3DCNN_Starter_MNIST.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "acoustic-remains",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import h5py\n",
    "import os\n",
    "sns.set_style('white')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "conscious-consensus",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['full_dataset_vectors.h5', 'plot3D.py', 'test_point_clouds.h5', 'train_point_clouds.h5', 'voxelgrid.py']\n"
     ]
    }
   ],
   "source": [
    "print(os.listdir('../datasets/mnist3d/'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "large-grass",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train shape: (10000, 4096)\n",
      "Train label: (10000,)\n",
      "Test shape: (2000, 4096)\n",
      "Test label: (2000,)\n",
      "0\n",
      "1000\n",
      "2000\n",
      "3000\n",
      "4000\n",
      "5000\n",
      "6000\n",
      "7000\n",
      "8000\n",
      "9000\n",
      "0\n",
      "1000\n"
     ]
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from tensorflow.keras.utils import to_categorical\n",
    "\n",
    "with h5py.File('../datasets/mnist3d/full_dataset_vectors.h5','r') as dataset:\n",
    "    X_train, X_test = dataset['X_train'][:],dataset['X_test'][:]\n",
    "    y_train, y_test = dataset['y_train'][:],dataset['y_test'][:]\n",
    "    \n",
    "print('Train shape:', X_train.shape)\n",
    "print('Train label:', y_train.shape)\n",
    "print('Test shape:', X_test.shape)\n",
    "print('Test label:', y_test.shape)\n",
    "\n",
    "def array_to_color(array, cmap = 'Oranges'):\n",
    "    s_m = plt.cm.ScalarMappable(cmap=cmap)\n",
    "    return s_m.to_rgba(array)[:,:-1]\n",
    "def translate(x):\n",
    "    xx = np.ndarray((x.shape[0], 4096, 3))\n",
    "    for i in range(x.shape[0]):\n",
    "        xx[i] = array_to_color(x[i])\n",
    "        if i % 1000 == 0:\n",
    "            print(i)\n",
    "    del x\n",
    "    return xx\n",
    "\n",
    "X_train = translate(X_train).reshape(-1,16,16,16,3)\n",
    "X_test = translate(X_test).reshape(-1,16,16,16,3)\n",
    "y_train = to_categorical(y_train,num_classes=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "driven-needle",
   "metadata": {},
   "outputs": [],
   "source": [
    "y_test = to_categorical(y_test,num_classes=10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "underlying-designation",
   "metadata": {},
   "source": [
    "### Translate data to fed in 3d CNN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "fixed-reference",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(10000, 16, 16, 16, 3)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "alternative-neighbor",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10000"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(X_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "about-interval",
   "metadata": {},
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "from tensorflow.keras.layers import Dense,Dropout, Flatten,Conv3D, MaxPool3D,BatchNormalization\n",
    "from tensorflow.keras.optimizers import RMSprop\n",
    "from tensorflow.keras.models import Sequential\n",
    "from tensorflow.keras.callbacks import ReduceLROnPlateau,TensorBoard\n",
    "\n",
    "def build_model(input_shape,num_classes):\n",
    "    model = Sequential()\n",
    "\n",
    "    model.add(Conv3D(8, (3,3,3), input_shape=input_shape))\n",
    "    model.add(Conv3D(16, (3,3,3)))\n",
    "    # model.add(BatchNormalization())\n",
    "    model.add(MaxPool3D())\n",
    "    # model.add(Dropout(0.25))\n",
    "\n",
    "    model.add(Conv3D(32, (3,3,3)))\n",
    "    model.add(Conv3D(64, (3,3,3)))\n",
    "    model.add(BatchNormalization())\n",
    "    model.add(MaxPool3D())\n",
    "    model.add(Dropout(0.25))\n",
    "\n",
    "    model.add(Flatten())\n",
    "\n",
    "    model.add(Dense(4096, activation='relu'))\n",
    "    model.add(Dropout(0.5))\n",
    "\n",
    "    model.add(Dense(1024, activation='relu'))\n",
    "    model.add(Dropout(0.5))\n",
    "\n",
