Alexnet on RAVDESS dataset.ipynb

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   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "Collecting plotly\n",
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      "Using legacy 'setup.py install' for retrying, since package 'wheel' is not installed.\n",
      "Installing collected packages: retrying, plotly\n",
      "    Running setup.py install for retrying: started\n",
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     ]
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       "        </script>\n",
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     "metadata": {},
     "output_type": "display_data"
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   ],
   "source": [
    "## Importing libraries\n",
    "\n",
    "!pip install librosa\n",
    "!pip install tqdm\n",
    "!pip install plotly\n",
    "import os\n",
    "import random\n",
    "import sys\n",
    "import glob\n",
    "import IPython.display as ipd\n",
    "import librosa\n",
    "import librosa.display\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import scipy.stats\n",
    "import warnings\n",
    "from sklearn.model_selection import StratifiedShuffleSplit\n",
    "from scipy.fftpack import fft\n",
    "from scipy import signal\n",
    "from scipy.io import wavfile\n",
    "from tqdm import tqdm\n",
    "import plotly.offline as py\n",
    "\n",
    "warnings.simplefilter(\"ignore\")\n",
    "pd.set_option('display.max_columns', None)\n",
    "py.init_notebook_mode(connected=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Loading Data\n",
    "def metadata(basepath):\n",
    "    dir_list = os.listdir(basepath)\n",
    "    dir_list.sort()\n",
    "\n",
    "    ## DataFrame to save metadata of Ravdess audio files\n",
    "    df = pd.DataFrame(columns=['path', 'source', 'actor', 'gender', 'intensity', 'statement', 'repetition', 'emotion'])\n",
    "    count = 0\n",
    "\n",
    "    ## Iterating through the directory, reading audio files, and extracting information from the file name\n",
    "    for f in os.listdir(basepath):\n",
    "        filename = f.split('.')[0].split('-')\n",
    "        if(len(filename)==7):\n",
    "            path = basepath + f\n",
    "            src = int(filename[1])\n",
    "            actor = int(filename[-1])\n",
    "            emotion = int(filename[2])\n",
    "            if int(actor)%2 == 0:\n",
    "                gender = \"female\"\n",
    "            else:\n",
    "                gender = \"male\"\n",
    "\n",
    "            if filename[3] == '01':\n",
    "                intensity = 0\n",
    "            else:\n",
    "                intensity = 1\n",
    "\n",
    "            if filename[4] == '01':\n",
    "                statement = 0\n",
    "            else:\n",
    "                statement = 1\n",
    "\n",
    "            if filename[5] == '01':\n",
    "                repeat = 0\n",
    "            else:\n",
    "                repeat = 1\n",
    "\n",
    "            df.loc[count] = [path, src, actor, gender, intensity, statement, repeat, emotion]\n",
    "        count += 1\n",
    "        \n",
    "    labels = []\n",
    "    y=[]\n",
    "    for i in range(len(df)):\n",
    "        if df.emotion.iloc[i] == 1:\n",
    "            label = \"_neutral\"\n",
    "            y.append(1)\n",
    "        elif df.emotion.iloc[i] == 2:\n",
    "            label = \"_calm\"\n",
    "            y.append(2)\n",
    "        elif df.emotion.iloc[i] == 3:\n",
    "            label = \"_happy\"\n",
    "            y.append(3)\n",
    "        elif df.emotion.iloc[i] == 4:\n",
    "            label = \"_sad\"\n",
    "            y.append(4)\n",
    "        elif df.emotion.iloc[i] == 5:\n",
    "            label = \"_angry\"\n",
    "            y.append(5)\n",
    "        elif df.emotion.iloc[i] == 6:\n",
    "            label = \"_fearful\"\n",
    "            y.append(6)\n",
    "        elif df.emotion.iloc[i] == 7:\n",
    "            label = \"_disgust\"\n",
    "            y.append(7)\n",
    "        elif df.emotion.iloc[i] == 8:\n",
    "            label = \"_surprised\"\n",
    "            y.append(8)\n",
    "        else:\n",
    "            label = \"_none\"\n",
    "\n",
    "        # Add gender to the label \n",
    "        labels.append(label)\n",
    "\n",
    "    df['label'] = labels\n",
    "    \n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = metadata(\"C:/Users/Shireen/A FINAL SER ATTEMPT/data/wavfiles\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [],
   "source": [
    "y = df.emotion.values.tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Spectrograms():\n",
    "    def __init__(self, df, datasettype, outputpath, sample=False, augmentation=False, mel=True, mfcc=False, spectral=False, mfccbanks=20, n_mels=128):\n",
    "        self.df = df\n",
    "        self.augmentation = augmentation\n",
    "        self.mel = mel\n",
    "        self.mfcc = mfcc\n",
    "        self.spectral = spectral\n",
    "        self.mfccbanks = mfccbanks\n",
    "        self.n_mels = n_mels\n",
    "        self.outputpath = outputpath\n",
    "        self.datasettype = datasettype\n",
    "        self.sample = sample\n",
    "        \n",
    "    def get_spectrograms(self):\n",
    "        if self.sample:\n",
    "            x, sample_rate = librosa.load(self.df.index[0])\n",
    "            self.generate(x, sample_rate, '', 0)\n",
    "        \n",
    "        else:\n",
    "            for file in tqdm(range(self.df.shape[0])):\n",
    "                emotion = df.iloc[file, df.columns.get_loc('label')]\n",
    "                path = self.outputpath+self.datasettype+\"/\"+str(emotion)+\"/\"\n",
    "\n",
    "                if not os.path.isdir(path):\n",
    "                    os.makedirs(path)\n",
    "\n",
    "                ## Reading signal from .wav file\n",
    "                x, sample_rate = librosa.load(self.df.index[file])\n",
    "                emo = df.iloc[file, df.columns.get_loc('emotion')]\n",
    "                self.generate(x, sample_rate, path, file, emo)\n",
    "\n",
    "        \n",
    "    def generate(self, x, sample_rate, path, count, emo):\n",
    "        if self.mel:\n",
    "            mel_features = librosa.feature.melspectrogram(x, sr=sample_rate, n_mels=self.n_mels)\n",
    "            log_mel_features = librosa.power_to_db(mel_features, ref=np.max)\n",
    "            fig = plt.figure(figsize=(12,4))\n",
    "            ax = plt.Axes(fig, [0., 0., 1., 1.])\n",
    "            ax.set_axis_off()\n",
    "            fig.add_axes(ax)\n",
    "            librosa.display.specshow(log_mel_features, sr=sample_rate, x_axis='time', y_axis='mel')\n",
    "            if self.sample:\n",
    "                plt.show()\n",
    "            else:\n",
    "                plt.savefig(path+emo+\"-\"+str(count)+\".jpg\")\n",
    "                plt.close()\n",
    "            \n",
    "        if self.mfcc:\n",
