colour)\n",
    "            # resize the to 128 x 128, you can choose the image size you want here\n",
    "            image = cv2.resize(image, shape)\n",
    "            # creates a training data in matrix form of all the raw pixel values\n",
    "            data.append(image)\n",
    "            if augment:\n",
    "                augmented_image = transform(image=image)['image']\n",
    "                data.append(augmented_image)\n",
    "            \n",
    "    if scale:\n",
    "        # scale the raw pixel intensities to the range [0, 1]\n",
    "        data = np.array(data, dtype=\"float\") / 255.0  \n",
    "\n",
    "    return data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "code_folding": [
     0
    ]
   },
   "outputs": [],
   "source": [
    "def pickler(filename, operation, data=\"\"):\n",
    "    import pickle\n",
    "    if operation == \"save\":\n",
    "        pickle_out = open(f\"{filename}.pickle\", \"wb\")\n",
    "        pickle.dump(data, pickle_out)\n",
    "        pickle_out.close()\n",
    "    elif operation == \"load\":\n",
    "        pickle_in = open(f\"{filename}.pickle\", \"rb\")\n",
    "        data = pickle.load(pickle_in)\n",
    "        \n",
    "    return data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "code_folding": [
     0
    ],
    "run_control": {
     "marked": false
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   "outputs": [],
   "source": [
    "def cm_plot(y_test,\n",
    "            y_pred,\n",
    "            categories=None,\n",
    "            cmap=\"binary\",\n",
    "            cbar=True,\n",
    "            figsize=None,\n",
    "            calculate=False,\n",
    "            legend=False):\n",
    "\n",
    "    cf_matrix = confusion_matrix(y_test_expt, y_pred)\n",
    "    cf_matrix_normal = cf_matrix.astype('float') / cf_matrix.sum(axis=1)[:, np.newaxis]\n",
    "\n",
    "    if categories is None:\n",
    "        categories = [0, 1]\n",
    "\n",
    "    # Code to generate text inside each square\n",
    "    group_names = [\"TN\", \"FP\", \"FN\", \"TP\"]\n",
    "\n",
    "    group_counts = [\"{0:0.0f}\".format(value) for value in\n",
    "                    cf_matrix.flatten()]\n",
    "\n",
    "    group_percentages = [\"{0:.2%}\".format(value) for value in\n",
    "                         cf_matrix_normal.flatten()]\n",
    "\n",
    "    labels = [f\"{v1}\\n{v2}\\n{v3}\" for v1, v2, v3 in\n",
    "              zip(group_names, group_counts, group_percentages)]\n",
    "\n",
    "    labels = np.asarray(labels).reshape(2, 2)\n",
    "\n",
    "    stats_text = \"\"\n",
    "\n",
    "    if calculate:\n",
    "        # Metrics for Binary Confusion Matrices\n",
    "        TP = (np.diag(cf_matrix))[1]\n",
    "        FN = (cf_matrix.sum(axis=1) - np.diag(cf_matrix))[1]\n",
    "        FP = (cf_matrix.sum(axis=0) - np.diag(cf_matrix))[1]\n",
    "        TN = cf_matrix.sum() - (FP + FN + TP)\n",
    "        # Sensitivity, hit rate, recall, or true positive rate\n",
    "        TPR = TP/(TP+FN)\n",
    "        # Specificity or true negative rate\n",
    "        TNR = TN/(TN+FP)\n",
    "        # Precision or positive predictive value\n",
    "        PPV = TP/(TP+FP)\n",
    "        # Negative predictive value\n",
    "        NPV = TN/(TN+FN)\n",
    "        # Fall out or false positive rate\n",
    "        FPR = FP/(FP+TN)\n",
    "        # False negative rate\n",
    "        FNR = FN/(TP+FN)\n",
    "        # False discovery rate\n",
    "        FDR = FP/(TP+FP)\n",
    "        # F1 score is the harmonic mean of precision and recall\n",
    "        F1 = 2 * (PPV * TPR)/(PPV + TPR)\n",
    "        # Overall accuracy\n",
    "        ACC = (TP+TN)/(TP+FP+FN+TN)\n",
    "\n",
    "        if legend:\n",
    "            print(f\"\"\"\n",
    "                # True Positive\n",
    "                TP = np.diag(cf_matrix) : {TP:.2f}\n",
    "\n",
    "                # False Negative, Type II Error\n",
    "                FN = cf_matrix.sum(axis=1) - np.diag(cf_matrix) : {FN:.2f}\n",
    "\n",
    "                # False Positive, Type I Error\n",
    "                FP = cf_matrix.sum(axis=0) - np.diag(cf_matrix) : {FP:.2f}\n",
    "\n",
    "                # True Negative\n",
    "                TN = cf_matrix.sum() - (FP + FN + TP) : {TN:.2f}\n",
    "\n",
    "                # Sensitivity, hit rate, recall, or true positive rate\n",
    "                TPR = TP/(TP+FN) : {TPR:.2f}\n",
    "\n",
    "                # Specificity, true negative rate or negative recall\n",
    "                TNR = TN/(TN+FP) : {TNR:.2f}\n",
    "\n",
    "                # Precision or positive predictive value\n",
    "                PPV = TP/(TP+FP) : {PPV:.2f}\n",
    "\n",
    "                # Negative predictive value\n",
    "                NPV = TN/(TN+FN) : {NPV:.2f}\n",
    "\n",
    "                # Fall out or false positive rate\n",
    "                FPR = FP/(FP+TN) : {FPR:.2f}\n",
    "\n",
    "                # False negative rate\n",
    "                FNR = FN/(TP+FN) : {FNR:.2f}\n",
    "\n",
    "                # False discovery rate\n",
    "                FDR = FP/(TP+FP) : {FDR:.2f}\n",
    "\n",
    "                # F1 score is the harmonic mean of positive predictive value\n",
    "                #  and sensitivity\n",
    "                F1 = 2 * (PPV * TPR)/(PPV + TPR) : {F1:.2f}\n",
    "\n",
    "                # Overall accuracy\n",
    "                ACC = (TP+TN)/(TP+FP+FN+TN) : {ACC:.2f}\n",
    "                \"\"\")\n",
    "\n",
    "        stats_text = f\"\\n\"\\\n",
    "            f\"TPR: {TPR:.2f}\\n\"\\\n",
    "            f\"TNR: {TNR:.2f}\\n\"\\\n",
    "            f\"PPV: {PPV:.2f}\\n\"\\\n",
    "            f\"NPV: {NPV:.2f}\\n\"\\\n",
    "            f\"FPR: {FPR:.2f}\\n\"\\\n",
    "            f\"FNR: {FNR:.2f}\\n\"\\\n",
    "            f\"FDR: {FDR:.2f}\\n\"\\\n",
    "            f\"F1 : {F1:.2f}\\n\"\\\n",
    "            f\"ACC: {ACC:.2f}\"\n",
    "\n",
    "    if figsize is None:\n",
    "        # Get default figure size if not set\n",
    "        figsize = plt.rcParams.get(\"figure.figsize\")\n",
    "    else:\n",
    "        plt.figure(figsize=figsize)\n",
    "\n",
    "    font_size = 12\n",
    "\n",
    "    ax = sns.heatmap(cf_matrix, annot=labels, annot_kws={\"size\": font_size},\n",
    "                     fmt=\"\", cmap=cmap, cbar=cbar, xticklabels=categories,\n",
    "                     yticklabels=categories)\n",
    "\n",
    "    ax.set_xticklabels(ax.get_xticklabels(), fontsize=font_size)\n",
    "    ax.set_yticklabels(ax.get_yticklabels(), fontsize=font_size)\n",
    "\n",
    "    cbar = ax.collections[0].colorbar\n",
    "    cbar.ax.tick_params(labelsize=font_size)\n",
    "\n",
    "    plt.ylabel(\"True label\", fontsize=font_size)\n",
    "    plt.xlabel(\"Predicted label\\n\" + stats_text, fontsize=font_size)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "code_folding": [
     0
    ],
    "run_control": {
     "marked": false
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   },
   "outputs": [],
   "source": [
    "def data_setup(dir_name, train_path, teat_path, preprocessed=True, shape=(128, 128), binary=False, augment=False):\n",
    "    if preprocessed:\n",
    "        print(\"[INFO] Loading preprocessed file(s)\")\n",
    "        X_train = pickler(\"X_train\", \"load\")\n",
    "        y_train = pickler(\"y_train\", \"load\")\n",
    "        X_test = pickler(\"X_test\", \"load\")\n",
    "        y_test = pickler(\"y_test\", \"load\")\n",
    "    \n",
    "        if binary:\n",
    "            binary = False\n",
    "            print(\"[INFO] Can only be used on dataload\")\n",