    "    model.add(Dense(num_classes, activation='softmax'))\n",
    "\n",
    "    return model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "descending-underground",
   "metadata": {},
   "outputs": [],
   "source": [
    "model = build_model((16,16,16,3),10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "desperate-asset",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "conv3d (Conv3D)              (None, 14, 14, 14, 8)     656       \n",
      "_________________________________________________________________\n",
      "conv3d_1 (Conv3D)            (None, 12, 12, 12, 16)    3472      \n",
      "_________________________________________________________________\n",
      "max_pooling3d (MaxPooling3D) (None, 6, 6, 6, 16)       0         \n",
      "_________________________________________________________________\n",
      "conv3d_2 (Conv3D)            (None, 4, 4, 4, 32)       13856     \n",
      "_________________________________________________________________\n",
      "conv3d_3 (Conv3D)            (None, 2, 2, 2, 64)       55360     \n",
      "_________________________________________________________________\n",
      "batch_normalization (BatchNo (None, 2, 2, 2, 64)       256       \n",
      "_________________________________________________________________\n",
      "max_pooling3d_1 (MaxPooling3 (None, 1, 1, 1, 64)       0         \n",
      "_________________________________________________________________\n",
      "dropout (Dropout)            (None, 1, 1, 1, 64)       0         \n",
      "_________________________________________________________________\n",
      "flatten (Flatten)            (None, 64)                0         \n",
      "_________________________________________________________________\n",
      "dense (Dense)                (None, 4096)              266240    \n",
      "_________________________________________________________________\n",
      "dropout_1 (Dropout)          (None, 4096)              0         \n",
      "_________________________________________________________________\n",
      "dense_1 (Dense)              (None, 1024)              4195328   \n",
      "_________________________________________________________________\n",
      "dropout_2 (Dropout)          (None, 1024)              0         \n",
      "_________________________________________________________________\n",
      "dense_2 (Dense)              (None, 10)                10250     \n",
      "=================================================================\n",
      "Total params: 4,545,418\n",
      "Trainable params: 4,545,290\n",
      "Non-trainable params: 128\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "electoral-seattle",
   "metadata": {},
   "outputs": [],
   "source": [
    "model.compile(optimizer ='rmsprop', loss ='categorical_crossentropy', metrics = ['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "simple-nightmare",
   "metadata": {},
   "outputs": [],
   "source": [
    "from tensorflow.keras.callbacks import ModelCheckpoint, EarlyStopping, ReduceLROnPlateau\n",
    "\n",
    "filepath = '../HandGestureRecognitionUsingMnistDataset/bestweight.h5'\n",
    "mcp = ModelCheckpoint(filepath,monitor='val_loss',verbose=1,save_best_only=True,save_weights_only=True)\n",
    "\n",
    "earlystop = EarlyStopping(monitor ='val_loss',patience=10)\n",
    "reduce_lr = ReduceLROnPlateau(monitor='val_loss',factor=0.1,patience=1,verbose=0,mode='auto',min_lr=0.00001)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "spread-spyware",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train on 8000 samples, validate on 2000 samples\n",
      "Epoch 1/50\n",
      "7920/8000 [============================>.] - ETA: 0s - loss: 0.9507 - accuracy: 0.6596\n",
      "Epoch 00001: val_loss improved from inf to 2.83629, saving model to ../HandGestureRecognitionUsingMnistDataset/bestweight.h5\n",
      "8000/8000 [==============================] - 37s 5ms/sample - loss: 0.9496 - accuracy: 0.6600 - val_loss: 2.8363 - val_accuracy: 0.4435\n",
      "Epoch 2/50\n",