    "            mfcc_features = librosa.feature.mfcc(x, sr=sample_rate, n_mfcc=self.mfccbanks)\n",
    "            fig = plt.figure(figsize=(12,4))\n",
    "            ax = plt.Axes(fig, [0., 0., 1., 1.])\n",
    "            ax.set_axis_off()\n",
    "            fig.add_axes(ax)\n",
    "            librosa.display.specshow(mfcc_features, sr=sample_rate, x_axis='time', y_axis='mel')\n",
    "            if self.sample:\n",
    "                plt.show()\n",
    "            else:\n",
    "                plt.savefig(path+\"mfccspectrogram_\"+str(count)+\".jpg\")\n",
    "                plt.close()\n",
    "            \n",
    "        if self.spectral:\n",
    "            spectral_features = librosa.feature.spectral_contrast(x, sr=sample_rate)\n",
    "            fig = plt.figure(figsize=(12,4))\n",
    "            ax = plt.Axes(fig, [0., 0., 1., 1.])\n",
    "            ax.set_axis_off()\n",
    "            fig.add_axes(ax)\n",
    "            librosa.display.specshow(spectral_features, sr=sample_rate, x_axis='time', y_axis='mel')\n",
    "            if self.sample:\n",
    "                plt.show()\n",
    "            else:\n",
    "                plt.savefig(path+\"spectralspectrogram_\"+str(count)+\".jpg\")\n",
    "                plt.close()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_new = metadata(\"C:/Users/Shireen/A FINAL SER ATTEMPT/data/wavfiles/\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_new.index = df_new.path\n",
    "df_new = df_new.drop(\"path\", axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████████████████████████████████████████████████████████████████████████| 1440/1440 [06:11<00:00,  3.88it/s]\n"
     ]
    }
   ],
   "source": [
    "spectrograms = Spectrograms(df_new, 'images_new', 'C:/Users/Shireen/A FINAL SER ATTEMPT/data/spectograms/', sample=False)\n",
    "spectrograms.get_spectrograms()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: opencv-python in c:\\users\\shireen\\lib\\site-packages (4.4.0.40)\n",
      "Requirement already satisfied: numpy>=1.17.3 in c:\\users\\shireen\\lib\\site-packages (from opencv-python) (1.18.5)\n"
     ]
    }
   ],
   "source": [
    "!pip install opencv-python\n",
    "import os\n",
    "import cv2\n",
    "import numpy as np\n",
    "from PIL import Image\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "categories = os.listdir(\"C:/Users/Shireen/A FINAL SER ATTEMPT/data/spectograms/images/\")\n",
    "len(categories)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No. of images loaded =  1440 \n",
      "No. of labels loaded =  1440\n",
      "<class 'list'> <class 'list'>\n"
     ]
    }
   ],
   "source": [
    "def load_images_and_labels(categories):\n",
    "    img_lst=[]\n",
    "    labels=[]\n",
    "    for index, category in enumerate(categories):\n",
    "        for image_name in os.listdir(fpath+\"/\"+category):\n",
    "            img = cv2.imread(fpath+\"/\"+category+\"/\"+image_name)\n",
    "            img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)\n",
    "            \n",
    "            img_array = Image.fromarray(img, 'RGB')\n",
    "            \n",
    "            #resize image to 227 x 227 because the input image resolution for AlexNet is 227 x 227\n",
    "            resized_img = img_array.resize((227, 227))\n",
    "            \n",
    "            img_lst.append(np.array(resized_img))\n",
    "            \n",
    "            labels.append(index)\n",
    "    return img_lst, labels\n",
    "\n",
    "fpath = \"C:/Users/Shireen/A FINAL SER ATTEMPT/data/spectograms/images/\"\n",
    "images, labels = load_images_and_labels(categories)\n",
    "print(\"No. of images loaded = \",len(images),\"\\nNo. of labels loaded = \",len(labels))\n",
    "print(type(images),type(labels))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Images shape =  (1440, 227, 227, 3) \n",
      "Labels shape =  (1440,)\n",
      "<class 'numpy.ndarray'> <class 'numpy.ndarray'>\n"
     ]
    }
   ],
   "source": [
    "images = np.array(images)\n",
    "labels = np.array(labels)\n",
    "\n",
    "print(\"Images shape = \",images.shape,\"\\nLabels shape = \",labels.shape)\n",
    "print(type(images),type(labels))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "'n' values before shuffling =  [   0    1    2 ... 1437 1438 1439]\n",
      "\n",
      "'n' values after shuffling =  [ 168  605  548 ... 1294  860 1126]\n"
     ]
    }
   ],
   "source": [
    "#1-step in data shuffling\n",
    "random_seed=42\n",
    "#get equally spaced numbers in a given range\n",
    "n = np.arange(images.shape[0])\n",
    "print(\"'n' values before shuffling = \",n)\n",
    "\n",
    "#shuffle all the equally spaced values in list 'n'\n",
    "np.random.seed(random_seed)\n",
    "np.random.shuffle(n)\n",
    "print(\"\\n'n' values after shuffling = \",n)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Images shape after shuffling =  (1440, 227, 227, 3) \n",
      "Labels shape after shuffling =  (1440,)\n"
     ]
    }
   ],
   "source": [
    "#2-step in data shuffling\n",
    "\n",
    "#shuffle images and corresponding labels data in both the lists\n",
    "images = images[n]\n",
    "labels = labels[n]\n",
    "\n",
    "print(\"Images shape after shuffling = \",images.shape,\"\\nLabels shape after shuffling = \",labels.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Images shape after normalization =  (1440, 227, 227, 3)\n"
     ]
    }
   ],
   "source": [
    "images = images.astype(np.float32)\n",
    "labels = labels.astype(np.int32)\n",
    "images = images/255\n",
    "print(\"Images shape after normalization = \",images.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x_train shape =  (1152, 227, 227, 3)\n",
      "y_train shape =  (1152,)\n",
      "\n",
      "x_test shape =  (288, 227, 227, 3)\n",
      "y_test shape =  (288,)\n"
     ]
    }
   ],
   "source": [
    "x_train, x_test, y_train, y_test = train_test_split(images, labels, test_size = 0.2, random_state = random_seed)\n",
    "\n",
    "print(\"x_train shape = \",x_train.shape)\n",
    "print(\"y_train shape = \",y_train.shape)\n",
    "print(\"\\nx_test shape = \",x_test.shape)\n",
    "print(\"y_test shape = \",y_test.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tensorflow import keras\n",
    "from keras.models import Sequential\n",
    "from keras.layers import Conv2D,MaxPooling2D,Dense,Flatten,Dropout\n",
    "from keras.layers.normalization import BatchNormalization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential_7\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "conv2d_25 (Conv2D)           (None, 55, 55, 96)        34944     \n",
      "_________________________________________________________________\n",
      "max_pooling2d_15 (MaxPooling (None, 27, 27, 96)        0         \n",
      "_________________________________________________________________\n",
      "batch_normalization_12 (Batc (None, 27, 27, 96)        384       \n",
      "_________________________________________________________________\n",
      "conv2d_26 (Conv2D)           (None, 23, 23, 256)       614656    \n",