    "            y_test_expt = y_test\n",
    "        else:\n",
    "            y_test_expt = np.array([y_test[x][1] for x in range(len(y_test))], dtype=int)\n",
    "        \n",
    "    else:\n",
    "        train_image_paths_csv = \"MURA/MURA-v1.1/train_image_paths.csv\"\n",
    "        test_image_paths_csv = \"MURA/MURA-v1.1/valid_image_paths.csv\"\n",
    "\n",
    "        print(\"[INFO] Loading images from CSV filepaths\")\n",
    "        X_train = image_processor(\"MURA\", train_image_paths_csv, shape=shape, scale=True, augment=augment)\n",
    "        X_test = image_processor(\"MURA\", test_image_paths_csv, shape=shape, scale=True)\n",
    "\n",
    "        print(f\"[INFO] Reshaping images to {shape}\")\n",
    "        X_train = X_train.reshape((X_train.shape[0], *shape, 1))\n",
    "        X_test = X_test.reshape((X_test.shape[0], *shape, 1))\n",
    "\n",
    "        train_image_paths = csv_reader_parser(train_image_paths_csv)\n",
    "        test_image_paths = csv_reader_parser(test_image_paths_csv)\n",
    "        \n",
    "        temp_y_train = np.array([])\n",
    "\n",
    "        if binary:\n",
    "            y_train = train_image_paths.label.values\n",
    "            y_test = test_image_paths.label.values\n",
    "            if augment:\n",
    "                temp_y_test = np.array([], dtype=\"float32\")\n",
    "                for i in range(len(y_train)):\n",
    "                    temp_y_train = np.append(temp_y_train, [y_train[i]])\n",
    "                    temp_y_train = np.append(temp_y_train, [y_train[i]])\n",
    "                temp_y_train = temp_y_train.reshape(-1,2)\n",
    "\n",
    "                y_train = temp_y_train\n",
    "            y_test_expt = y_test\n",
    "            \n",
    "        else:\n",
    "            y_train = to_categorical(train_image_paths.label.values)\n",
    "            y_test = to_categorical(test_image_paths.label.values)\n",
    "            if augment:\n",
    "                temp_y_test = np.array([], dtype=\"float32\")\n",
    "                for i in range(len(y_train)):\n",
    "                    temp_y_train = np.append(temp_y_train, [y_train[i]])\n",
    "                    temp_y_train = np.append(temp_y_train, [y_train[i]])\n",
    "                temp_y_train = temp_y_train.reshape(-1,2)\n",
    "\n",
    "                y_train = temp_y_train\n",
    "            y_test_expt = np.array([y_test[x][1] for x in range(len(y_test))], dtype=int)\n",
    "\n",
    "        print(\"[INFO] Saving to preprocessed file(s)\")\n",
    "        X_train = pickler(\"X_train\", \"save\", X_train)\n",
    "        y_train = pickler(\"y_train\", \"save\", y_train)\n",
    "        X_test = pickler(\"X_test\", \"save\", X_test)\n",
    "        y_test = pickler(\"y_test\", \"save\", y_test)\n",
    "        \n",
    "        # Garbage collection\n",
    "        del train_image_paths_csv\n",
    "        del test_image_paths_csv\n",
    "        del train_image_paths\n",
    "        del test_image_paths\n",
    "        gc.collect()\n",
    "\n",
    "    print(\"[INFO] Done!\")\n",
    "    return X_train, y_train, X_test, y_test, y_test_expt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "code_folding": [
     0
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    "run_control": {
     "marked": false
    }
   },
   "outputs": [],
   "source": [
    "def prepare_img(filepath, show=True, img_size = (128, 128)):\n",
    "    img_array = cv2.imread(filepath, cv2.IMREAD_GRAYSCALE)\n",
    "    new_array = cv2.resize(img_array, img_size)\n",
    "    \n",
    "    if show:\n",
    "        plt.imshow(img_array, cmap=\"Greys\")\n",
    "        plt.axis(\"off\")\n",
    "        plt.show()\n",
    "    \n",
    "    return new_array.reshape(-1, *img_size, 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "code_folding": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] Loading images from CSV filepaths\n",
      "[INFO] Reshaping images to (128, 128)\n",
      "[INFO] Saving to preprocessed file(s)\n",
      "[INFO] Done!\n"
     ]
    }
   ],
   "source": [
    "X_train, y_train, X_test, y_test, y_test_expt = data_setup(\n",
    "    \"MURA\",\n",
    "    \"MURA/MURA-v1.1/train_image_paths.csv\",\n",
    "    \"MURA/MURA-v1.1/valid_image_paths.csv\",\n",
    "    preprocessed=True,\n",
    "    shape=(128,128),\n",
    "    binary=False,\n",
    "    augment=False\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(36808, 128, 128, 1)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(36808, 2)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(3197, 128, 128, 1)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(3197, 2)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(3197,)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(X_train.shape)\n",
    "display(y_train.shape)\n",
    "display(X_test.shape)\n",
    "display(y_test.shape)\n",
    "display(y_test_expt.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras.backend import clear_session\n",
    "clear_session()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:plaidml:Opening device \"metal_amd_radeon_pro_560.0\"\n"
     ]
    }
   ],
   "source": [
    "# Collective hyperparameters\n",
    "epochs = 50\n",
    "batch_size = 32  # Should be a factor of 2.\n",
    "validation_split = 0.1\n",
    "\n",
    "learning_rate = .001\n",
    "learning_rate_reduction_factor = 0.5\n",
    "learning_rate_min = 0.000001\n",
    "learning_rate_patience = 2\n",
    "\n",
    "#b1 = 0.09\n",
    "#b2 = 0.9995\n",
    "#epsi = 1e-07\n",
    "\n",
    "early_stop_patience = epochs/10  # How many times in a row.\n",
    "\n",
    "# optimizer = Nadam(lr=learning_rate, beta_1=b1, beta_2=b2, epsilon=epsi)\n",
    "optimizer = Adam(lr=learning_rate) \n",
    "loss_function = \"categorical_crossentropy\"\n",
    "metrics = [\"accuracy\"]\n",
    "\n",
    "categories = [\"Normal\", \"Abnormal\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "checkpoint_filepath = \"checkpoint\"\n",
    "\n",
    "model_checkpoint = ModelCheckpoint(\n",
    "    filepath=checkpoint_filepath,\n",
    "    save_weights_only=False,\n",
    "    monitor=\"val_loss\",\n",
    "    verbose=1,\n",
    "    mode=\"auto\",\n",
    "    save_best_only=True)\n",
    "\n",
    "lr_reduce = ReduceLROnPlateau(\n",
    "    monitor=\"val_loss\",\n",
    "    factor=learning_rate_reduction_factor,\n",
    "    min_lr=learning_rate_min,\n",
    "    patience=3,\n",
    "    verbose=1,\n",
    "    mode=\"auto\")\n",
    "\n",
    "early_stop = EarlyStopping(\n",
    "    monitor=\"val_loss\",    \n",
    "    patience=early_stop_patience,\n",
    "    mode=\"auto\",\n",
    "    verbose=1)\n",
    "    # min_delta=0.1,"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Split into training and validation set\n",
    "X_train, X_val, y_train, y_val = train_test_split(X_train, y_train, test_size=validation_split, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(128, 128, 1)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train.shape[1:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "run_control": {
     "marked": false
    }
   },
   "outputs": [],
   "source": [
    "model = Sequential()\n",
    "\n",
    "# the 2 first values in in input shape is the width and height of the image, the last is the color channel.\n",
    "first_layer = X_train.shape[1:]  # <-- Not hidden, not counted\n",
    "\n",
    "# ### Conv2D ###\n",
    "# filters is the number of filters that is learning.\n",
    "# The kernel_size is the filter/matrix size\n",
    "# The stride is the actual convolving.\n",
    "# padding = \"same\" keeps the origional dimensionality\n",
    "\n",