      "7920/8000 [============================>.] - ETA: 0s - loss: 0.9467 - accuracy: 0.6660\n",
      "Epoch 00002: val_loss improved from 2.83629 to 2.50463, saving model to ../HandGestureRecognitionUsingMnistDataset/bestweight.h5\n",
      "8000/8000 [==============================] - 35s 4ms/sample - loss: 0.9453 - accuracy: 0.6662 - val_loss: 2.5046 - val_accuracy: 0.5445\n",
      "Epoch 3/50\n",
      "7920/8000 [============================>.] - ETA: 0s - loss: 0.9425 - accuracy: 0.6665\n",
      "Epoch 00003: val_loss improved from 2.50463 to 1.47832, saving model to ../HandGestureRecognitionUsingMnistDataset/bestweight.h5\n",
      "8000/8000 [==============================] - 34s 4ms/sample - loss: 0.9443 - accuracy: 0.6656 - val_loss: 1.4783 - val_accuracy: 0.5310\n",
      "Epoch 4/50\n",
      "7920/8000 [============================>.] - ETA: 0s - loss: 0.9462 - accuracy: 0.6607\n",
      "Epoch 00004: val_loss improved from 1.47832 to 1.09232, saving model to ../HandGestureRecognitionUsingMnistDataset/bestweight.h5\n",
      "8000/8000 [==============================] - 34s 4ms/sample - loss: 0.9470 - accuracy: 0.6604 - val_loss: 1.0923 - val_accuracy: 0.6485\n",
      "Epoch 5/50\n",
      "7920/8000 [============================>.] - ETA: 0s - loss: 0.9315 - accuracy: 0.6691\n",
      "Epoch 00005: val_loss did not improve from 1.09232\n",
      "8000/8000 [==============================] - 34s 4ms/sample - loss: 0.9327 - accuracy: 0.6690 - val_loss: 1.1065 - val_accuracy: 0.6575\n",
      "Epoch 6/50\n",
      "7920/8000 [============================>.] - ETA: 0s - loss: 0.9270 - accuracy: 0.6684\n",
      "Epoch 00006: val_loss improved from 1.09232 to 1.06044, saving model to ../HandGestureRecognitionUsingMnistDataset/bestweight.h5\n",
      "8000/8000 [==============================] - 34s 4ms/sample - loss: 0.9271 - accuracy: 0.6687 - val_loss: 1.0604 - val_accuracy: 0.6565\n",
      "Epoch 7/50\n",
      "7920/8000 [============================>.] - ETA: 0s - loss: 0.9316 - accuracy: 0.6678\n",
      "Epoch 00007: val_loss improved from 1.06044 to 0.99832, saving model to ../HandGestureRecognitionUsingMnistDataset/bestweight.h5\n",
      "8000/8000 [==============================] - 34s 4ms/sample - loss: 0.9303 - accuracy: 0.6676 - val_loss: 0.9983 - val_accuracy: 0.6635\n",
      "Epoch 8/50\n",
      "7920/8000 [============================>.] - ETA: 0s - loss: 0.9165 - accuracy: 0.6711\n",
      "Epoch 00008: val_loss did not improve from 0.99832\n",
      "8000/8000 [==============================] - 34s 4ms/sample - loss: 0.9178 - accuracy: 0.6709 - val_loss: 0.9993 - val_accuracy: 0.6605\n",
      "Epoch 9/50\n",
      "7920/8000 [============================>.] - ETA: 0s - loss: 0.9238 - accuracy: 0.6742\n",
      "Epoch 00009: val_loss did not improve from 0.99832\n",
      "8000/8000 [==============================] - 34s 4ms/sample - loss: 0.9228 - accuracy: 0.6744 - val_loss: 1.0117 - val_accuracy: 0.6630\n",
      "Epoch 10/50\n",
      "7920/8000 [============================>.] - ETA: 0s - loss: 0.9194 - accuracy: 0.6741\n",
      "Epoch 00010: val_loss did not improve from 0.99832\n",
      "8000/8000 [==============================] - 34s 4ms/sample - loss: 0.9193 - accuracy: 0.6740 - val_loss: 0.9995 - val_accuracy: 0.6655\n",
      "Epoch 11/50\n",
      "7920/8000 [============================>.] - ETA: 0s - loss: 0.9201 - accuracy: 0.6676\n",
      "Epoch 00011: val_loss did not improve from 0.99832\n",
      "8000/8000 [==============================] - 34s 4ms/sample - loss: 0.9184 - accuracy: 0.6680 - val_loss: 1.0055 - val_accuracy: 0.6595\n",
      "Epoch 12/50\n",
      "7920/8000 [============================>.] - ETA: 0s - loss: 0.9228 - accuracy: 0.6731\n",
      "Epoch 00012: val_loss improved from 0.99832 to 0.99140, saving model to ../HandGestureRecognitionUsingMnistDataset/bestweight.h5\n",
      "8000/8000 [==============================] - 34s 4ms/sample - loss: 0.9238 - accuracy: 0.6734 - val_loss: 0.9914 - val_accuracy: 0.6680\n",