      "_________________________________________________________________\n",
      "max_pooling2d_16 (MaxPooling (None, 11, 11, 256)       0         \n",
      "_________________________________________________________________\n",
      "batch_normalization_13 (Batc (None, 11, 11, 256)       1024      \n",
      "_________________________________________________________________\n",
      "conv2d_27 (Conv2D)           (None, 9, 9, 384)         885120    \n",
      "_________________________________________________________________\n",
      "conv2d_28 (Conv2D)           (None, 7, 7, 384)         1327488   \n",
      "_________________________________________________________________\n",
      "conv2d_29 (Conv2D)           (None, 5, 5, 256)         884992    \n",
      "_________________________________________________________________\n",
      "max_pooling2d_17 (MaxPooling (None, 2, 2, 256)         0         \n",
      "_________________________________________________________________\n",
      "batch_normalization_14 (Batc (None, 2, 2, 256)         1024      \n",
      "_________________________________________________________________\n",
      "flatten_6 (Flatten)          (None, 1024)              0         \n",
      "_________________________________________________________________\n",
      "dense_22 (Dense)             (None, 4096)              4198400   \n",
      "_________________________________________________________________\n",
      "dropout_15 (Dropout)         (None, 4096)              0         \n",
      "_________________________________________________________________\n",
      "batch_normalization_15 (Batc (None, 4096)              16384     \n",
      "_________________________________________________________________\n",
      "dense_23 (Dense)             (None, 4096)              16781312  \n",
      "_________________________________________________________________\n",
      "dropout_16 (Dropout)         (None, 4096)              0         \n",
      "_________________________________________________________________\n",
      "batch_normalization_16 (Batc (None, 4096)              16384     \n",
      "_________________________________________________________________\n",
      "dense_24 (Dense)             (None, 1000)              4097000   \n",
      "_________________________________________________________________\n",
      "dropout_17 (Dropout)         (None, 1000)              0         \n",
      "_________________________________________________________________\n",
      "batch_normalization_17 (Batc (None, 1000)              4000      \n",
      "_________________________________________________________________\n",
      "dense_25 (Dense)             (None, 20)                20020     \n",
      "=================================================================\n",
      "Total params: 28,883,132\n",
      "Trainable params: 28,863,532\n",
      "Non-trainable params: 19,600\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model=Sequential()\n",
    "\n",
    "#1 conv layer\n",
    "model.add(Conv2D(filters=96,kernel_size=(11,11),strides=(4,4),padding=\"valid\",activation=\"relu\",input_shape=(227,227,3)))\n",
    "\n",
    "#1 max pool layer\n",
    "model.add(MaxPooling2D(pool_size=(3,3),strides=(2,2)))\n",
    "\n",
    "model.add(BatchNormalization())\n",
    "\n",
    "#2 conv layer\n",
    "model.add(Conv2D(filters=256,kernel_size=(5,5),strides=(1,1),padding=\"valid\",activation=\"relu\"))\n",
    "\n",
    "#2 max pool layer\n",
    "model.add(MaxPooling2D(pool_size=(3,3),strides=(2,2)))\n",
    "\n",
    "model.add(BatchNormalization())\n",
    "\n",
    "#3 conv layer\n",
    "model.add(Conv2D(filters=384,kernel_size=(3,3),strides=(1,1),padding=\"valid\",activation=\"relu\"))\n",
    "\n",
    "#4 conv layer\n",
    "model.add(Conv2D(filters=384,kernel_size=(3,3),strides=(1,1),padding=\"valid\",activation=\"relu\"))\n",
    "\n",
    "#5 conv layer\n",
    "model.add(Conv2D(filters=256,kernel_size=(3,3),strides=(1,1),padding=\"valid\",activation=\"relu\"))\n",
    "\n",
    "#3 max pool layer\n",
    "model.add(MaxPooling2D(pool_size=(3,3),strides=(2,2)))\n",
    "\n",
    "model.add(BatchNormalization())\n",
    "\n",
    "\n",
    "model.add(Flatten())\n",
    "\n",
    "#1 dense layer\n",
    "model.add(Dense(4096,input_shape=(227,227,3),activation=\"relu\"))\n",
    "\n",
    "model.add(Dropout(0.4))\n",
    "\n",
    "model.add(BatchNormalization())\n",
    "\n",
    "#2 dense layer\n",
    "model.add(Dense(4096,activation=\"relu\"))\n",
    "\n",
    "model.add(Dropout(0.4))\n",
    "\n",
    "model.add(BatchNormalization())\n",
    "\n",
    "#3 dense layer\n",
    "model.add(Dense(1000,activation=\"relu\"))\n",
    "\n",
    "model.add(Dropout(0.4))\n",
    "\n",
    "model.add(BatchNormalization())\n",
    "\n",
    "#output layer\n",
    "model.add(Dense(20,activation=\"softmax\"))\n",
    "\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.compile(optimizer=\"adam\", loss=\"sparse_categorical_crossentropy\", metrics=[\"accuracy\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 206,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/100\n",
      "36/36 [==============================] - 70s 2s/step - loss: 2.5159 - accuracy: 0.2309\n",
      "Epoch 2/100\n",
      "36/36 [==============================] - 69s 2s/step - loss: 2.0505 - accuracy: 0.3333\n",
      "Epoch 3/100\n",
      "36/36 [==============================] - 68s 2s/step - loss: 1.8162 - accuracy: 0.3958\n",
      "Epoch 4/100\n",
      "36/36 [==============================] - 68s 2s/step - loss: 1.7086 - accuracy: 0.4158\n",
      "Epoch 5/100\n",
      "36/36 [==============================] - 69s 2s/step - loss: 1.5923 - accuracy: 0.4688\n",
      "Epoch 6/100\n",
      "36/36 [==============================] - 69s 2s/step - loss: 1.5468 - accuracy: 0.4592\n",
      "Epoch 7/100\n",
      "36/36 [==============================] - 68s 2s/step - loss: 1.5436 - accuracy: 0.4861\n",
      "Epoch 8/100\n",
      "36/36 [==============================] - 74s 2s/step - loss: 1.3983 - accuracy: 0.5078\n",
      "Epoch 9/100\n",
      "36/36 [==============================] - 82s 2s/step - loss: 1.2994 - accuracy: 0.5130\n",
      "Epoch 10/100\n",
      "36/36 [==============================] - 75s 2s/step - loss: 1.1701 - accuracy: 0.5868\n",
      "Epoch 11/100\n",
      "36/36 [==============================] - 74s 2s/step - loss: 1.1168 - accuracy: 0.5955\n",
      "Epoch 12/100\n",
      "36/36 [==============================] - 73s 2s/step - loss: 1.0099 - accuracy: 0.6398\n",
      "Epoch 13/100\n",
      "36/36 [==============================] - 73s 2s/step - loss: 1.0552 - accuracy: 0.6172\n",
      "Epoch 14/100\n",
      "36/36 [==============================] - 71s 2s/step - loss: 0.9387 - accuracy: 0.6684\n",
      "Epoch 15/100\n",
      "36/36 [==============================] - 74s 2s/step - loss: 0.8948 - accuracy: 0.6988\n",
      "Epoch 16/100\n",
      "36/36 [==============================] - 71s 2s/step - loss: 0.8063 - accuracy: 0.7075\n",