    "model.add(Conv2D(32, kernel_size=(3,3), activation=\"relu\", padding=\"same\", input_shape=first_layer))\n",
    "model.add(MaxPooling2D(pool_size=(4,4)))\n",
    "model.add(Dropout(0.15))\n",
    "\n",
    "model.add(Conv2D(64, kernel_size=(3,3), activation=\"relu\", padding=\"same\"))\n",
    "model.add(MaxPooling2D(pool_size=(2,2)))\n",
    "model.add(Dropout(0.15))\n",
    "\n",
    "model.add(Conv2D(64, kernel_size=(3,3), activation=\"relu\", padding=\"same\"))\n",
    "model.add(MaxPooling2D(pool_size=(2,2)))\n",
    "model.add(Dropout(0.15))\n",
    "\n",
    "# First dense layer in model has to have a flatten\n",
    "model.add(Flatten())\n",
    "\n",
    "model.add(Dense(512, activation=\"relu\"))\n",
    "model.add(Dropout(0.5))\n",
    "\n",
    "# Dropout should not be added to last hidden layer\n",
    "model.add(Dense(256, activation=\"relu\"))\n",
    "\n",
    "### Will give same result ###\n",
    "## Binary only\n",
    "# When using loss=\"binary_crossentropy\"\n",
    "# model.add(Dense(1, activation=\"sigmoid\"))\n",
    "\n",
    "## Can also be used when more than two classes\n",
    "# When using loss=\"categorical_crossentropy\"\n",
    "model.add(Dense(2, activation=\"softmax\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.compile(optimizer, loss=loss_function, metrics=metrics)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train on 33127 samples, validate on 3681 samples\n",
      "Epoch 1/50\n",
      " - 94s - loss: 0.6663 - acc: 0.5940 - val_loss: 0.6512 - val_acc: 0.6039\n",
      "\n",
      "Epoch 00001: val_loss improved from inf to 0.65118, saving model to checkpoint\n",
      "Epoch 2/50\n",
      " - 88s - loss: 0.6558 - acc: 0.5996 - val_loss: 0.6479 - val_acc: 0.6134\n",
      "\n",
      "Epoch 00002: val_loss improved from 0.65118 to 0.64794, saving model to checkpoint\n",
      "Epoch 3/50\n",
      " - 87s - loss: 0.6507 - acc: 0.6105 - val_loss: 0.6390 - val_acc: 0.6387\n",
      "\n",
      "Epoch 00003: val_loss improved from 0.64794 to 0.63904, saving model to checkpoint\n",
      "Epoch 4/50\n",
      " - 88s - loss: 0.6429 - acc: 0.6215 - val_loss: 0.6435 - val_acc: 0.6248\n",
      "\n",
      "Epoch 00004: val_loss did not improve from 0.63904\n",
      "Epoch 5/50\n",
      " - 88s - loss: 0.6380 - acc: 0.6250 - val_loss: 0.6341 - val_acc: 0.6425\n",
      "\n",
      "Epoch 00005: val_loss improved from 0.63904 to 0.63407, saving model to checkpoint\n",
      "Epoch 6/50\n",
      " - 88s - loss: 0.6292 - acc: 0.6391 - val_loss: 0.6150 - val_acc: 0.6620\n",
      "\n",
      "Epoch 00006: val_loss improved from 0.63407 to 0.61499, saving model to checkpoint\n",
      "Epoch 7/50\n",
      " - 88s - loss: 0.6256 - acc: 0.6431 - val_loss: 0.6141 - val_acc: 0.6580\n",
      "\n",
      "Epoch 00007: val_loss improved from 0.61499 to 0.61406, saving model to checkpoint\n",
      "Epoch 8/50\n",
      " - 88s - loss: 0.6160 - acc: 0.6501 - val_loss: 0.6054 - val_acc: 0.6710\n",
      "\n",
      "Epoch 00008: val_loss improved from 0.61406 to 0.60545, saving model to checkpoint\n",
      "Epoch 9/50\n",
      " - 89s - loss: 0.6112 - acc: 0.6596 - val_loss: 0.6013 - val_acc: 0.6759\n",
      "\n",
      "Epoch 00009: val_loss improved from 0.60545 to 0.60129, saving model to checkpoint\n",
      "Epoch 10/50\n",
      " - 89s - loss: 0.6056 - acc: 0.6639 - val_loss: 0.6040 - val_acc: 0.6873\n",
      "\n",
      "Epoch 00010: val_loss did not improve from 0.60129\n",
      "Epoch 11/50\n",
      " - 88s - loss: 0.6020 - acc: 0.6677 - val_loss: 0.5869 - val_acc: 0.6887\n",
      "\n",
      "Epoch 00011: val_loss improved from 0.60129 to 0.58687, saving model to checkpoint\n",
      "Epoch 12/50\n",
      " - 88s - loss: 0.5978 - acc: 0.6728 - val_loss: 0.5792 - val_acc: 0.7012\n",
      "\n",
      "Epoch 00012: val_loss improved from 0.58687 to 0.57915, saving model to checkpoint\n",
      "Epoch 13/50\n",
      " - 88s - loss: 0.5945 - acc: 0.6768 - val_loss: 0.5823 - val_acc: 0.6946\n",
      "\n",
      "Epoch 00013: val_loss did not improve from 0.57915\n",
      "Epoch 14/50\n",
      " - 89s - loss: 0.5915 - acc: 0.6786 - val_loss: 0.5795 - val_acc: 0.6960\n",
      "\n",
      "Epoch 00014: val_loss did not improve from 0.57915\n",
      "Epoch 15/50\n",
      " - 89s - loss: 0.5886 - acc: 0.6807 - val_loss: 0.5823 - val_acc: 0.6979\n",
      "\n",
      "Epoch 00015: val_loss did not improve from 0.57915\n",
      "\n",
      "Epoch 00015: ReduceLROnPlateau reducing learning rate to 0.0005000000237487257.\n",
      "Epoch 16/50\n",
      " - 89s - loss: 0.5757 - acc: 0.6929 - val_loss: 0.5628 - val_acc: 0.7118\n",
      "\n",
      "Epoch 00016: val_loss improved from 0.57915 to 0.56285, saving model to checkpoint\n",
      "Epoch 17/50\n",
      " - 89s - loss: 0.5685 - acc: 0.6996 - val_loss: 0.5671 - val_acc: 0.7050\n",
      "\n",
      "Epoch 00017: val_loss did not improve from 0.56285\n",
      "Epoch 18/50\n",
      " - 88s - loss: 0.5693 - acc: 0.6992 - val_loss: 0.5641 - val_acc: 0.7120\n",
      "\n",
      "Epoch 00018: val_loss did not improve from 0.56285\n",
      "Epoch 19/50\n",
      " - 88s - loss: 0.5645 - acc: 0.7025 - val_loss: 0.5618 - val_acc: 0.7175\n",
      "\n",
      "Epoch 00019: val_loss improved from 0.56285 to 0.56182, saving model to checkpoint\n",
      "Epoch 20/50\n",
      " - 88s - loss: 0.5615 - acc: 0.7046 - val_loss: 0.5642 - val_acc: 0.7063\n",
      "\n",
      "Epoch 00020: val_loss did not improve from 0.56182\n",
      "Epoch 21/50\n",
      " - 88s - loss: 0.5597 - acc: 0.7084 - val_loss: 0.5615 - val_acc: 0.7131\n",
      "\n",
      "Epoch 00021: val_loss improved from 0.56182 to 0.56148, saving model to checkpoint\n",
      "Epoch 22/50\n",
      " - 88s - loss: 0.5583 - acc: 0.7073 - val_loss: 0.5612 - val_acc: 0.7112\n",
      "\n",
      "Epoch 00022: val_loss improved from 0.56148 to 0.56124, saving model to checkpoint\n",
      "Epoch 23/50\n",
      " - 87s - loss: 0.5571 - acc: 0.7099 - val_loss: 0.5597 - val_acc: 0.7153\n",
      "\n",
      "Epoch 00023: val_loss improved from 0.56124 to 0.55966, saving model to checkpoint\n",
      "Epoch 24/50\n",
      " - 88s - loss: 0.5545 - acc: 0.7100 - val_loss: 0.5637 - val_acc: 0.7096\n",
      "\n",
      "Epoch 00024: val_loss did not improve from 0.55966\n",
      "Epoch 25/50\n",
      " - 88s - loss: 0.5545 - acc: 0.7094 - val_loss: 0.5628 - val_acc: 0.7137\n",
      "\n",
      "Epoch 00025: val_loss did not improve from 0.55966\n",
      "Epoch 26/50\n",
      " - 88s - loss: 0.5533 - acc: 0.7088 - val_loss: 0.5605 - val_acc: 0.7134\n",
      "\n",
      "Epoch 00026: val_loss did not improve from 0.55966\n",
      "\n",
      "Epoch 00026: ReduceLROnPlateau reducing learning rate to 0.0002500000118743628.\n",
      "Epoch 27/50\n",
      " - 87s - loss: 0.5421 - acc: 0.7214 - val_loss: 0.5514 - val_acc: 0.7213\n",
      "\n",
      "Epoch 00027: val_loss improved from 0.55966 to 0.55136, saving model to checkpoint\n",
      "Epoch 28/50\n",
      " - 87s - loss: 0.5403 - acc: 0.7210 - val_loss: 0.5595 - val_acc: 0.7077\n",
      "\n",
      "Epoch 00028: val_loss did not improve from 0.55136\n",
      "Epoch 29/50\n",
      " - 87s - loss: 0.5374 - acc: 0.7252 - val_loss: 0.5567 - val_acc: 0.7134\n",
      "\n",
      "Epoch 00029: val_loss did not improve from 0.55136\n",
      "Epoch 30/50\n",
      " - 88s - loss: 0.5362 - acc: 0.7242 - val_loss: 0.5485 - val_acc: 0.7226\n",
      "\n",
      "Epoch 00030: val_loss improved from 0.55136 to 0.54848, saving model to checkpoint\n",
      "Epoch 31/50\n",
      " - 89s - loss: 0.5335 - acc: 0.7273 - val_loss: 0.5520 - val_acc: 0.7194\n",
      "\n",
      "Epoch 00031: val_loss did not improve from 0.54848\n",