      "Epoch 13/50\n",
      "7920/8000 [============================>.] - ETA: 0s - loss: 0.9142 - accuracy: 0.6734\n",
      "Epoch 00013: val_loss improved from 0.99140 to 0.98573, saving model to ../HandGestureRecognitionUsingMnistDataset/bestweight.h5\n",
      "8000/8000 [==============================] - 34s 4ms/sample - loss: 0.9145 - accuracy: 0.6737 - val_loss: 0.9857 - val_accuracy: 0.6665\n",
      "Epoch 14/50\n",
      "7920/8000 [============================>.] - ETA: 0s - loss: 0.9182 - accuracy: 0.6699\n",
      "Epoch 00014: val_loss did not improve from 0.98573\n",
      "8000/8000 [==============================] - 34s 4ms/sample - loss: 0.9204 - accuracy: 0.6691 - val_loss: 0.9999 - val_accuracy: 0.6655\n",
      "Epoch 15/50\n",
      "7920/8000 [============================>.] - ETA: 0s - loss: 0.9058 - accuracy: 0.6721\n",
      "Epoch 00015: val_loss did not improve from 0.98573\n",
      "8000/8000 [==============================] - 34s 4ms/sample - loss: 0.9066 - accuracy: 0.6724 - val_loss: 1.0032 - val_accuracy: 0.6675\n",
      "Epoch 16/50\n",
      "7920/8000 [============================>.] - ETA: 0s - loss: 0.9080 - accuracy: 0.6747\n",
      "Epoch 00016: val_loss did not improve from 0.98573\n",
      "8000/8000 [==============================] - 34s 4ms/sample - loss: 0.9099 - accuracy: 0.6747 - val_loss: 0.9885 - val_accuracy: 0.6700\n",
      "Epoch 17/50\n",
      "7920/8000 [============================>.] - ETA: 0s - loss: 0.9096 - accuracy: 0.6770\n",
      "Epoch 00017: val_loss did not improve from 0.98573\n",
      "8000/8000 [==============================] - 35s 4ms/sample - loss: 0.9087 - accuracy: 0.6773 - val_loss: 0.9899 - val_accuracy: 0.6685\n",
      "Epoch 18/50\n",
      "7920/8000 [============================>.] - ETA: 0s - loss: 0.9024 - accuracy: 0.6789\n",
      "Epoch 00018: val_loss did not improve from 0.98573\n",
      "8000/8000 [==============================] - 34s 4ms/sample - loss: 0.9022 - accuracy: 0.6786 - val_loss: 0.9967 - val_accuracy: 0.6710\n",
      "Epoch 19/50\n",
      "7920/8000 [============================>.] - ETA: 0s - loss: 0.9089 - accuracy: 0.6753\n",
      "Epoch 00019: val_loss did not improve from 0.98573\n",
      "8000/8000 [==============================] - 34s 4ms/sample - loss: 0.9097 - accuracy: 0.6749 - val_loss: 0.9965 - val_accuracy: 0.6665\n",
      "Epoch 20/50\n",
      "7920/8000 [============================>.] - ETA: 0s - loss: 0.9202 - accuracy: 0.6730\n",
      "Epoch 00020: val_loss did not improve from 0.98573\n",
      "8000/8000 [==============================] - 34s 4ms/sample - loss: 0.9194 - accuracy: 0.6730 - val_loss: 0.9982 - val_accuracy: 0.6695\n",
      "Epoch 21/50\n",
      "7920/8000 [============================>.] - ETA: 0s - loss: 0.9029 - accuracy: 0.6740\n",
      "Epoch 00021: val_loss improved from 0.98573 to 0.98301, saving model to ../HandGestureRecognitionUsingMnistDataset/bestweight.h5\n",
      "8000/8000 [==============================] - 34s 4ms/sample - loss: 0.9041 - accuracy: 0.6737 - val_loss: 0.9830 - val_accuracy: 0.6695\n",
      "Epoch 22/50\n",
      "7920/8000 [============================>.] - ETA: 0s - loss: 0.9107 - accuracy: 0.6760\n",
      "Epoch 00022: val_loss did not improve from 0.98301\n",
      "8000/8000 [==============================] - 34s 4ms/sample - loss: 0.9105 - accuracy: 0.6760 - val_loss: 0.9999 - val_accuracy: 0.6605\n",
      "Epoch 23/50\n",
      "7920/8000 [============================>.] - ETA: 0s - loss: 0.9164 - accuracy: 0.6761\n",
      "Epoch 00023: val_loss did not improve from 0.98301\n",
      "8000/8000 [==============================] - 34s 4ms/sample - loss: 0.9166 - accuracy: 0.6765 - val_loss: 0.9906 - val_accuracy: 0.6685\n",
      "Epoch 24/50\n",
      "7920/8000 [============================>.] - ETA: 0s - loss: 0.9072 - accuracy: 0.6758\n",
      "Epoch 00024: val_loss did not improve from 0.98301\n",
      "8000/8000 [==============================] - 34s 4ms/sample - loss: 0.9075 - accuracy: 0.6759 - val_loss: 0.9974 - val_accuracy: 0.6675\n",