      "Epoch 17/100\n",
      "36/36 [==============================] - 71s 2s/step - loss: 0.7242 - accuracy: 0.7500\n",
      "Epoch 18/100\n",
      "36/36 [==============================] - 73s 2s/step - loss: 0.6538 - accuracy: 0.7491\n",
      "Epoch 19/100\n",
      "36/36 [==============================] - 78s 2s/step - loss: 0.6380 - accuracy: 0.7717\n",
      "Epoch 20/100\n",
      "36/36 [==============================] - 80s 2s/step - loss: 0.5688 - accuracy: 0.7873\n",
      "Epoch 21/100\n",
      "36/36 [==============================] - 79s 2s/step - loss: 0.5524 - accuracy: 0.7960\n",
      "Epoch 22/100\n",
      "36/36 [==============================] - 78s 2s/step - loss: 0.5378 - accuracy: 0.7951\n",
      "Epoch 23/100\n",
      "36/36 [==============================] - 78s 2s/step - loss: 0.4884 - accuracy: 0.8264\n",
      "Epoch 24/100\n",
      "36/36 [==============================] - 74s 2s/step - loss: 0.4445 - accuracy: 0.8481\n",
      "Epoch 25/100\n",
      "36/36 [==============================] - 76s 2s/step - loss: 0.4893 - accuracy: 0.8316\n",
      "Epoch 26/100\n",
      "36/36 [==============================] - 82s 2s/step - loss: 0.3402 - accuracy: 0.8872\n",
      "Epoch 27/100\n",
      "36/36 [==============================] - 82s 2s/step - loss: 0.2716 - accuracy: 0.9002\n",
      "Epoch 28/100\n",
      "36/36 [==============================] - 76s 2s/step - loss: 0.2783 - accuracy: 0.8950\n",
      "Epoch 29/100\n",
      "36/36 [==============================] - 78s 2s/step - loss: 0.2590 - accuracy: 0.9106\n",
      "Epoch 30/100\n",
      "36/36 [==============================] - 78s 2s/step - loss: 0.2618 - accuracy: 0.9054\n",
      "Epoch 31/100\n",
      "36/36 [==============================] - 84s 2s/step - loss: 0.2579 - accuracy: 0.8967\n",
      "Epoch 32/100\n",
      "36/36 [==============================] - 78s 2s/step - loss: 0.1652 - accuracy: 0.9427\n",
      "Epoch 33/100\n",
      "36/36 [==============================] - 71s 2s/step - loss: 0.1667 - accuracy: 0.9401\n",
      "Epoch 34/100\n",
      "36/36 [==============================] - 82s 2s/step - loss: 0.2434 - accuracy: 0.9141\n",
      "Epoch 35/100\n",
      "36/36 [==============================] - 80s 2s/step - loss: 0.1930 - accuracy: 0.9349\n",
      "Epoch 36/100\n",
      "36/36 [==============================] - 79s 2s/step - loss: 0.1512 - accuracy: 0.9523\n",
      "Epoch 37/100\n",
      "36/36 [==============================] - 79s 2s/step - loss: 0.1500 - accuracy: 0.9557\n",
      "Epoch 38/100\n",
      "36/36 [==============================] - 79s 2s/step - loss: 0.1335 - accuracy: 0.9566\n",
      "Epoch 39/100\n",
      "36/36 [==============================] - 75s 2s/step - loss: 0.1370 - accuracy: 0.9618\n",
      "Epoch 40/100\n",
      "36/36 [==============================] - 77s 2s/step - loss: 0.1591 - accuracy: 0.9479\n",
      "Epoch 41/100\n",
      "36/36 [==============================] - 86s 2s/step - loss: 0.1284 - accuracy: 0.9592\n",
      "Epoch 42/100\n",
      "36/36 [==============================] - 78s 2s/step - loss: 0.1264 - accuracy: 0.9592\n",
      "Epoch 43/100\n",
      "36/36 [==============================] - 71s 2s/step - loss: 0.1182 - accuracy: 0.9549\n",
      "Epoch 44/100\n",
      "36/36 [==============================] - 72s 2s/step - loss: 0.1063 - accuracy: 0.9592\n",
      "Epoch 45/100\n",
      "36/36 [==============================] - 82s 2s/step - loss: 0.1171 - accuracy: 0.9531\n",
      "Epoch 46/100\n",
      "36/36 [==============================] - 73s 2s/step - loss: 0.1719 - accuracy: 0.9453\n",
      "Epoch 47/100\n",
      "36/36 [==============================] - 77s 2s/step - loss: 0.1363 - accuracy: 0.9531\n",
      "Epoch 48/100\n",
      "36/36 [==============================] - 76s 2s/step - loss: 0.1127 - accuracy: 0.9583\n",
      "Epoch 49/100\n",
      "36/36 [==============================] - 81s 2s/step - loss: 0.0999 - accuracy: 0.9627\n",
      "Epoch 50/100\n",
      "36/36 [==============================] - 75s 2s/step - loss: 0.0616 - accuracy: 0.9809\n",
      "Epoch 51/100\n",
      "36/36 [==============================] - 79s 2s/step - loss: 0.0725 - accuracy: 0.9748\n",
      "Epoch 52/100\n",
      "36/36 [==============================] - 81s 2s/step - loss: 0.1079 - accuracy: 0.9635\n",
      "Epoch 53/100\n",
      "36/36 [==============================] - 77s 2s/step - loss: 0.1246 - accuracy: 0.9557\n",
      "Epoch 54/100\n",
      "36/36 [==============================] - 72s 2s/step - loss: 0.1231 - accuracy: 0.9540\n",
      "Epoch 55/100\n",
      "36/36 [==============================] - 80s 2s/step - loss: 0.1362 - accuracy: 0.9566\n",
      "Epoch 56/100\n",
      "36/36 [==============================] - 73s 2s/step - loss: 0.1167 - accuracy: 0.9601\n",
      "Epoch 57/100\n",
      "36/36 [==============================] - 77s 2s/step - loss: 0.0596 - accuracy: 0.9800\n",
      "Epoch 58/100\n",
      "36/36 [==============================] - 71s 2s/step - loss: 0.0694 - accuracy: 0.9809\n",
      "Epoch 59/100\n",
      "36/36 [==============================] - 71s 2s/step - loss: 0.0612 - accuracy: 0.9826\n",
      "Epoch 60/100\n",
      "36/36 [==============================] - 71s 2s/step - loss: 0.0565 - accuracy: 0.9783\n",
      "Epoch 61/100\n",
      "36/36 [==============================] - 72s 2s/step - loss: 0.0817 - accuracy: 0.9714\n",
      "Epoch 62/100\n",
      "36/36 [==============================] - 74s 2s/step - loss: 0.0639 - accuracy: 0.9792\n",
      "Epoch 63/100\n",
      "36/36 [==============================] - 74s 2s/step - loss: 0.0844 - accuracy: 0.9653\n",
      "Epoch 64/100\n",
      "36/36 [==============================] - 75s 2s/step - loss: 0.1466 - accuracy: 0.9549\n",
      "Epoch 65/100\n",
      "36/36 [==============================] - 73s 2s/step - loss: 0.1402 - accuracy: 0.9635\n",
      "Epoch 66/100\n",
      "36/36 [==============================] - 73s 2s/step - loss: 0.1209 - accuracy: 0.9583\n",
      "Epoch 67/100\n",
      "36/36 [==============================] - 71s 2s/step - loss: 0.0899 - accuracy: 0.9688\n",
      "Epoch 68/100\n",
      "36/36 [==============================] - 72s 2s/step - loss: 0.0797 - accuracy: 0.9714\n",
      "Epoch 69/100\n",
      "36/36 [==============================] - 72s 2s/step - loss: 0.0674 - accuracy: 0.9766\n",
      "Epoch 70/100\n",
      "36/36 [==============================] - 71s 2s/step - loss: 0.0540 - accuracy: 0.9844\n",
      "Epoch 71/100\n",
      "36/36 [==============================] - 70s 2s/step - loss: 0.0570 - accuracy: 0.9809\n",
      "Epoch 72/100\n",
      "36/36 [==============================] - 69s 2s/step - loss: 0.0697 - accuracy: 0.9818\n",
      "Epoch 73/100\n",
      "36/36 [==============================] - 71s 2s/step - loss: 0.0797 - accuracy: 0.9748\n",
      "Epoch 74/100\n",
      "36/36 [==============================] - 73s 2s/step - loss: 0.1213 - accuracy: 0.9601\n",
      "Epoch 75/100\n",