      "Epoch 32/50\n",
      " - 89s - loss: 0.5341 - acc: 0.7287 - val_loss: 0.5503 - val_acc: 0.7196\n",
      "\n",
      "Epoch 00032: val_loss did not improve from 0.54848\n",
      "Epoch 33/50\n",
      " - 88s - loss: 0.5328 - acc: 0.7274 - val_loss: 0.5481 - val_acc: 0.7264\n",
      "\n",
      "Epoch 00033: val_loss improved from 0.54848 to 0.54807, saving model to checkpoint\n",
      "Epoch 34/50\n",
      " - 88s - loss: 0.5291 - acc: 0.7285 - val_loss: 0.5470 - val_acc: 0.7275\n",
      "\n",
      "Epoch 00034: val_loss improved from 0.54807 to 0.54704, saving model to checkpoint\n",
      "Epoch 35/50\n",
      " - 88s - loss: 0.5303 - acc: 0.7296 - val_loss: 0.5505 - val_acc: 0.7270\n",
      "\n",
      "Epoch 00035: val_loss did not improve from 0.54704\n",
      "Epoch 36/50\n",
      " - 88s - loss: 0.5268 - acc: 0.7304 - val_loss: 0.5443 - val_acc: 0.7338\n",
      "\n",
      "Epoch 00036: val_loss improved from 0.54704 to 0.54435, saving model to checkpoint\n",
      "Epoch 37/50\n",
      " - 88s - loss: 0.5245 - acc: 0.7331 - val_loss: 0.5454 - val_acc: 0.7343\n",
      "\n",
      "Epoch 00037: val_loss did not improve from 0.54435\n",
      "Epoch 38/50\n",
      " - 88s - loss: 0.5266 - acc: 0.7329 - val_loss: 0.5450 - val_acc: 0.7324\n",
      "\n",
      "Epoch 00038: val_loss did not improve from 0.54435\n",
      "Epoch 39/50\n",
      " - 88s - loss: 0.5215 - acc: 0.7372 - val_loss: 0.5443 - val_acc: 0.7289\n",
      "\n",
      "Epoch 00039: val_loss improved from 0.54435 to 0.54430, saving model to checkpoint\n",
      "\n",
      "Epoch 00039: ReduceLROnPlateau reducing learning rate to 0.0001250000059371814.\n",
      "Epoch 40/50\n",
      " - 88s - loss: 0.5160 - acc: 0.7394 - val_loss: 0.5422 - val_acc: 0.7302\n",
      "\n",
      "Epoch 00040: val_loss improved from 0.54430 to 0.54217, saving model to checkpoint\n",
      "Epoch 41/50\n",
      " - 88s - loss: 0.5188 - acc: 0.7352 - val_loss: 0.5452 - val_acc: 0.7300\n",
      "\n",
      "Epoch 00041: val_loss did not improve from 0.54217\n",
      "Epoch 42/50\n",
      " - 88s - loss: 0.5156 - acc: 0.7387 - val_loss: 0.5462 - val_acc: 0.7297\n",
      "\n",
      "Epoch 00042: val_loss did not improve from 0.54217\n",
      "Epoch 43/50\n",
      " - 89s - loss: 0.5130 - acc: 0.7415 - val_loss: 0.5442 - val_acc: 0.7272\n",
      "\n",
      "Epoch 00043: val_loss did not improve from 0.54217\n",
      "\n",
      "Epoch 00043: ReduceLROnPlateau reducing learning rate to 6.25000029685907e-05.\n",
      "Epoch 44/50\n",
      " - 89s - loss: 0.5159 - acc: 0.7407 - val_loss: 0.5443 - val_acc: 0.7297\n",
      "\n",
      "Epoch 00044: val_loss did not improve from 0.54217\n",
      "Epoch 45/50\n",
      " - 89s - loss: 0.5109 - acc: 0.7416 - val_loss: 0.5435 - val_acc: 0.7291\n",
      "\n",
      "Epoch 00045: val_loss did not improve from 0.54217\n",
      "Epoch 00045: early stopping\n"
     ]
    }
   ],
   "source": [
    "# history = model.fit(X_train, y_train, batch_size=batch_size, epochs=epochs, validation_split=validation_split, verbose=2, callbacks = [model_checkpoint, lr_reduce, early_stop])\n",
    "\n",
    "history = model.fit(X_train, y_train, batch_size=batch_size, epochs=epochs, validation_data=(X_val, y_val), verbose=2, callbacks = [model_checkpoint, lr_reduce, early_stop])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "#model.save(Best_model_path)\n",
    "y_pred = model.predict_classes(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3197/3197 [==============================] - 2s 491us/step\n",
      "Evaluation loss: 0.6147081267658456\n",
      "Evaluation accuracy: 0.6671879885716478\n"
     ]
    }
   ],
   "source": [
    "eval_loss, eval_accuracy = model.evaluate(X_test, y_test, batch_size=batch_size, verbose=1)\n",
    "\n",
    "print(\"Evaluation loss:\", eval_loss)\n",
    "print(\"Evaluation accuracy:\", eval_accuracy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "                # True Positive\n",
      "                TP = np.diag(cf_matrix) : 747.00\n",
      "\n",
      "                # False Negative, Type II Error\n",
      "                FN = cf_matrix.sum(axis=1) - np.diag(cf_matrix) : 783.00\n",
      "\n",
      "                # False Positive, Type I Error\n",
      "                FP = cf_matrix.sum(axis=0) - np.diag(cf_matrix) : 281.00\n",
      "\n",
      "                # True Negative\n",
      "                TN = cf_matrix.sum() - (FP + FN + TP) : 1386.00\n",
      "\n",
      "                # Sensitivity, hit rate, recall, or true positive rate\n",
      "                TPR = TP/(TP+FN) : 0.49\n",
      "\n",
      "                # Specificity, true negative rate or negative recall\n",
      "                TNR = TN/(TN+FP) : 0.83\n",
      "\n",
      "                # Precision or positive predictive value\n",
      "                PPV = TP/(TP+FP) : 0.73\n",
      "\n",
      "                # Negative predictive value\n",
      "                NPV = TN/(TN+FN) : 0.64\n",
      "\n",
      "                # Fall out or false positive rate\n",
      "                FPR = FP/(FP+TN) : 0.17\n",
      "\n",
      "                # False negative rate\n",
      "                FNR = FN/(TP+FN) : 0.51\n",
      "\n",
      "                # False discovery rate\n",
      "                FDR = FP/(TP+FP) : 0.27\n",
      "\n",
      "                # F1 score is the harmonic mean of positive predictive value\n",
      "                #  and sensitivity\n",
      "                F1 = 2 * (PPV * TPR)/(PPV + TPR) : 0.58\n",
      "\n",
      "                # Overall accuracy\n",
      "                ACC = (TP+TN)/(TP+FP+FN+TN) : 0.67\n",
      "                \n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cm_plot(y_test_expt, y_pred, calculate=True, categories=(\"Negative\", \"Positive\"), legend=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "           OPERATION           DATA DIMENSIONS   WEIGHTS(N)   WEIGHTS(%)\n",
      "\n",
      "               Input   #####    128  128    1\n",
      "              Conv2D    \\|/  -------------------       320     0.1%\n",
      "                relu   #####    128  128   32\n",
      "        MaxPooling2D   Y max -------------------         0     0.0%\n",
      "                       #####     32   32   32\n",
      "             Dropout    | || -------------------         0     0.0%\n",
      "                       #####     32   32   32\n",
      "              Conv2D    \\|/  -------------------     18496     5.8%\n",
      "                relu   #####     32   32   64\n",
      "        MaxPooling2D   Y max -------------------         0     0.0%\n",
      "                       #####      8    8   64\n",
      "             Dropout    | || -------------------         0     0.0%\n",
      "                       #####      8    8   64\n",
      "              Conv2D    \\|/  -------------------     36928    11.6%\n",
      "                relu   #####      8    8   64\n",
      "        MaxPooling2D   Y max -------------------         0     0.0%\n",
      "                       #####      2    2   64\n",
      "             Dropout    | || -------------------         0     0.0%\n",
      "                       #####      2    2   64\n",
      "             Flatten   ||||| -------------------         0     0.0%\n",
      "                       #####         256\n",
      "               Dense   XXXXX -------------------    131584    41.2%\n",
      "                relu   #####         512\n",
      "             Dropout    | || -------------------         0     0.0%\n",
      "                       #####         512\n",
      "               Dense   XXXXX -------------------    131328    41.1%\n",