      "Epoch 25/50\n",
      "7920/8000 [============================>.] - ETA: 0s - loss: 0.9121 - accuracy: 0.6711\n",
      "Epoch 00025: val_loss did not improve from 0.98301\n",
      "8000/8000 [==============================] - 34s 4ms/sample - loss: 0.9125 - accuracy: 0.6706 - val_loss: 0.9870 - val_accuracy: 0.6655\n",
      "Epoch 26/50\n",
      "7920/8000 [============================>.] - ETA: 0s - loss: 0.9159 - accuracy: 0.6750\n",
      "Epoch 00026: val_loss did not improve from 0.98301\n",
      "8000/8000 [==============================] - 34s 4ms/sample - loss: 0.9156 - accuracy: 0.6751 - val_loss: 0.9937 - val_accuracy: 0.6675\n",
      "Epoch 27/50\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7920/8000 [============================>.] - ETA: 0s - loss: 0.9151 - accuracy: 0.6707\n",
      "Epoch 00027: val_loss did not improve from 0.98301\n",
      "8000/8000 [==============================] - 34s 4ms/sample - loss: 0.9161 - accuracy: 0.6704 - val_loss: 0.9898 - val_accuracy: 0.6655\n",
      "Epoch 28/50\n",
      "7920/8000 [============================>.] - ETA: 0s - loss: 0.9180 - accuracy: 0.6657\n",
      "Epoch 00028: val_loss improved from 0.98301 to 0.98063, saving model to ../HandGestureRecognitionUsingMnistDataset/bestweight.h5\n",
      "8000/8000 [==============================] - 34s 4ms/sample - loss: 0.9158 - accuracy: 0.6670 - val_loss: 0.9806 - val_accuracy: 0.6715\n",
      "Epoch 29/50\n",
      "7920/8000 [============================>.] - ETA: 0s - loss: 0.9001 - accuracy: 0.6817\n",
      "Epoch 00029: val_loss did not improve from 0.98063\n",
      "8000/8000 [==============================] - 35s 4ms/sample - loss: 0.8991 - accuracy: 0.6820 - val_loss: 0.9966 - val_accuracy: 0.6645\n",
      "Epoch 30/50\n",
      "7920/8000 [============================>.] - ETA: 0s - loss: 0.9068 - accuracy: 0.6729\n",
      "Epoch 00030: val_loss did not improve from 0.98063\n",
      "8000/8000 [==============================] - 34s 4ms/sample - loss: 0.9064 - accuracy: 0.6730 - val_loss: 0.9865 - val_accuracy: 0.6645\n",
      "Epoch 31/50\n",
      "7920/8000 [============================>.] - ETA: 0s - loss: 0.9144 - accuracy: 0.6811\n",
      "Epoch 00031: val_loss did not improve from 0.98063\n",
      "8000/8000 [==============================] - 35s 4ms/sample - loss: 0.9155 - accuracy: 0.6804 - val_loss: 0.9925 - val_accuracy: 0.6670\n",
      "Epoch 32/50\n",
      "7920/8000 [============================>.] - ETA: 0s - loss: 0.9118 - accuracy: 0.6747\n",
      "Epoch 00032: val_loss did not improve from 0.98063\n",
      "8000/8000 [==============================] - 36s 4ms/sample - loss: 0.9130 - accuracy: 0.6745 - val_loss: 0.9891 - val_accuracy: 0.6680\n",
      "Epoch 33/50\n",
      "7920/8000 [============================>.] - ETA: 0s - loss: 0.9113 - accuracy: 0.6777\n",
      "Epoch 00033: val_loss did not improve from 0.98063\n",
      "8000/8000 [==============================] - 35s 4ms/sample - loss: 0.9107 - accuracy: 0.6776 - val_loss: 0.9930 - val_accuracy: 0.6685\n",
      "Epoch 34/50\n",
      "7920/8000 [============================>.] - ETA: 0s - loss: 0.9081 - accuracy: 0.6716\n",
      "Epoch 00034: val_loss did not improve from 0.98063\n",
      "8000/8000 [==============================] - 35s 4ms/sample - loss: 0.9068 - accuracy: 0.6721 - val_loss: 0.9825 - val_accuracy: 0.6670\n",
      "Epoch 35/50\n",
      "7920/8000 [============================>.] - ETA: 0s - loss: 0.8937 - accuracy: 0.6830\n",
      "Epoch 00035: val_loss did not improve from 0.98063\n",
      "8000/8000 [==============================] - 36s 5ms/sample - loss: 0.8926 - accuracy: 0.6835 - val_loss: 0.9938 - val_accuracy: 0.6670\n",
      "Epoch 36/50\n",
      "7920/8000 [============================>.] - ETA: 0s - loss: 0.9187 - accuracy: 0.6711\n",
      "Epoch 00036: val_loss did not improve from 0.98063\n",