      "36/36 [==============================] - 76s 2s/step - loss: 0.1400 - accuracy: 0.9488\n",
      "Epoch 76/100\n",
      "36/36 [==============================] - 71s 2s/step - loss: 0.1370 - accuracy: 0.9566\n",
      "Epoch 77/100\n",
      "36/36 [==============================] - 70s 2s/step - loss: 0.0908 - accuracy: 0.9696\n",
      "Epoch 78/100\n",
      "36/36 [==============================] - 71s 2s/step - loss: 0.0629 - accuracy: 0.9809\n",
      "Epoch 79/100\n",
      "36/36 [==============================] - 73s 2s/step - loss: 0.0488 - accuracy: 0.9852\n",
      "Epoch 80/100\n",
      "36/36 [==============================] - 71s 2s/step - loss: 0.0522 - accuracy: 0.9800\n",
      "Epoch 81/100\n",
      "36/36 [==============================] - 71s 2s/step - loss: 0.0568 - accuracy: 0.9792\n",
      "Epoch 82/100\n",
      "36/36 [==============================] - 71s 2s/step - loss: 0.0613 - accuracy: 0.9783\n",
      "Epoch 83/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "36/36 [==============================] - 70s 2s/step - loss: 0.0312 - accuracy: 0.9861\n",
      "Epoch 84/100\n",
      "36/36 [==============================] - 71s 2s/step - loss: 0.0485 - accuracy: 0.9826\n",
      "Epoch 85/100\n",
      "36/36 [==============================] - 73s 2s/step - loss: 0.0587 - accuracy: 0.9835\n",
      "Epoch 86/100\n",
      "36/36 [==============================] - 71s 2s/step - loss: 0.0595 - accuracy: 0.9826\n",
      "Epoch 87/100\n",
      "36/36 [==============================] - 67s 2s/step - loss: 0.0496 - accuracy: 0.9835\n",
      "Epoch 88/100\n",
      "36/36 [==============================] - 65s 2s/step - loss: 0.0583 - accuracy: 0.9774\n",
      "Epoch 89/100\n",
      "36/36 [==============================] - 66s 2s/step - loss: 0.0548 - accuracy: 0.9800\n",
      "Epoch 90/100\n",
      "36/36 [==============================] - 66s 2s/step - loss: 0.0457 - accuracy: 0.9878\n",
      "Epoch 91/100\n",
      "36/36 [==============================] - 62s 2s/step - loss: 0.0240 - accuracy: 0.9939\n",
      "Epoch 92/100\n",
      "36/36 [==============================] - 61s 2s/step - loss: 0.0150 - accuracy: 0.9939\n",
      "Epoch 93/100\n",
      "36/36 [==============================] - 62s 2s/step - loss: 0.0282 - accuracy: 0.9922\n",
      "Epoch 94/100\n",
      "36/36 [==============================] - 63s 2s/step - loss: 0.0212 - accuracy: 0.9922\n",
      "Epoch 95/100\n",
      "36/36 [==============================] - 62s 2s/step - loss: 0.0863 - accuracy: 0.9722\n",
      "Epoch 96/100\n",
      "36/36 [==============================] - 62s 2s/step - loss: 0.0516 - accuracy: 0.9809\n",
      "Epoch 97/100\n",
      "36/36 [==============================] - 62s 2s/step - loss: 0.0475 - accuracy: 0.9783\n",
      "Epoch 98/100\n",
      "36/36 [==============================] - 61s 2s/step - loss: 0.0707 - accuracy: 0.9757\n",
      "Epoch 99/100\n",
      "36/36 [==============================] - 62s 2s/step - loss: 0.0593 - accuracy: 0.9783\n",
      "Epoch 100/100\n",
      "36/36 [==============================] - 62s 2s/step - loss: 0.0641 - accuracy: 0.9774\n",
      "Wall time: 2h 5min 3s\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<tensorflow.python.keras.callbacks.History at 0x23126b1c6d0>"
      ]
     },
     "execution_count": 206,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "model.fit(x_train, y_train, epochs=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 207,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test loss: 3.9927990436553955\n",
      "Test accuracy: 0.5416666865348816\n"
     ]
    }
   ],
   "source": [
    "score = model.evaluate(x_test, y_test, verbose=0)\n",
    "print('Test loss:', score[0])\n",
    "print('Test accuracy:', score[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From <ipython-input-208-1e588765245b>:1: Sequential.predict_classes (from tensorflow.python.keras.engine.sequential) is deprecated and will be removed after 2021-01-01.\n",
      "Instructions for updating:\n",
      "Please use instead:* `np.argmax(model.predict(x), axis=-1)`,   if your model does multi-class classification   (e.g. if it uses a `softmax` last-layer activation).* `(model.predict(x) > 0.5).astype(\"int32\")`,   if your model does binary classification   (e.g. if it uses a `sigmoid` last-layer activation).\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([7, 7, 5, 7, 1, 4, 1, 1, 7, 1, 7, 6, 7, 4, 7, 1, 6, 4, 7, 2, 4, 2,\n",
       "       4, 2, 0, 0, 3, 5, 5, 0, 3, 7, 6, 4, 4, 1, 2, 3, 7, 2, 2, 4, 6, 3,\n",
       "       7, 1, 4, 3, 4, 6, 2, 0, 7, 6, 6, 1, 5, 7, 3, 1, 0, 1, 1, 0, 7, 4,\n",
       "       3, 2, 6, 7, 6, 3, 6, 0, 6, 7, 6, 3, 1, 4, 7, 0, 7, 7, 0, 7, 1, 7,\n",
       "       5, 3, 6, 1, 2, 2, 0, 7, 3, 7, 6, 2, 1, 1, 0, 6, 3, 2, 6, 7, 7, 3,\n",
       "       4, 3, 0, 6, 5, 1, 6, 7, 0, 3, 5, 0, 7, 3, 3, 2, 3, 2, 1, 2, 2, 5,\n",
       "       4, 7, 2, 1, 4, 0, 4, 0, 4, 1, 3, 5, 4, 7, 5, 5, 7, 4, 5, 3, 1, 7,\n",
       "       1, 4, 7, 5, 0, 3, 6, 7, 3, 7, 6, 2, 7, 7, 2, 2, 1, 1, 5, 1, 6, 3,\n",
       "       0, 6, 0, 2, 7, 4, 2, 7, 0, 6, 7, 0, 3, 2, 0, 7, 3, 3, 1, 0, 0, 1,\n",
       "       1, 3, 7, 4, 3, 2, 5, 5, 1, 0, 6, 5, 0, 0, 7, 3, 4, 0, 1, 3, 4, 2,\n",
       "       6, 7, 1, 0, 1, 4, 0, 6, 0, 6, 0, 4, 2, 0, 0, 3, 0, 7, 0, 3, 1, 6,\n",
       "       3, 7, 3, 4, 3, 6, 0, 3, 1, 1, 4, 4, 0, 0, 2, 7, 0, 6, 0, 7, 6, 7,\n",
       "       6, 4, 0, 0, 2, 0, 2, 3, 3, 6, 1, 1, 4, 2, 1, 0, 4, 2, 4, 1, 6, 4,\n",
       "       0, 1])"
      ]
     },
     "execution_count": 208,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predictions = model.predict_classes(x_test)\n",
    "predictions\n",
    "y_test\n",
    "new_Ytest = y_test.astype(int)\n",
    "new_Ytest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.71      0.70      0.70        46\n",
      "           1       0.38      0.97      0.54        40\n",
      "           2       0.57      0.87      0.69        31\n",
      "           3       0.66      0.50      0.57        38\n",
      "           4       0.69      0.53      0.60        34\n",
      "           5       0.32      0.35      0.33        17\n",
      "           6       0.50      0.09      0.15        34\n",
      "           7       1.00      0.25      0.40        48\n",
      "\n",
      "    accuracy                           0.54       288\n",
      "   macro avg       0.60      0.53      0.50       288\n",
      "weighted avg       0.64      0.54      0.51       288\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import classification_report\n",
    "report = classification_report(new_Ytest, predictions)\n",
    "print(report)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 210,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[32  5  3  1  4  1  0  0]\n",
      " [ 0 39  1  0  0  0  0  0]\n",
      " [ 2  1 27  0  0  0  1  0]\n",
      " [ 1 12  4 19  1  1  0  0]\n",
      " [ 1  6  2  4 18  2  1  0]\n",
      " [ 0 10  0  0  0  6  1  0]\n",
      " [ 3 19  5  2  1  1  3  0]\n",