      "                relu   #####         256\n",
      "               Dense   XXXXX -------------------       514     0.2%\n",
      "             softmax   #####           2\n"
     ]
    }
   ],
   "source": [
    "keras2ascii(model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "conv2d_1 (Conv2D)            (None, 128, 128, 32)      320       \n",
      "_________________________________________________________________\n",
      "max_pooling2d_1 (MaxPooling2 (None, 32, 32, 32)        0         \n",
      "_________________________________________________________________\n",
      "dropout_1 (Dropout)          (None, 32, 32, 32)        0         \n",
      "_________________________________________________________________\n",
      "conv2d_2 (Conv2D)            (None, 32, 32, 64)        18496     \n",
      "_________________________________________________________________\n",
      "max_pooling2d_2 (MaxPooling2 (None, 8, 8, 64)          0         \n",
      "_________________________________________________________________\n",
      "dropout_2 (Dropout)          (None, 8, 8, 64)          0         \n",
      "_________________________________________________________________\n",
      "conv2d_3 (Conv2D)            (None, 8, 8, 64)          36928     \n",
      "_________________________________________________________________\n",
      "max_pooling2d_3 (MaxPooling2 (None, 2, 2, 64)          0         \n",
      "_________________________________________________________________\n",
      "dropout_3 (Dropout)          (None, 2, 2, 64)          0         \n",
      "_________________________________________________________________\n",
      "flatten_1 (Flatten)          (None, 256)               0         \n",
      "_________________________________________________________________\n",
      "dense_1 (Dense)              (None, 512)               131584    \n",
      "_________________________________________________________________\n",
      "dropout_4 (Dropout)          (None, 512)               0         \n",
      "_________________________________________________________________\n",
      "dense_2 (Dense)              (None, 256)               131328    \n",
      "_________________________________________________________________\n",
      "dense_3 (Dense)              (None, 2)                 514       \n",
      "=================================================================\n",
      "Total params: 319,170\n",
      "Trainable params: 319,170\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "with open(\"last_model_run/model_summary.txt\", \"w\") as writer:\n",
    "    model.summary(print_fn=lambda x: writer.write(x + '\\n'))\n",
    "\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_model(model, show_shapes=True, to_file=\"last_model_run/model.png\")\n",
    "Image(\"model.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "ann_viz(model, title=\"MURA\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "lbl_org = [x for x in range(epochs)]\n",
    "lbl_new = [x + 1 for x in range(epochs)]\n",
    "\n",
    "# list all data in history\n",
    "#print(history.history.keys())\n",
    "# summarize history for accuracy\n",
    "plt.figure(figsize=(14, 8))\n",
    "plt.plot(history.history[\"acc\"], color=\"g\", linestyle=\"dashed\", marker=\"o\", markerfacecolor=\"g\", markersize=5)\n",
    "plt.plot(history.history[\"val_acc\"], color=\"b\", linestyle=\"dashed\", marker=\"o\", markerfacecolor=\"b\", markersize=5)\n",
    "plt.title(\"model accuracy\")\n",
    "plt.ylabel(\"accuracy\")\n",
    "plt.xlabel(\"epoch\")\n",
    "plt.legend([\"train_acc\", \"val_acc\"]) #, loc=\"upper left\")\n",
    "plt.xlim(-.25, (max(lbl_org) + 0.25))\n",
    "plt.xticks(lbl_org, lbl_new)\n",
    "plt.ylim(0, 1)\n",
    "plt.grid()\n",
    "plt.savefig(\"last_model_run/model accuracy\")\n",
    "plt.show()\n",
    "plt.close()\n",
    "\n",
    "\n",
    "max_loss = max(max(history.history[\"loss\"]), max(history.history[\"val_loss\"]))\n",
    "# summarize history for loss\n",
    "plt.figure(figsize=(14, 8))\n",
    "plt.plot(history.history[\"loss\"], color=\"g\", linestyle=\"dashed\", marker=\"o\", markerfacecolor=\"g\", markersize=5)\n",
    "plt.plot(history.history[\"val_loss\"], color=\"b\", linestyle=\"dashed\", marker=\"o\", markerfacecolor=\"b\", markersize=5)\n",
    "plt.title(\"model loss\")\n",
    "plt.ylabel(\"loss\")\n",
    "plt.xlabel(\"epoch\")\n",
    "plt.legend([\"train_loss\", \"val_loss\"]) #, loc=\"upper left\")\n",
    "plt.xlim(-.25, (max(lbl_org) + 0.25))\n",
    "plt.xticks(lbl_org, lbl_new)\n",
    "if max_loss <= 1:\n",
    "    plt.ylim(0,1)\n",
    "else:\n",
    "    plt.ylim(0, (max_loss + (max_loss *.1)))\n",
    "plt.grid()\n",
    "plt.savefig(\"last_model_run/model loss\")\n",
    "plt.show()\n",
    "plt.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2133\n",
      "3197\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0.6672"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Manual test\n",
    "counter = 0\n",
    "for i in range(len(y_pred)):\n",
    "    if y_test_expt[i] == y_pred[i]:\n",
    "        counter += 1\n",
    "\n",
    "print(counter)\n",
    "print(len(y_pred))\n",
    "round((counter / len(y_pred)), 4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "cell_style": "center",
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Class: Normal 100.00000%\n"
     ]
    }
   ],
   "source": [
    "prediction = model.predict_classes([prepare_img(\"test/evan_l.jpeg\")])\n",
    "pro = model.predict_proba([prepare_img(\"test/evan_l.jpeg\", show=False)])\n",
    "print(f\"Class: {categories[prediction[0]]} {max(pro[0][0], pro[0][1]):.5%}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "cell_style": "center",
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Class: Normal 100.00000%\n"
     ]
    }
   ],
   "source": [
    "prediction = model.predict_classes([prepare_img(\"test/evan_f.jpeg\")])\n",
    "pro = model.predict_proba([prepare_img(\"test/evan_f.jpeg\", show=False)])\n",
    "print(f\"Class: {categories[prediction[0]]} {max(pro[0][0], pro[0][1]):.5%}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "cell_style": "center"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Class: Normal 100.00000%\n"
     ]
    }
   ],
   "source": [
    "prediction = model.predict_classes([prepare_img(\"test/not-evan_l.png\")])\n",
    "pro = model.predict_proba([prepare_img(\"test/not-evan_l.png\", show=False)])\n",
    "print(f\"Class: {categories[prediction[0]]} {max(pro[0][0], pro[0][1]):.5%}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "cell_style": "center",
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Class: Normal 100.00000%\n"
     ]
    }
   ],
   "source": [
    "prediction = model.predict_classes([prepare_img(\"test/not-evan_f.png\")])\n",
    "pro = model.predict_proba([prepare_img(\"test/not-evan_f.png\", show=False)])\n",