      "8000/8000 [==============================] - 34s 4ms/sample - loss: 0.9190 - accuracy: 0.6711 - val_loss: 1.0098 - val_accuracy: 0.6635\n",
      "Epoch 37/50\n",
      "7920/8000 [============================>.] - ETA: 0s - loss: 0.9049 - accuracy: 0.6770\n",
      "Epoch 00037: val_loss did not improve from 0.98063\n",
      "8000/8000 [==============================] - 34s 4ms/sample - loss: 0.9046 - accuracy: 0.6771 - val_loss: 1.0070 - val_accuracy: 0.6635\n",
      "Epoch 38/50\n",
      "7920/8000 [============================>.] - ETA: 0s - loss: 0.9185 - accuracy: 0.6720\n",
      "Epoch 00038: val_loss did not improve from 0.98063\n",
      "8000/8000 [==============================] - 34s 4ms/sample - loss: 0.9176 - accuracy: 0.6724 - val_loss: 0.9880 - val_accuracy: 0.6610\n"
     ]
    }
   ],
   "source": [
    "batch_size = 132\n",
    "epoch = 50\n",
    "history = model.fit(x=X_train,y=y_train,batch_size=batch_size,epochs=epoch,validation_split = 0.20,verbose=1,callbacks=[earlystop,reduce_lr,mcp])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "id": "medical-firewall",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'loss': [0.9495854872763156,\n",
       "  0.9453020444214344,\n",
       "  0.9442794869244099,\n",
       "  0.9469992652535438,\n",
       "  0.9326776329278946,\n",
       "  0.927093661993742,\n",
       "  0.9302931317090988,\n",
       "  0.9177526409327984,\n",
       "  0.9227803989946842,\n",
       "  0.9192880414426327,\n",
       "  0.918408262938261,\n",
       "  0.9237736931145191,\n",
       "  0.914473569482565,\n",
       "  0.920411417633295,\n",
       "  0.906563556611538,\n",
       "  0.9099333702921867,\n",
       "  0.9086674618422985,\n",
       "  0.9022282868027687,\n",
       "  0.9097092979550362,\n",
       "  0.9194321795701981,\n",
       "  0.9041050127446651,\n",
       "  0.9105350058674813,\n",
       "  0.9165623835921287,\n",
       "  0.9075232070088387,\n",
       "  0.9125433737039566,\n",
       "  0.9155936156213283,\n",
       "  0.9160514540970326,\n",
       "  0.9157912639379502,\n",
       "  0.8990803453028202,\n",
       "  0.9064038655459881,\n",
       "  0.9154898245036602,\n",
       "  0.912953162163496,\n",
       "  0.9107190055251122,\n",
       "  0.9067578064799309,\n",
       "  0.8925557076632976,\n",
       "  0.9190336818695068,\n",
       "  0.904628861695528,\n",
       "  0.9176390172541141],\n",
       " 'accuracy': [0.66,\n",
       "  0.66625,\n",
       "  0.665625,\n",
       "  0.660375,\n",
       "  0.669,\n",
       "  0.66875,\n",
       "  0.667625,\n",
       "  0.670875,\n",
       "  0.674375,\n",
       "  0.674,\n",
       "  0.668,\n",
       "  0.673375,\n",
       "  0.67375,\n",
       "  0.669125,\n",
       "  0.672375,\n",
       "  0.67475,\n",
       "  0.67725,\n",
       "  0.678625,\n",
       "  0.674875,\n",
       "  0.673,\n",
       "  0.67375,\n",
       "  0.676,\n",
       "  0.6765,\n",
       "  0.675875,\n",
       "  0.670625,\n",
       "  0.675125,\n",
       "  0.670375,\n",
       "  0.667,\n",
       "  0.682,\n",
       "  0.673,\n",
       "  0.680375,\n",
       "  0.6745,\n",
       "  0.677625,\n",
       "  0.672125,\n",
       "  0.6835,\n",
       "  0.671125,\n",
       "  0.677125,\n",
       "  0.672375],\n",
       " 'val_loss': [2.8362852516174315,\n",
       "  2.5046337432861328,\n",
       "  1.478323011636734,\n",
       "  1.0923243380784988,\n",
       "  1.1065171885490417,\n",
       "  1.0604364119768144,\n",
       "  0.9983185416460038,\n",
       "  0.9992510672807694,\n",
       "  1.0117173043489456,\n",
       "  0.9994834467172623,\n",
       "  1.005521690249443,\n",
       "  0.9914010097980499,\n",
       "  0.9857332737445831,\n",
       "  0.9998819996118545,\n",
       "  1.0031964908838271,\n",
       "  0.9884540395736694,\n",
       "  0.9899323550462723,\n",
       "  0.9966564297676086,\n",
       "  0.9964747226238251,\n",
       "  0.9982288762331009,\n",
       "  0.983010172367096,\n",
       "  0.9999448075294495,\n",
       "  0.9905911008119583,\n",