      " [ 6 12  5  3  2  8  0 12]]\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import confusion_matrix\n",
    "matrix = confusion_matrix(new_Ytest, predictions)\n",
    "print (matrix)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1368x720 with 9 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pred = model.predict(x_test)\n",
    "plt.figure(1 , figsize = (19 , 10))\n",
    "n = 0 \n",
    "\n",
    "for i in range(9):\n",
    "    n += 1 \n",
    "    r = np.random.randint( 0, x_test.shape[0], 1)\n",
    "    \n",
    "    plt.subplot(3, 3, n)\n",
    "    plt.subplots_adjust(hspace = 0.3, wspace = 0.3)\n",
    "    \n",
    "    plt.imshow(x_test[r[0]])\n",
    "    plt.title('Actual = {}, Predicted = {}'.format(y_test[r[0]] , y_test[r[0]]*pred[r[0]][y_test[r[0]]]) )\n",
    "    plt.xticks([]) , plt.yticks([])\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras.layers import Dense, Flatten, Reshape, Input, InputLayer\n",
    "from keras.models import Sequential, Model\n",
    "\n",
    "def build_autoencoder(img_shape, code_size):\n",
    "    # The encoder\n",
    "    encoder = Sequential()\n",
    "    encoder.add(InputLayer(img_shape))\n",
    "    encoder.add(Flatten())\n",
    "    encoder.add(Dense(code_size))\n",
    "\n",
    "    # The decoder\n",
    "    decoder = Sequential()\n",
    "    decoder.add(InputLayer((code_size,)))\n",
    "    decoder.add(Dense(np.prod(img_shape))) # np.prod(img_shape) is the same as 32*32*3, it's more generic than saying 3072\n",
    "    decoder.add(Reshape(img_shape))\n",
    "\n",
    "    return encoder, decoder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"functional_1\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "input_3 (InputLayer)         [(None, 227, 227, 3)]     0         \n",
      "_________________________________________________________________\n",
      "sequential_1 (Sequential)    (None, 32)                4946816   \n",
      "_________________________________________________________________\n",
      "sequential_2 (Sequential)    (None, 227, 227, 3)       5101371   \n",
      "=================================================================\n",
      "Total params: 10,048,187\n",
      "Trainable params: 10,048,187\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "IMG_SHAPE = images.shape[1:]\n",
    "encoder, decoder = build_autoencoder(IMG_SHAPE, 32)\n",
    "\n",
    "inp = Input(IMG_SHAPE)\n",
    "code = encoder(inp)\n",
    "reconstruction = decoder(code)\n",
    "\n",
    "autoencoder = Model(inp,reconstruction)\n",
    "autoencoder.compile(optimizer='adamax', loss='mse')\n",
    "\n",
    "print(autoencoder.summary())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/20\n",
      "36/36 [==============================] - 5s 153ms/step - loss: 0.0704 - val_loss: 0.0000e+00\n",
      "Epoch 2/20\n",
      "36/36 [==============================] - 5s 151ms/step - loss: 0.0181 - val_loss: 0.0000e+00\n",
      "Epoch 3/20\n",
      "36/36 [==============================] - 5s 151ms/step - loss: 0.0172 - val_loss: 0.0000e+00\n",
      "Epoch 4/20\n",
      "36/36 [==============================] - 5s 151ms/step - loss: 0.0170 - val_loss: 0.0000e+00\n",
      "Epoch 5/20\n",
      "36/36 [==============================] - 5s 150ms/step - loss: 0.0167 - val_loss: 0.0000e+00\n",
      "Epoch 6/20\n",
      "36/36 [==============================] - 5s 151ms/step - loss: 0.0164 - val_loss: 0.0000e+00\n",
      "Epoch 7/20\n",
      "36/36 [==============================] - 5s 151ms/step - loss: 0.0160 - val_loss: 0.0000e+00\n",
      "Epoch 8/20\n",
      "36/36 [==============================] - 5s 151ms/step - loss: 0.0156 - val_loss: 0.0000e+00\n",
      "Epoch 9/20\n",
      "36/36 [==============================] - 5s 148ms/step - loss: 0.0153 - val_loss: 0.0000e+00\n",
      "Epoch 10/20\n",
      "36/36 [==============================] - 5s 149ms/step - loss: 0.0150 - val_loss: 0.0000e+00\n",
      "Epoch 11/20\n",
      "36/36 [==============================] - 5s 148ms/step - loss: 0.0148 - val_loss: 0.0000e+00\n",
      "Epoch 12/20\n",
      "36/36 [==============================] - 5s 151ms/step - loss: 0.0146 - val_loss: 0.0000e+00\n",
      "Epoch 13/20\n",
      "36/36 [==============================] - 5s 148ms/step - loss: 0.0144 - val_loss: 0.0000e+00\n",
      "Epoch 14/20\n",
      "36/36 [==============================] - 5s 148ms/step - loss: 0.0143 - val_loss: 0.0000e+00\n",
      "Epoch 15/20\n",
      "36/36 [==============================] - 5s 150ms/step - loss: 0.0141 - val_loss: 0.0000e+00\n",
      "Epoch 16/20\n",
      "36/36 [==============================] - 6s 154ms/step - loss: 0.0140 - val_loss: 0.0000e+00\n",
      "Epoch 17/20\n",
      "36/36 [==============================] - 5s 149ms/step - loss: 0.0138 - val_loss: 0.0000e+00\n",
      "Epoch 18/20\n",
      "36/36 [==============================] - 5s 150ms/step - loss: 0.0137 - val_loss: 0.0000e+00\n",
      "Epoch 19/20\n",
      "36/36 [==============================] - 5s 146ms/step - loss: 0.0135 - val_loss: 0.0000e+00\n",
      "Epoch 20/20\n",
      "36/36 [==============================] - 5s 142ms/step - loss: 0.0134 - val_loss: 0.0000e+00\n"
     ]
    }
   ],
   "source": [
    "history = autoencoder.fit(x=x_train, y=x_train, epochs=20,\n",
    "                validation_data=[x_test, x_test])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy= 0.9269862994551659 \n",
      "\n"
     ]
    }
   ],
   "source": [
    "decoded_imgs = autoencoder.predict(images)\n",
    "\n",
    "n = 1\n",
    "plt.figure(figsize=(20, 4))\n",
    "for i in range(n):\n",
    "    # display original\n",
    "    ax = plt.subplot(2, n, i+1)\n",
    "    plt.imshow(x_test[i].reshape(227, 227,3))\n",
    "    plt.gray()\n",
    "    ax.get_xaxis().set_visible(False)\n",
    "    ax.get_yaxis().set_visible(False)\n",
    "\n",
    "    # display reconstruction\n",
    "    ax = plt.subplot(2, n, i + n+1)\n",
    "    plt.imshow(decoded_imgs[i].reshape(227, 227,3))\n",
    "    plt.gray()\n",
    "    ax.get_xaxis().set_visible(False)\n",
    "    ax.get_yaxis().set_visible(False)\n",
    "plt.show()\n",
    "\n",
    "print(\"Accuracy=\",1-np.mean(abs(images-decoded_imgs)),'\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy= 0.9267575740814209 \n",
      "\n"
     ]
    }
   ],
   "source": [
    "decoded_imgs = autoencoder.predict(images)\n",
    "n = 1\n",
    "plt.figure(figsize=(20, 4))\n",
    "for i in range(n):\n",
    "    # display original\n",
    "    ax = plt.subplot(2, n, i+1)\n",
    "    plt.imshow(images[i].reshape(227, 227,3))\n",
    "    plt.gray()\n",
    "    ax.get_xaxis().set_visible(False)\n",
    "    ax.get_yaxis().set_visible(False)\n",
    "\n",
    "    # display reconstruction\n",
    "    ax = plt.subplot(2, n, i + n+1)\n",
    "    plt.imshow(decoded_imgs[i].reshape(227, 227,3))\n",
    "    plt.gray()\n",
    "    ax.get_xaxis().set_visible(False)\n",
    "    ax.get_yaxis().set_visible(False)\n",
    "plt.show()\n",
    "\n",