    "print(f\"Class: {categories[prediction[0]]} {max(pro[0][0], pro[0][1]):.5%}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAwQAAAEjCAYAAACMzcZFAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8vihELAAAACXBIWXMAAAsTAAALEwEAmpwYAAAJZklEQVR4nO3avWpVeRvG4ZXXxGD8SIxJp8wW9QxsJIjkBGwUsRFyDoKFrSGFiL1FKq0stBDsRUGEFFZCiihTRYiCGGNMCtecwOT9G0h8Zua+rnat4q6ezY+1h/q+7wAAgEz/qx4AAADUEQQAABBMEAAAQDBBAAAAwQQBAAAEEwQAABBseDcvHzlypJ+cnNyvLXvmxIkT1ROa3r59Wz3hl/R9P1S9AX63qampfjAYVM9o+vHjR/WEptXV1eoJTRsbG92PHz/cOuIcO3asn56erp7R9P79++oJTePj49UTmr5//95tb2//7a3bVRBMTk52N2/e3JtV+2hubq56QtPExET1BGAHg8GgW1paqp7RtLy8XD2haX5+vnpC0/Pnz6snQInp6enu7t271TOarl69Wj2h6eLFi9UTml6+fLnjM38ZAgCAYIIAAACCCQIAAAgmCAAAIJggAACAYIIAAACCCQIAAAgmCAAAIJggAACAYIIAAACCCQIAAAgmCAAAIJggAACAYIIAAACCCQIAAAgmCAAAIJggAACAYIIAAACCCQIAAAgmCAAAIJggAACAYIIAAACCCQIAAAgmCAAAIJggAACAYIIAAACCCQIAAAgmCAAAIJggAACAYIIAAACCCQIAAAgmCAAAIJggAACAYIIAAACCCQIAAAgmCAAAIJggAACAYIIAAACCCQIAAAg2vJuXf/782W1ubu7Xlj0zPj5ePaHp1KlT1ROaPn78WD0BSnz48KG7ceNG9YymR48eVU9o+jf8ZszMzFRPgBKrq6vd/Px89Yym8+fPV09oevfuXfWEpv93j30hAACAYIIAAACCCQIAAAgmCAAAIJggAACAYIIAAACCCQIAAAgmCAAAIJggAACAYIIAAACCCQIAAAgmCAAAIJggAACAYIIAAACCCQIAAAgmCAAAIJggAACAYIIAAACCCQIAAAgmCAAAIJggAACAYIIAAACCCQIAAAgmCAAAIJggAACAYIIAAACCCQIAAAgmCAAAIJggAACAYIIAAACCCQIAAAgmCAAAIJggAACAYIIAAACCCQIAAAgmCAAAIJggAACAYIIAAACCCQIAAAgmCAAAINjwbl4+fvx4d+XKlf3asme+f/9ePaHpxYsX1ROaLl++XD0BSnz79q179epV9YymmzdvVk9ompubq57Q9OHDh+oJUOLo0aPd7Oxs9Yym+/fvV09oevDgQfWEpoWFhR2f+UIAAADBBAEAAAQTBAAAEEwQAABAMEEAAADBBAEAAAQTBAAAEEwQAABAMEEAAADBBAEAAAQTBAAAEEwQAABAMEEAAADBBAEAAAQTBAAAEEwQAABAMEEAAADBBAEAAAQTBAAAEEwQAABAMEEAAADBBAEAAAQTBAAAEEwQAABAMEEAAADBBAEAAAQTBAAAEEwQAABAMEEAAADBBAEAAAQTBAAAEEwQAABAMEEAAADBBAEAAAQTBAAAEEwQAABAMEEAAADBBAEAAAQTBAAAEEwQAABAMEEAAADBhvq+//WXh4bWuq77c//m8A/zR9/309Uj4Hdz6+K4dURy6+LseOt2FQQAAMB/i78MAQBAMEEAAADBBAEAAAQTBAAAEEwQAABAMEEAAADBBAEAAAQTBAAAEEwQAABAMEEAAADBBAEAAAQTBAAAEEwQAABAMEEAAADBBAEAAAQTBAAAEEwQAABAMEEAAADBBAEAAAQTBAAAEEwQAABAMEEAAADBBAEAAAQb3s3LU1NT/WAw2Kcpe+fTp0/VE5oOHDhQPaFpbW2t+/r161D1DvjdRkdH+7GxseoZTV++fKme0HT69OnqCU1ra2vd+vq6W0ecAwcO9CMjI9Uzmra2tqonNE1PT1dPaFpfX+82Nzf/9tbtKggGg0G3tLS0N6v20eLiYvWEpomJieoJTbdu3aqeACXGxsa62dnZ6hlNz549q57QtLCwUD2h6fbt29UToMTIyEh38uTJ6hlNKysr1ROarl27Vj2h6fHjxzs+85chAAAIJggAACCYIAAAgGCCAAAAggkCAAAIJggAACCYIAAAgGCCAAAAggkCAAAIJggAACCYIAAAgGCCAAAAggkCAAAIJggAACCYIAAAgGCCAAAAggkCAAAIJggAACCYIAAAgGCCAAAAggkCAAAIJggAACCYIAAAgGCCAAAAggkCAAAIJggAACCYIAAAgGCCAAAAggkCAAAIJggAACCYIAAAgGCCAAAAggkCAAAIJggAACCYIAAAgGCCAAAAggkCAAAIJggAACCYIAAAgGDDu3m57/tua2trv7bsmYMHD1ZPaDpz5kz1hKbR0dHqCVDi8OHD3YULF6pnND19+rR6QtP169erJzTdu3evegKUGBoa6g4dOlQ9o2lmZqZ6QtPr16+rJzRtbGzs+MwXAgAACCYIAAAgmCAAAIBgggAAAIIJAgAACCYIAAAgmCAAAIBgggAAAIIJAgAACCYIAAAgmCAAAIBgggAAAIIJAgAACCYIAAAgmCAAAIBgggAAAIIJAgAACCYIAAAgmCAAAIBgggAAAIIJAgAACCYIAAAgmCAAAIBgggAAAIIJAgAACCYIAAAgmCAAAIBgggAAAIIJAgAACCYIAAAgmCAAAIBgggAAAIIJAgAACCYIAAAgmCAAAIBgggAAAIIJAgAACCYIAAAgmCAAAIBgggAAAIIN7+bl5eXl7tKlS/u1Zc+8efOmekLT6Oho9YSm7e3t6glQYmtrq1tZWame0fTkyZPqCU0PHz6sntD0+fPn6glQ4uzZs/+KO3Lu3LnqCU2Li4vVE5ru3Lmz4zNfCAAAIJggAACAYIIAAACCCQIAAAgmCAAAIJggAACAYIIAAACCCQIAAAgmCAAAIJggAACAYIIAAACCCQIAAAgmCAAAIJggAACAYIIAAACCCQIAAAgmCAAAIJggAACAYIIAAACCCQIAAAgmCAAAIJggAACAYIIAAACCCQIAAAgmCAAAIJggAACAYIIAAACCCQIAAAgmCAAAIJggAACAYIIAAACCCQIAAAgmCAAAIJggAACAYIIAAACCCQIAAAgmCAAAIJggAACAYIIAAACCCQIAAAgmCAAAINhQ3/e//vLQ0FrXdX/u3xz+Yf7o+366egT8bm5dHLeOSG5dnB1v3a6CAAAA+G/xlyEAAAgmCAAAIJggAACAYIIAAACCCQIAAAgmCAAAIJggAACAYIIAAACCCQIAAAj2Fwou8D9T9SYJAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1152x1152 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16, 16))\n",
    "# retrieve weights from the second hidden layer\n",
    "filters, biases = model.layers[0].get_weights()\n",
    "# normalize filter values to 0-1 so we can visualize them\n",
    "f_min, f_max = filters.min(), filters.max()\n",
    "filters = (filters - f_min) / (f_max - f_min)\n",
    "# plot first few filters\n",
    "n_filters, ix = 6, 1\n",
    "for i in range(n_filters):\n",
    "    # get the filter\n",
    "    f = filters[:, :, :, i]\n",
    "    # plot each channel separately\n",
    "    for j in range(1):\n",
    "        # specify subplot and turn of axis\n",
    "        ax = plt.subplot(n_filters, 3, ix)\n",
    "        ax.set_xticks([])\n",
    "        ax.set_yticks([])\n",
    "        # plot filter channel in grayscale\n",
    "        plt.imshow(f[:, :, j], cmap='gray')\n",
    "        ix += 1\n",
    "# show the figure\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "run_control": {
     "marked": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1, 32, 32, 32)\n",
      "(1, 32, 32, 32)\n",
      "(1, 32, 32, 64)\n",
      "(1, 8, 8, 64)\n",
      "(1, 8, 8, 64)\n",
      "(1, 8, 8, 64)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-33-c6e971e4cc9f>:39: RuntimeWarning: invalid value encountered in true_divide\n",
      "  x /= x.std()\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1, 2, 2, 64)\n",
      "(1, 2, 2, 64)\n",
      "(1, 256)\n",
      "(1, 512)\n",
      "(1, 512)\n",
      "(1, 256)\n",
      "(1, 2)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x45 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x45 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x22.5 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x22.5 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x22.5 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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jdJjX+7Edj8eXPF1xtlHGmSN8s6Wil0OW2XphtVppampi586dZgr/zE5GKpUqOjXbmLLX2NhoZqpVVFTQ0tJCLBYjHo9js9lobm42p0MZo1kwdc4y0qrdbreZ5bMYLpeLLVu2UFlZSS6XIxKJ3HY9NqYpR6PRaTenNpuNTZs2UVdXZ253u924XC6CwaCZ8Wgc36UYtfX5fDQ1NdHd3b3kG+XJyUkmJycX1Q4qKyvZvHkzwWBwWhuyWq3U19fj9/uXPT1MrA82mw273U4ikWBsbIxEIrHoYIjNZsNms5nXJrvdvuzsB5vNRn19PZWVlWZWYTEikQi9vb2LPkcsZLVuDI3fqSGXyy2YDWVkHZaCMRW68LxjZNgbmS6lYJSHaGpqMoPu8+1TTU0NjY2Nc77WbrezadMmamtrzekuFovltuuWUopkMonT6SSRSGCxWKS/sEKMLFyjX2GIxWJznmOM4M5c11Gr1YrH48HlcpnZpkZ/obq6elofM5fLYbfbi87UX2lWqxWbzXZb/97I1jOCO/OVk4hGo9y8edN8nzGV1PgbFL7PGCibmSk0mwXPnlrrjFLqN4CfMbUU+ne01pcWet9609/fb0YkYeqXnEwmicVi3Lp1a433bordbue+++5j9+7dTExMEIlEzBos4XDYHCk3at40NzfjcrmIRCIkk0kmJibKbhTg3nvvpa2tja6uLt59990NkxYpxO7du/nIRz5Cf38/J0+eLMvRh7VUU1NDbW2tGeSJxWIMDNyWFCoWkM1mOXnyJB0dHbS0tNDa2kogEKCnp4dgMFh0rZ9sNsupU6e4du0aIyMjAFy7do1vf/vbVFZW0tLSQjab5aWXXiKZTJp14WKxGIlEgqqqKmpra/F4PNTV1S0pQyAUCtHe3o5SioGBAWKxGIODg9NeMzo6yq1bt8wOYy6XIx6PEwqF6OjowOv1minjPT09DAwMMDQ0RDQaNW9GZ3ailkNrTXt7O88//3xRtUIW48qVK2Ztg8LzitVqpa6ujk2bNhVdE0OsD0ZG5WIHfZRSPPLII7S1tXHp0iXefvvtor7/5OQkr732GgB9fX0LvHpjUkqxd+9e7rvvPnPb4OAgJ06cWPE6jsa0OI/Hw4EDB2hoaDCfGxsbY3R0lOHh4XmnQi9FJpPh3XffxWKx3DbAPFMymeT48eOcPXt2zvuocDjMyZMncTgcJJNJM9N35vlYKUUkEmFwcNDMahKl53A4ePDBB/H7/Vy+fJne3t4F32O1WmltbaW6uprBwcFZj4tkMsmNGzew2WzmuWpoaMic4VEY/DP6gslksmwHs7XWJBIJUqnUnPtoTCMH5jxerVYrTqeTXC5HMpnE5XLR1taG3++nrq5u2iBNZ2cn7e3tJJNJcyBoLosKjWut/wH4h8W8dr2aK4KeTqeXPee31Iz5wy0tLWZkz4huFh44drsdp9NpjqYEAoFFpXqvNqUUmzZt4p577iEej2OxWCS4s0EVFjS9U1Jp/X4/e/bsAZg1xfhO53Q6qampwWq1YrfbCYfDjIyMlKRA4p3AGJXNZDL09PRw7tw5tNb4/X7Gxsa4efMmiUSi6KyxXC7HwMDAtMDb+Pg4XV1dNDQ0sGnTJlKpFBcvXiQYDJqjtKFQiEgkQmNjI83NzWYWzVICKclkkuHhYdLpNB0dHbNewyKRCJOTk+aIlvE7SSaT5rWvoqICh8PByMgIg4ODhMNhM2OhMMW8GFprhoeHuXLlSkkK1M5nZGTEDLTN5Ha7Fyz4KNY/IxujsJ5WYRHP2Rg3zVu2bKGtra0kg32pVIobN26YNxx3KqMva5zbjIVLlsv4Wy7UZzIyIT0eDzt37mTbtm3mPvT39+N2u8lkMty4cWPZ+1Iol8vR19e3qFIV2Wx2Wo3N2SSTSTMoONcUnLlqmxR73jauRdI/+5DVaqWxsZHNmzcvOlhrZN80NDRMW+CnMLsqk8ksueZVuVso8GQURp+PkXGXyWTMrJ2mpiaamppoaWmhurp62myc69evm2VX5utjlKygslh5Rh0Fh8NBa2srra2tdHV1cePGDeLxOFprszB0ZWUlDQ0N5qpaxspJc3UI14LWmo6ODqLRKKOjoxLY2cCGhoY4c+YM/f39d8zfubOzkx/96EcEg0HJ2plHbW0tO3fuJJvNcv/999PT08O7774r9bkWkEgk+PnPf87Zs2fp6uoCMM+lPp+Pw4cPMzIyws9//vOiau7Mxui0JBIJJiYmpqVvu1wuKioqzKySsbEx4vE4gUDAXK1lsdlEPp+PBx54gEQiQU9Pz6zBHa01qVQKpRQOhwOPx0NFRQXV1dXcfffdeDweTp48SXd3t7lvNpsNl8uF0+mkurqaRCJRkulrDzzwAF/4whe4ceMGH3zwgYwuixWRTqc5ffo0XV1d+Hw+nn76aXM639DQEBcvXiSXy5kDZkZ7a21txe/309jYWNLA5p1Oa82lS5eYmJgwtwWDwWWvHGZk4Xi9Xt5///15C8lmMhni8bi5KEhVVRX19fVmxuLmzZsJBAJlO2BiZB4Bc05RMwI6pRwYVEpx//33c/fdd5PJZDZUQeViGItgzMwKnY/FYqG1tZVdu3YRCATo6urirrvu4uGHH6avr4/XX3+dbDZLbW0tVqvVnE0iZSamAjbG/buRDXTu3Dk6Ozt56KGH2LJlC06n05yRs3v3brMIuVKKb33rW7N+rgR31hljjp9RfKy/v5/h4eFpSxA7nU48Hg9VVVX4/X6z4FMp5kOXWn9//21p9mLjCQaDXL9+nWAweMdcQIeGhsypkmJulZWV7Nixw6xXYGQcivml02kuXLgwbVsymSQUClFTU8PDDz9Md3d30dMuZmN0RIyVMIxacEadKaPjkclkzKxYIzszmUwuOujhdrvZunUr0Wh0ztp3Rm0LYyloY0WOyspKmpqaqKysZGRkhPb2dnbt2sX27dvN1xjBII/HU5Il5rdu3cr+/fvJZDJmkdu1cKecY+9URiaGy+Xi8ccf55577jHb5JUrV+js7DTrRhrBT5jKLmlubjYzJiWwUzq9vb2LmsKyGG63mwcffJBNmzbR2dm54CpBRq21Dz74AIvFws6dO6mvr2fPnj1s3boVr9db1sEd49w+3/FY6oxvpRStra3s37+f06dPl+3vZ7UVliRZbOClcFaJz+cDplb3PHDgABcuXODNN98EpqbiGzNNjOyTOz24YxRPN6TTabq6urDb7dTX1+NwOKisrMTj8WC322lubsbtdrNly5Z5B6QWFdxRSnUDk0AWyGitHynuxxHLkclkuH79uhm1s9vt9PX1TTvpZTIZQqEQyWSSM2fO4Ha7zeKm4+Pja7j3YqmUUtx7773s2LHD3GakPiulcDqdZDIZrl27Rjgcxu/3U1lZydjYWNn9rScnJ83l/WQ0u/w4HA4effRRHnroIS5dukRfXx87d+5k165dhMNhBgcHicfjjI6OluzvF4lEGBgYIJvNYrVazdUA+/v7y6Y2WEVFBffddx9VVVV0d3eXPAOm1EKhEL29veZqIkbNHWNlh1Lf0MXjcbP46datW83544WMqcNGcfHCqSQLGRsb44033jCDSEY9gNraWq5cuUJvby9+v5/a2lpzNS673c7u3bupr683Czb6/X7zptbtdps3wg6HA5/PZy7JWwytNVevXuVnP/sZvb29axZgMUZD5Ty7cdlsNvbs2UN9fT2BQICjR48CU8egsVqpUbsEPgz29ff3Ew6HGR0d5cKFC9y8eZNcLldU1prH46GtrQ2bzcb58+fp7Ows/ge8w8ViMd555x08Hs+CdW1myuVyjI+PmwW2e3t7GRwcLNvzQTqdZnR0FKfTydatW82abIX/kskk8XicaDTKyMhISX4WrTXXrl0jmUzS0dEhAfE8Y1pWS0uLWeh3IZlMhrNnzzIwMGC2/56eHl577TVzgNNut5PL5bDZbOzfv5/Kykoze2fmVO1gMMj58+fLspzIbOrr66mtrTWz5goZtXTOnz+/pGz0bDZLZ2cnExMTZh8qnU6TTCbNgM98fZalZO48qbUeW8LrRYllMhm6urrmPdgLR0pHRkbMVHWr1SpTQ9ahe+65h0984hPmY6OgnFIKn89HIpEgFAqRzWbNuhZa67IL7hTutyg/DoeDRx55hEOHDhEOh+nr62PHjh186lOfor+/n7NnzxIIBJiYmChZJ9E4T0UiESKRCIlEgoGBAcbHx0u2gkixPB4P99xzDzU1NeZNUzkzfqd9fX3TMkesVqs5IJBOp0vWkU0kEvT29uLz+XjiiSeoqqpidHR02spVdrudyspKHA7HkldtGR8f59ixY+bjyspKPvKRj7Br1y5zVR2/38+mTZsYHBzk1q1bWK1Wdu3axaZNm4CpmiB+v5/NmzdTU1MzLYPV5XJRXV1NMBgselpWYXBnLRlLqd4ptc3uRHa7nT179rBjxw5efvnlRWfnDQ4OMjg4SEdHx7TtxQZ3Hn/8cbxeL9/73veW/TniQ/F4nHfeeWfZ7w8EAgQCgXVR4DqdTjM+Pk5FRQV79+41l8A2arYYhZQDgQCjo6OMj4+XNLhz7do1Ojo65HyZZ7FYaGhoYNu2bXi93kW9J5PJ0N7ePm2bkcmWy+XQWmOz2cxA8qOPPsr27dvNwZ6Z9am6u7sZGhpibGxs2VMbV1NdXR27du2ipaWFe++9d1q9LGNganBwcEnBnVwux82bNxcdYJtJpmWtQxaLhT179tDc3GwuO26z2cxMjnA4jFJq2rKCSik6OjqWfaDU1dWxY8cOotEo169fXxcNbjHsdjt33XUXFRUVa5pGP5eRkRE6OjqIx+NmrYpQKGSOxBsXxkQiwfDwMLFYrGyyHsTyVVVVcdddd5HNZrl27dqqjV4UBt/6+vo4ceIEwWCQgYEBotHoiqTQGnVbKioqePTRRxkfH+ftt98ui5o78Xiczs5Oqqur18UI0lyMZcFdLpcZfCmlVCpFT08PHo/HXLGqtraW6upqfD6fOQ3EZrMRDAYZHh5e1rGUTqe5dOkSo6Oj5ohgKBQyz3u5XI5gMMgbb7xhTu3L5XJ0dXURiUSwWCxkMhlcLpcZcKqrqyMcDhcd3CkHRkr32NjYtPofYmPJZDJ0dnYSDoeXNZDj9/vx+/2EQiHGxoobszVqRNjt9qI/SxTHZrNhtVppaWkx65sULs9+5coVjh8/XhbXMofDgd/vN6elGP3ZeDxuDkgbgQFjKq8EYNYfY1nwXC5HKBQilUrx3nvvcePGDfPvOzNzZ3x83FwModwyzowaUUb/wlgYqKWlhVQqxYkTJ6bViMpms+Zq1cWy2+24XC6qqqrYunUrdrudZ599dtbXLja4o4EjSikN/F+t9W2fppT6KvDVZe+1WDSLxcKBAwd48sknmZycJBQK4fF4qKmpIRaL0d3djVKKbdu24fF4zOjoiy++uOzgTnNzM8888wz9/f309fVtmOCOw+Fg3759bNu2zUxtLic9PT2kUimGh4fp6+ub80RnFEETG0NdXR1PPfUUiUSCoaGhNemMXb16levXr09boWIlOlfGcpJGYdCxsTGee+65kn+f5YhGo7S3t1NdXb2uO5bGXG2v10ssFiv5uSKRSHD58mWsViubNm3C6/Wyfft2mpqaqKuro6mpiWw2a2ZnXbhwYVlLtCeTSU6ePAl8eCyOjo4SCATMFapGRkZ4/vnnzfdYLBZzOlYsFsPlclFXV0dFRQVut5vNmzcTi8U2xOpSRt0NpdSSp3OI9SOVStHe3o7dbicQCCzpvUopmpub2bVrF11dXUVn+UYiEY4dO0YikZhzuWuxOoxC8Q899BAPPPAALpdr2lLKb775Jn/xF3+xhnv4Ibfbjc/nI5vNEg6HsdlspFIpIpEIbrfbzDI1/i11Sq8oD4UF3Y1+bF9f37xZ/Cu92mQxLBYLXq+X6upq83FLSwv33Xcfb7/9Nj/4wQ9mXSGrFMety+XC7/ezc+dOnnnmGTweD1/60pdmfe1igztPaK0HlFKbgKNKqQ6t9fHCF+QDPs8C5INAYoXkcjm6u7s5c+YMsViMWCyG0+k05zAaK2JNTEzgdDrNVPhiVsoKhUJcuXKFQCCwoQpgZbNZent7icfjZTfSaQRsxsbGiEQis17Y7HY727Ztm1aAdmJigmAwiMfjkWlQ61Q0GjXng69GINWY8llXV2d29o1Rh5kcDgdbt27F5XLR29tbkkwx40Ju1IQpl0KfM4NaSilaWlqoqam57bXG1EOj5kk5dUIzmQyjo6NEIpEVCxQaHbJ4PA5gLmE+MTHB2NiYWfh4fHy8qCnCs3X6Co9TI3PIYLFYSCQS5ghiIpEwl0uPx+N4vV4ziL7e2Ww2s+CiUdhSbDw2m43W1laqqqq4fPnykpcgD4VCDA4OEgwGb1ta2ufzmVNh5lvG1+PxsG3bNjMoGo1Gi5pKJBansH7ZzAC5cY4dGBjAZrOZBeYNnZ2dZdN/T6fThMNh8+ewWCyMjY2ZtdVsNtu0+mHpdJpIJFKym36lFI2NjdTV1TE8PCx95VU08/rsdrtxu91mkoKRrWUsnx6NRqdloK0lY9+MtqeUoq+vj3PnzjEyMoLP5yOZTJqZwj6fD5vNRiQSMY/n5R7DmUyGWCzG6OgoFy9enNa2Z1rUb0trPZD/f0Qp9QrwGHB8/neJlZLL5XjzzTc5ceIEMP3Gw3gebq88X8xJvaenh8HBQbNTvFEkk0neeusttNZlWQhwfHyciYkJM31xJo/Hw1NPPcXdd98NTB0L586do729XWrcrGMjIyP8+Mc/Bpi3g10qiUSCN954g66urgXbd2VlJYcPH6a+vp6XX375thWbNjK73c7BgwfZu3fvbc/dvHmTV199lXA4TCwWK6t04mQyyaVLl8yVSVZqCpIxLSoUCpk134x/ha/JZDKrdm4yCnUbhegBs55DTU0Ng4ODZgB9vXO5XBw4cIDGxkbz/CE2HofDwcGDB9m5cyfxeHxJtVW01vT19TEwMHBbv8LlctHa2orVajVX3JpLQ0MDn//856mqqgKmAkZHjx7l3Llzy/65xMLcbjd+v594PE4qlZp2o2iUaTh16hRnzpwBbp9qXQ5TsmAqiyMSiUzLDF4oC62UGR1KKdra2jh48CATExO88MILZXXNvhMY0wjr6+vZvHkzra2tPPzww2QyGTPQd+HCBUZGRspmtedsNmvOljGcPHmS9957D7/fz7Zt25icnKSzsxO73c6uXbtwuVx0d3cTDoeJRqPLHrBNJBIkEgkCgQDXrl2btw+1YHBHKVUBWLTWk/mvnwL+YFl7JkrGSFWci8Vioba2FrvdbkYKi6mZYVT83miMglfGUr7lZq7sCUM2m2V0dNQ88RmrZRgX/o1MKUVtbS1er5dgMFh2mVfFmLk84mowKvEvJJPJMDIyYs6PL5V4PM7NmzcZHx8v23ON1ppAIMDAwMBtz42Ojpqd7XI7lxjnEWO1ipUK7iilqKqqwul0mtPtjFFXY9nxbDa75EyDYs319zBW2AoGgxumY2+M2G+EGkJidrlczlxhaDlBybnOUblcjlgshtVqXbCvmEwmuXXrltmWJycnS3o9KLWamhqqq6vNFUeNjJHC4MJ6YNTwmK//b2QIzJROp8vqZ50ZXJx5Drbb7eb5zFjlsPB+Rmu97EECrfWcGWxidRjBukQiYRbN7u/vNzN2jACgkW1bLozjzpiCbhzHVquVWCw27bxiZECmUqmiM7qN9xpTFOezmMydBuCVfAOyAc9rrX+67L0Tq6KiooJ9+/ZRV1dnNo7Lly/T1dW11rsmSigajfKTn/xkWsqicRIxpkJsVFarlX379tHW1sbbb7/Nm2++KRfoVRCJRHj11VfN6S6lMjQ0xAsvvEAwGCzbwpyZTIbjx4/POv3AuFmYK8vuTmC327n//vtpamqit7eX4eFhsxh8XV0dd911F9FolPPnz5dFAC8ajdLV1UU4HN7wwXCxcSQSCY4ePYrNZivpoEYymaSnpwdYONN7aGiI73//++bNtbFyXjlSSrF3716eeOIJ+vr6uHTpkrmqoBGQXy/n7Gg0at48buT+HUxlCVdVVdHY2MjOnTvJZDJMTk4SiUS4evUqsVhs2VO4tdacOXOGixcv8v7772/432U5MoIURt28a9eu8e677wIfBqCNqdTlFji22Ww8+eSTtLW1kUqlSKfTfPDBBxw5coR0Om1OJzQybIxg7GqdZxYM7mitu4Dbc9BFWVNK4Xa7qaioMC/S5TJnUZTOfIWUN8pI9HxcLhderxen07nWu3LHMEbNSs1Y6c+oL1WOtNbE4/Gy62iUC6WUOcpqjLoaNZSsVitOp5NUKlU200WNDLlyG9EWYj5aa3N6TSmDkkYm82IY0x0NRo2McuV0OvF6vXg8HrOmS7mch5aqXK+PpWaxWMyVgN1uN5lMxpy1UIrafEZNw1IOUomlK8xEme1vUW41DOHDe+yqqipSqRTJZBKHw2EGdmDqfLpWg0ZqJX5hSqlRIAqU5/CrEBtHHdLOhFhp0s6EWHnSzoRYedLOhFh5q9HOtmqt62duXJHgDoBS6rTW+pEV+XAhBCDtTIjVIO1MiJUn7UyIlSftTIiVt5btrDzWmxVCCCGEEEIIIYQQyyLBHSGEEEIIIYQQQoh1bCWDO8+u4GcLIaZIOxNi5Uk7E2LlSTsTYuVJOxNi5a1ZO1uxmjtCCCGEEEIIIYQQYuXJtCwhhBBCCCGEEEKIdazkwR2l1GGl1FWl1A2l1G+V+vOFuFMopb6jlBpRSl0s2OZXSh1VSl3P/1+T366UUn+Wb3fnlVIPr92eC7F+KKValFLHlFKXlVKXlFK/md8ubU2IElFKuZRSp5RSH+Tb2dfy27crpd7Lt6cXlVKO/HZn/vGN/PPb1vQHEGIdUUpZlVLtSqlX84+lnQlRQkqpbqXUBaXUOaXU6fy2sug3ljS4o5SyAv8H+DRwL/ArSql7S/k9hLiDPAccnrHtt4B/1FrfDfxj/jFMtbm78/++CnxrlfZRiPUuA/wnrfW9wH7g3+avW9LWhCidJHBIa70XaAMOK6X2A/8L+KbW+i5gAvj1/Ot/HZjIb/9m/nVCiMX5TeBKwWNpZ0KU3pNa67aCJc/Lot9Y6sydx4AbWusurXUKeAH4XIm/hxB3BK31cSAwY/PngL/Kf/1XwOcLtn9XT3kXqFZKNa3Kjgqxjmmtb2mtz+a/nmSqQ7wFaWtClEy+vUTyD+35fxo4BHw/v31mOzPa3/eBTyil1OrsrRDrl1KqGXgG+Mv8Y4W0MyFWQ1n0G0sd3NkC9BU87s9vE0KURoPW+lb+6yGgIf+1tD0hipRPSX8IeA9pa0KUVH6qyDlgBDgKdAJBrXUm/5LCtmS2s/zzIaB2VXdYiPXpT4D/AuTyj2uRdiZEqWngiFLqjFLqq/ltZdFvtK3UBwshVpbWWiulZLk7IUpAKVUJ/AD4D1rrcOHgpbQ1IYqntc4CbUqpauAVYM/a7pEQG4tS6jPAiNb6jFLq42u8O0JsZE9orQeUUpuAo0qpjsIn17LfWOrMnQGgpeBxc36bEKI0ho1Uvvz/I/nt0vaEWCallJ2pwM7faK3/Lr9Z2poQK0BrHQSOAY8zlZ5uDDQWtiWzneWfrwLGV3dPhVh3DgKfVUp1M1Ua4xDwp0g7E6KktNYD+f9HmBqseIwy6TeWOrjzPnB3viq7A/gi8KMSfw8h7mQ/Ar6S//orwA8Ltn85X5F9PxAqSA0UQswhX1/g28AVrfUfFzwlbU2IElFK1eczdlBKuYFPMlXf6hjwi/mXzWxnRvv7ReANrbVkzwkxD631b2utm7XW25i6B3tDa/2rSDsTomSUUhVKKa/xNfAUcJEy6TeqUrdhpdTTTM33tALf0Vp/vaTfQIg7hFLqb4GPA3XAMPD7wN8DLwGtQA/wy1rrQP4G9c+ZWl0rBvya1vr0Guy2EOuKUuoJ4C3gAh/WKPgdpuruSFsTogSUUg8yVWDSytTA4kta6z9QSu1gKsPAD7QD/1xrnVRKuYDvMVUDKwB8UWvdtTZ7L8T6k5+W9Z+11p+RdiZE6eTb0yv5hzbgea3115VStZRBv7HkwR0hhBBCCCGEEEIIsXpKPS1LCCGEEEIIIYQQQqwiCe4IIYQQQgghhBBCrGMS3BFCCCGEEEIIIYRYxyS4I4QQQgghhBBCCLGOSXBHCCGEEEIIIYQQYh2T4I4QQgghhBBCCCHEOibBHSGEEEIIIYQQQoh1TII7QgghhBBCCCGEEOvY/wfcFi48Zm0vKgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1440x22.5 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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dk35DRPwO1SLgY4EVwMlU/+HkfKueFhFfAT5FdWvAfcBnqdZ4cM5Vz4iIRcBHgUnA08CXgX9mE3Nsnai8hOoWw1eBkzPz3lHotjTU2D0X2Ap4tg67MzPPrOPPo1qHZyPVsho3DK7z3aSryR1JkiRJkiR1lwsqS5IkSZIk9TGTO5IkSZIkSX3M5I4kSZIkSVIfM7kjSZIkSZLUx0zuSJIkSZIk9TGTO5IkSZIkSX3M5I4kSZIkSVIfM7kjSZIkSZLUx/4XH9ZlQ+BA2BIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1440x22.5 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x22.5 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "counter = 0\n",