       "  0.9973949006795884,\n",
       "  0.9869854120016098,\n",
       "  0.9936515597105027,\n",
       "  0.9897699085474014,\n",
       "  0.9806344681978225,\n",
       "  0.9966024792194367,\n",
       "  0.9864672720432281,\n",
       "  0.9925369637012482,\n",
       "  0.9891324954032898,\n",
       "  0.9930432969331742,\n",
       "  0.9825400395393371,\n",
       "  0.993839075088501,\n",
       "  1.0097665994167329,\n",
       "  1.0069737317562104,\n",
       "  0.9879749984741211],\n",
       " 'val_accuracy': [0.4435,\n",
       "  0.5445,\n",
       "  0.531,\n",
       "  0.6485,\n",
       "  0.6575,\n",
       "  0.6565,\n",
       "  0.6635,\n",
       "  0.6605,\n",
       "  0.663,\n",
       "  0.6655,\n",
       "  0.6595,\n",
       "  0.668,\n",
       "  0.6665,\n",
       "  0.6655,\n",
       "  0.6675,\n",
       "  0.67,\n",
       "  0.6685,\n",
       "  0.671,\n",
       "  0.6665,\n",
       "  0.6695,\n",
       "  0.6695,\n",
       "  0.6605,\n",
       "  0.6685,\n",
       "  0.6675,\n",
       "  0.6655,\n",
       "  0.6675,\n",
       "  0.6655,\n",
       "  0.6715,\n",
       "  0.6645,\n",
       "  0.6645,\n",
       "  0.667,\n",
       "  0.668,\n",
       "  0.6685,\n",
       "  0.667,\n",
       "  0.667,\n",
       "  0.6635,\n",
       "  0.6635,\n",
       "  0.661],\n",
       " 'lr': [0.000100000005,\n",
       "  0.000100000005,\n",
       "  0.000100000005,\n",
       "  0.000100000005,\n",
       "  0.000100000005,\n",
       "  1.0000001e-05,\n",
       "  1.0000001e-05,\n",
       "  1.0000001e-05,\n",
       "  1e-05,\n",
       "  1e-05,\n",
       "  1e-05,\n",
       "  1e-05,\n",
       "  1e-05,\n",
       "  1e-05,\n",
       "  1e-05,\n",
       "  1e-05,\n",
       "  1e-05,\n",
       "  1e-05,\n",
       "  1e-05,\n",
       "  1e-05,\n",
       "  1e-05,\n",
       "  1e-05,\n",
       "  1e-05,\n",
       "  1e-05,\n",
       "  1e-05,\n",
       "  1e-05,\n",
       "  1e-05,\n",
       "  1e-05,\n",
       "  1e-05,\n",
       "  1e-05,\n",
       "  1e-05,\n",
       "  1e-05,\n",
       "  1e-05,\n",
       "  1e-05,\n",
       "  1e-05,\n",
       "  1e-05,\n",
       "  1e-05,\n",
       "  1e-05]}"
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "history.history"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "registered-cigarette",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "2000/1 [================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================] - 1s 516us/sample - loss: 1.0011 - accuracy: 0.6580\n"
     ]
    }
   ],
   "source": [
    "results =model.evaluate(x= X_test, y= y_test,batch_size = 132)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "id": "casual-relief",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "def plot(history):\n",
    "   \n",
    "    \n",
    "    plt.figure(figsize = (10,5))\n",
    "    \n",
    "    plt.subplot(1,2,1)\n",
    "    plt.plot(history['loss'], label = 'Training Loss')\n",
    "    plt.plot(history['val_loss'], label = 'Validation Loss')\n",
    "    plt.title('Training and Validation loss')\n",
    "    plt.xlabel('epochs')\n",
    "    plt.ylabel('Loss')\n",
    "    plt.legend()\n",
    "    \n",
    "    plt.subplot(1,2,2)\n",
    "    plt.plot(history['accuracy'], label = 'Training Accuracy')\n",
    "    plt.plot(history['val_accuracy'], label = 'Validation Accuracy')\n",
    "    plt.title('Training and validation accuracy')\n",
    "    plt.xlabel('epochs')\n",
    "    plt.ylabel('accuracy')\n",
    "    plt.legend()\n",
    "    \n",
    "    plt.show()\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "id": "controlled-camel",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(history.history)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "interior-noise",
   "metadata": {},
   "outputs": [],
   "source": [
    "model.load_weights('../HandGestureRecognitionUsingMnistDataset/bestweight.h5')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "preceding-agenda",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting h5py<3.0.0\n",