    "print(\"Accuracy=\",1-np.mean(abs(images-decoded_imgs)),'\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x_train shape =  (1152, 227, 227, 3)\n",
      "y_train shape =  (1152,)\n",
      "\n",
      "x_test shape =  (288, 227, 227, 3)\n",
      "y_test shape =  (288,)\n"
     ]
    }
   ],
   "source": [
    "X_train, X_test, Y_train, Y_test = train_test_split(decoded_imgs, labels, test_size = 0.2, random_state = random_seed)\n",
    "\n",
    "print(\"x_train shape = \",X_train.shape)\n",
    "print(\"y_train shape = \",Y_train.shape)\n",
    "print(\"\\nx_test shape = \",X_test.shape)\n",
    "print(\"y_test shape = \",Y_test.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/300\n",
      "36/36 [==============================] - 61s 2s/step - loss: 1.9043 - accuracy: 0.3038\n",
      "Epoch 2/300\n",
      "36/36 [==============================] - 62s 2s/step - loss: 1.9047 - accuracy: 0.3082\n",
      "Epoch 3/300\n",
      "36/36 [==============================] - 62s 2s/step - loss: 1.8784 - accuracy: 0.3151\n",
      "Epoch 4/300\n",
      "36/36 [==============================] - 62s 2s/step - loss: 1.8554 - accuracy: 0.3273\n",
      "Epoch 5/300\n",
      "36/36 [==============================] - 60s 2s/step - loss: 1.8870 - accuracy: 0.2995\n",
      "Epoch 6/300\n",
      "36/36 [==============================] - 71s 2s/step - loss: 1.8368 - accuracy: 0.3108\n",
      "Epoch 7/300\n",
      "36/36 [==============================] - 62s 2s/step - loss: 1.8226 - accuracy: 0.3368\n",
      "Epoch 8/300\n",
      "36/36 [==============================] - 62s 2s/step - loss: 1.8202 - accuracy: 0.3255\n",
      "Epoch 9/300\n",
      "36/36 [==============================] - 62s 2s/step - loss: 1.7897 - accuracy: 0.3464\n",
      "Epoch 10/300\n",
      "36/36 [==============================] - 62s 2s/step - loss: 1.8026 - accuracy: 0.3377\n",
      "Epoch 11/300\n",
      "36/36 [==============================] - 62s 2s/step - loss: 1.7740 - accuracy: 0.3377\n",
      "Epoch 12/300\n",
      "36/36 [==============================] - 62s 2s/step - loss: 1.7323 - accuracy: 0.3481\n",
      "Epoch 13/300\n",
      "36/36 [==============================] - 62s 2s/step - loss: 1.7421 - accuracy: 0.3516\n",
      "Epoch 14/300\n",
      "36/36 [==============================] - 62s 2s/step - loss: 1.7286 - accuracy: 0.3472\n",
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    },
    {
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     "output_type": "stream",
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      "36/36 [==============================] - 54s 1s/step - loss: 0.9759 - accuracy: 0.6276\n",
      "Epoch 192/300\n",
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      "Epoch 193/300\n",
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      "Epoch 194/300\n",
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      "Epoch 195/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.8787 - accuracy: 0.6571\n",
      "Epoch 196/300\n",
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      "Epoch 197/300\n",
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      "Epoch 198/300\n",
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      "Epoch 199/300\n",
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      "Epoch 200/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 1.0830 - accuracy: 0.5998\n",
      "Epoch 201/300\n",
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      "Epoch 202/300\n",
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      "Epoch 203/300\n",
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      "Epoch 210/300\n",
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      "Epoch 219/300\n",
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      "Epoch 220/300\n",
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      "Epoch 221/300\n",
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      "Epoch 224/300\n",
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      "Epoch 225/300\n",
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      "Epoch 226/300\n",
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      "Epoch 227/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.7789 - accuracy: 0.7214\n",
      "Epoch 228/300\n",
      "36/36 [==============================] - 54s 2s/step - loss: 0.8857 - accuracy: 0.6632\n",
      "Epoch 229/300\n",
      "36/36 [==============================] - 56s 2s/step - loss: 0.7964 - accuracy: 0.7092\n",
      "Epoch 230/300\n",
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      "Epoch 231/300\n",
      "36/36 [==============================] - 56s 2s/step - loss: 0.7475 - accuracy: 0.7075\n",
      "Epoch 232/300\n",
      "36/36 [==============================] - 56s 2s/step - loss: 0.7866 - accuracy: 0.6988\n",
      "Epoch 233/300\n",
      "36/36 [==============================] - 55s 2s/step - loss: 0.7494 - accuracy: 0.7300\n",
      "Epoch 234/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.6739 - accuracy: 0.7448\n",
      "Epoch 235/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.7267 - accuracy: 0.7378\n",
      "Epoch 236/300\n",
      "36/36 [==============================] - 52s 1s/step - loss: 0.8048 - accuracy: 0.6936\n",
      "Epoch 237/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.8122 - accuracy: 0.7031\n",
      "Epoch 238/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.7158 - accuracy: 0.7361\n",
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      "Epoch 240/300\n",
      "36/36 [==============================] - 53s 1s/step - loss: 0.7361 - accuracy: 0.7170\n",
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      "Epoch 242/300\n",
      "36/36 [==============================] - 55s 2s/step - loss: 0.7789 - accuracy: 0.7092\n",
      "Epoch 243/300\n",
      "36/36 [==============================] - 55s 2s/step - loss: 0.6627 - accuracy: 0.7535\n",
      "Epoch 244/300\n",
      "36/36 [==============================] - 56s 2s/step - loss: 0.8480 - accuracy: 0.6840\n",
      "Epoch 245/300\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "36/36 [==============================] - 54s 2s/step - loss: 0.6815 - accuracy: 0.7543\n",
      "Epoch 246/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.6791 - accuracy: 0.7387\n",
      "Epoch 247/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.6428 - accuracy: 0.7500\n",
      "Epoch 248/300\n",
      "36/36 [==============================] - 53s 1s/step - loss: 0.6664 - accuracy: 0.7526\n",
      "Epoch 249/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.6944 - accuracy: 0.7387\n",
      "Epoch 250/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.7087 - accuracy: 0.7344\n",
      "Epoch 251/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.6790 - accuracy: 0.7370\n",
      "Epoch 252/300\n",
      "36/36 [==============================] - 53s 1s/step - loss: 0.7077 - accuracy: 0.7378\n",
      "Epoch 253/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.8419 - accuracy: 0.6970\n",