    "img_path = \"test/evan_l.jpeg\"  # dog\n",
    "# Define a new Model, Input= image\n",
    "# Output= intermediate representations for all layers in the\n",
    "# previous model after the first.\n",
    "successive_outputs = [layer.output for layer in model.layers[1:]]\n",
    "#visualization_model = Model(img_input, successive_outputs)\n",
    "visualization_model = Model(inputs=model.input, outputs=successive_outputs)\n",
    "# Load the input image\n",
    "img = load_img(img_path, color_mode=\"grayscale\", target_size=(128, 128))\n",
    "# Convert ht image to Array of dimension (150,150,3)\n",
    "x = img_to_array(img)\n",
    "x = x.reshape((1,) + x.shape)\n",
    "# Rescale by 1/255\n",
    "x /= 255.0\n",
    "# Let's run input image through our vislauization network\n",
    "# to obtain all intermediate representations for the image.\n",
    "successive_feature_maps = visualization_model.predict(x)\n",
    "# Retrieve are the names of the layers, so can have them as part of our plot\n",
    "layer_names = [layer.name for layer in model.layers]\n",
    "for layer_name, feature_map in zip(layer_names, successive_feature_maps):\n",
    "    print(feature_map.shape)\n",
    "    if len(feature_map.shape) == 4:\n",
    "        counter += 1\n",
    "\n",
    "        # Plot Feature maps for the conv / maxpool layers, not the fully-connected layers\n",
    "\n",
    "        n_features = feature_map.shape[-1]  # number of features in the feature map\n",
    "        # feature map shape (1, size, size, n_features)\n",
    "        size = feature_map.shape[1]\n",
    "\n",
    "        # We will tile our images in this matrix\n",
    "        display_grid = np.zeros((size, size * n_features))\n",
    "\n",
    "        # Postprocess the feature to be visually palatable\n",
    "        for i in range(n_features):\n",
    "            x = feature_map[0, :, :, i]\n",
    "            x -= x.mean()\n",
    "            x /= x.std()\n",
    "            x *= 64\n",
    "            x += 128\n",
    "            x = np.clip(x, 0, 255).astype('uint8')\n",
    "            # Tile each filter into a horizontal grid\n",
    "            display_grid[:, i * size: (i + 1) * size] = x\n",
    "        # Display the grid\n",
    "        scale = 20. / n_features\n",
    "        plt.figure(figsize=(scale * n_features, scale))\n",
    "        plt.title(layer_name)\n",
    "        plt.grid(False)\n",
    "        plt.imsave(f\"last_model_run/evan{counter}.png\", display_grid)\n",
    "        plt.imshow(display_grid, aspect='auto', cmap='gray')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Conv:conv2d_1\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x1152 with 12 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Conv:conv2d_2\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x1152 with 12 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Conv:conv2d_3\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x1152 with 12 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Iterate thru all the layers of the model\n",
    "for layer in model.layers:\n",
    "    if 'conv' in layer.name:\n",
    "        print(f\"Conv:{layer.name}\")\n",
    "        plt.figure(figsize=(16, 16))\n",
    "        # retrieve weights from the second hidden layer\n",
    "        filters, biases = model.layers[0].get_weights()\n",
    "        # normalize filter values to 0-1 so we can visualize them\n",
    "        f_min, f_max = filters.min(), filters.max()\n",
    "        filters = (filters - f_min) / (f_max - f_min)\n",
    "        # plot first few filters\n",
    "        n_filters, ix = 12, 1\n",
    "        for i in range(n_filters):\n",
    "            # get the filter\n",
    "            f = filters[:, :, :, i]\n",
    "            # plot each channel separately\n",
    "            for j in range(1):\n",
    "                # specify subplot and turn of axis\n",
    "                ax = plt.subplot(n_filters, 3, ix)\n",
    "                ax.set_xticks([])\n",
    "                ax.set_yticks([])\n",
    "                # plot filter channel in grayscale\n",
    "                plt.imshow(f[:, :, j], cmap='gray')\n",
    "                ix += 1\n",
    "        # show the figure\n",
    "        plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "loaded_model = load_model(checkpoint_filepath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "#model.save(Best_model_path)\n",
    "loaded_y_pred = loaded_model.predict_classes(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "cell_style": "center"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Class: Normal 100.00000%\n"
     ]
    }
   ],
   "source": [
    "prediction = loaded_model.predict_classes([prepare_img(\"test/evan_l.jpeg\")])\n",
    "pro = loaded_model.predict_proba([prepare_img(\"test/evan_l.jpeg\", show=False)])\n",
    "print(f\"Class: {categories[prediction[0]]} {max(pro[0][0], pro[0][1]):.5%}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "cell_style": "center",
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Class: Normal 100.00000%\n"
     ]
    }
   ],
   "source": [
    "prediction = loaded_model.predict_classes([prepare_img(\"test/evan_f.jpeg\")])\n",
    "pro = loaded_model.predict_proba([prepare_img(\"test/evan_f.jpeg\", show=False)])\n",
    "print(f\"Class: {categories[prediction[0]]} {max(pro[0][0], pro[0][1]):.5%}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "cell_style": "center"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Class: Normal 100.00000%\n"
     ]
    }
   ],
   "source": [
    "prediction = loaded_model.predict_classes([prepare_img(\"test/not-evan_f.png\")])\n",
    "pro = loaded_model.predict_proba([prepare_img(\"test/not-evan_f.png\", show=False)])\n",
    "print(f\"Class: {categories[prediction[0]]} {max(pro[0][0], pro[0][1]):.5%}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "cell_style": "center",
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Class: Normal 100.00000%\n"
     ]
    }
   ],
   "source": [
    "prediction = loaded_model.predict_classes([prepare_img(\"test/not-evan_l.png\")])\n",
    "pro = loaded_model.predict_proba([prepare_img(\"test/not-evan_l.png\", show=False)])\n",
    "print(f\"Class: {categories[prediction[0]]} {max(pro[0][0], pro[0][1]):.5%}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "hide_input": false,
  "kernelspec": {
   "display_name": "venv",
   "language": "python",
   "name": "venv"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.3"
  },
  "latex_envs": {
   "LaTeX_envs_menu_present": true,
   "autoclose": false,
   "autocomplete": true,
   "bibliofile": "biblio.bib",
   "cite_by": "apalike",
   "current_citInitial": 1,
   "eqLabelWithNumbers": true,
   "eqNumInitial": 1,
   "hotkeys": {
    "equation": "Ctrl-E",
    "itemize": "Ctrl-I"
   },
   "labels_anchors": false,
   "latex_user_defs": false,
   "report_style_numbering": false,
   "user_envs_cfg": false
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  },
  "varInspector": {
   "cols": {
    "lenName": 16,
    "lenType": 16,
    "lenVar": 40
   },
   "kernels_config": {
    "python": {
     "delete_cmd_postfix": "",
     "delete_cmd_prefix": "del ",
     "library": "var_list.py",
     "varRefreshCmd": "print(var_dic_list())"
    },
    "r": {
     "delete_cmd_postfix": ") ",
     "delete_cmd_prefix": "rm(",
     "library": "var_list.r",
     "varRefreshCmd": "cat(var_dic_list()) "
    }
   },
   "types_to_exclude": [
    "module",
    "function",
    "builtin_function_or_method",
    "instance",
    "_Feature"
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   "window_display": false
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 },
 "nbformat": 4,
 "nbformat_minor": 4
}