      "  Downloading h5py-2.10.0-cp37-cp37m-manylinux1_x86_64.whl (2.9 MB)\n",
      "\u001b[K     |████████████████████████████████| 2.9 MB 3.1 MB/s eta 0:00:01\n",
      "\u001b[?25hRequirement already satisfied: six in /home/labina/anaconda3/envs/gesture/lib/python3.7/site-packages (from h5py<3.0.0) (1.15.0)\n",
      "Requirement already satisfied: numpy>=1.7 in /home/labina/anaconda3/envs/gesture/lib/python3.7/site-packages (from h5py<3.0.0) (1.19.4)\n",
      "Installing collected packages: h5py\n",
      "  Attempting uninstall: h5py\n",
      "    Found existing installation: h5py 3.1.0\n",
      "    Uninstalling h5py-3.1.0:\n",
      "      Successfully uninstalled h5py-3.1.0\n",
      "Successfully installed h5py-2.10.0\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "pip install 'h5py<3.0.0'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "fuzzy-teddy",
   "metadata": {},
   "outputs": [],
   "source": [
    "prediction = model.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "reasonable-block",
   "metadata": {},
   "outputs": [],
   "source": [
    "prediction = np.argmax(prediction,axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "knowing-perspective",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([7, 7, 2, ..., 0, 9, 4])"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "opened-session",
   "metadata": {},
   "outputs": [],
   "source": [
    "y_test = np.argmax(y_test,axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "modern-setup",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([7, 7, 2, ..., 8, 9, 9])"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "sought-notebook",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([7, 2, 2, 1, 1, 0, 0, 4, 4])"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_test[1:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "labeled-clock",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([7, 2, 5, 1, 1, 0, 0, 4, 2])"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prediction[1:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "authentic-lesson",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.662"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "accuracy_score(y_test,prediction)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "dressed-instrument",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "accuracy score: 0.662\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x576 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.metrics import confusion_matrix,accuracy_score\n",
    "\n",
    "def plot_confusion_matrix(model_name):\n",
    "    # Predict the values from the validation dataset\n",
    "    y_pred = model_name.predict(X_test)\n",
    "    # Because Y_pred is an array of probabilities, we have to convert it to one hot vectors \n",
    "    y_pred = np.argmax(y_pred,axis = 1)\n",
    "    #y_test = np.argmax(y_test,axis=1)\n",
    "    #Compute and print the accuracy scores:\n",
    "    print('accuracy score:', accuracy_score(y_test,y_pred))\n",
    "    # compute the confusion matrix .\n",
    "    cm = confusion_matrix(y_test, y_pred)\n",
    "    cm = pd.DataFrame(cm, index = range(10), columns = range(10))\n",
    "    # plot the confusion matrix\n",
    "    plt.figure(figsize=(8,8))\n",
    "    sns.heatmap(cm, cmap=\"Reds\", annot=True, fmt='.0f')\n",
    "    plt.ylabel('True label')\n",
    "    plt.xlabel('Predicted label')\n",
    "    plt.show()\n",
    "    return\n",
    "\n",
    "plot_confusion_matrix(model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "academic-square",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<PIL.Image.Image image mode=RGBA size=1368x75 at 0x7FAC4C2F2390>"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import visualkeras\n",
    "visualkeras.layered_view(model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "american-timeline",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.7.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}