      "Epoch 254/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.8701 - accuracy: 0.6866\n",
      "Epoch 255/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.7892 - accuracy: 0.7014\n",
      "Epoch 256/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.7340 - accuracy: 0.7127\n",
      "Epoch 257/300\n",
      "36/36 [==============================] - 53s 1s/step - loss: 0.7130 - accuracy: 0.7248\n",
      "Epoch 258/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.7007 - accuracy: 0.7344\n",
      "Epoch 259/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.7529 - accuracy: 0.7361\n",
      "Epoch 260/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.6897 - accuracy: 0.7491\n",
      "Epoch 261/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.7848 - accuracy: 0.7205\n",
      "Epoch 262/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.7215 - accuracy: 0.7248\n",
      "Epoch 263/300\n",
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      "Epoch 264/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.6198 - accuracy: 0.7526\n",
      "Epoch 265/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.7239 - accuracy: 0.7274\n",
      "Epoch 266/300\n",
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      "Epoch 268/300\n",
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      "Epoch 269/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.7232 - accuracy: 0.7300\n",
      "Epoch 270/300\n",
      "36/36 [==============================] - 55s 2s/step - loss: 1.0318 - accuracy: 0.6580\n",
      "Epoch 271/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.9934 - accuracy: 0.6267\n",
      "Epoch 272/300\n",
      "36/36 [==============================] - 53s 1s/step - loss: 1.3862 - accuracy: 0.5191\n",
      "Epoch 273/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 1.1113 - accuracy: 0.5929\n",
      "Epoch 274/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.9767 - accuracy: 0.6441\n",
      "Epoch 275/300\n",
      "36/36 [==============================] - 55s 2s/step - loss: 0.9477 - accuracy: 0.6389\n",
      "Epoch 276/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.8204 - accuracy: 0.6858\n",
      "Epoch 277/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.8411 - accuracy: 0.6797\n",
      "Epoch 278/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.6804 - accuracy: 0.7448\n",
      "Epoch 279/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.7245 - accuracy: 0.7318\n",
      "Epoch 280/300\n",
      "36/36 [==============================] - 53s 1s/step - loss: 0.7092 - accuracy: 0.7405\n",
      "Epoch 281/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.7297 - accuracy: 0.7144\n",
      "Epoch 282/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.6931 - accuracy: 0.7483\n",
      "Epoch 283/300\n",
      "36/36 [==============================] - 54s 2s/step - loss: 0.7659 - accuracy: 0.7161\n",
      "Epoch 284/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.7655 - accuracy: 0.7092\n",
      "Epoch 285/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.7101 - accuracy: 0.7274\n",
      "Epoch 286/300\n",
      "36/36 [==============================] - 53s 1s/step - loss: 0.6548 - accuracy: 0.7352\n",
      "Epoch 287/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.7046 - accuracy: 0.7248\n",
      "Epoch 288/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.7246 - accuracy: 0.7266\n",
      "Epoch 289/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.7146 - accuracy: 0.7370\n",
      "Epoch 290/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.7107 - accuracy: 0.7309\n",
      "Epoch 291/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.7458 - accuracy: 0.7257\n",
      "Epoch 292/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.6219 - accuracy: 0.7578\n",
      "Epoch 293/300\n",
      "36/36 [==============================] - 54s 2s/step - loss: 0.5820 - accuracy: 0.7839\n",
      "Epoch 294/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.6004 - accuracy: 0.7717\n",
      "Epoch 295/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.6264 - accuracy: 0.7691\n",
      "Epoch 296/300\n",
      "36/36 [==============================] - 53s 1s/step - loss: 0.7338 - accuracy: 0.7144\n",
      "Epoch 297/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.7327 - accuracy: 0.7266\n",
      "Epoch 298/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.8085 - accuracy: 0.7109\n",
      "Epoch 299/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 0.8274 - accuracy: 0.6884\n",
      "Epoch 300/300\n",
      "36/36 [==============================] - 54s 1s/step - loss: 1.1011 - accuracy: 0.6354\n",
      "Wall time: 4h 47min 15s\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<tensorflow.python.keras.callbacks.History at 0x11ed553dcd0>"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "model.fit(X_train, Y_train, epochs=300, batch_size=32)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test loss: 673.41796875\n",
      "Test accuracy: 0.2118055522441864\n"
     ]
    }
   ],
   "source": [
    "score = model.evaluate(X_test, Y_test, verbose=0)\n",
    "print('Test loss:', score[0])\n",
    "print('Test accuracy:', score[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 1, 0, 1, 0, 4, 3, 1, 1, 6, 7, 4, 2, 3, 3, 5, 2, 3, 7, 4, 3, 7,\n",
       "       0, 1, 4, 7, 7, 5, 3, 2, 0, 4, 4, 2, 1, 0, 1, 3, 1, 1, 0, 5, 2, 3,\n",
       "       2, 0, 0, 3, 6, 2, 3, 5, 1, 7, 1, 2, 6, 4, 2, 0, 1, 6, 2, 2, 4, 7,\n",
       "       7, 4, 6, 4, 7, 0, 6, 6, 7, 3, 0, 6, 0, 1, 3, 3, 7, 7, 3, 3, 4, 4,\n",
       "       7, 2, 0, 0, 0, 2, 6, 5, 3, 2, 4, 7, 0, 1, 1, 1, 6, 4, 0, 4, 7, 0,\n",
       "       4, 0, 4, 0, 1, 6, 4, 1, 0, 6, 1, 1, 7, 1, 3, 7, 2, 2, 6, 6, 1, 2,\n",
       "       2, 2, 2, 5, 4, 0, 1, 6, 0, 7, 1, 1, 5, 5, 3, 7, 6, 6, 2, 2, 6, 4,\n",
       "       6, 5, 7, 2, 3, 1, 3, 1, 6, 5, 3, 1, 0, 4, 7, 5, 0, 6, 4, 2, 2, 2,\n",
       "       4, 2, 6, 1, 1, 6, 4, 7, 7, 2, 1, 6, 7, 2, 7, 0, 2, 1, 5, 3, 4, 5,\n",
       "       4, 7, 3, 6, 0, 2, 7, 0, 7, 3, 1, 4, 0, 6, 2, 4, 4, 1, 4, 3, 3, 5,\n",
       "       1, 3, 7, 3, 3, 2, 3, 3, 2, 5, 1, 5, 1, 3, 0, 2, 6, 0, 3, 4, 3, 3,\n",
       "       1, 4, 1, 7, 2, 0, 7, 0, 0, 3, 0, 7, 2, 4, 0, 0, 6, 5, 3, 5, 6, 2,\n",
       "       6, 6, 0, 7, 3, 7, 0, 7, 5, 6, 3, 3, 7, 6, 7, 4, 6, 4, 1, 0, 1, 0,\n",
       "       1, 6])"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predictions_new = model.predict_classes(X_test)\n",
    "predictions_new\n",
    "y_test\n",
    "new_Ytest_new = y_test.astype(int)\n",
    "new_Ytest_new"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.00      0.00      0.00        41\n",
      "           1       0.17      0.95      0.29        43\n",
      "           2       0.00      0.00      0.00        38\n",
      "           3       0.11      0.10      0.11        40\n",
      "           4       0.50      0.03      0.05        35\n",
      "           5       0.00      0.00      0.00        19\n",
      "           6       0.12      0.03      0.05        35\n",
      "           7       0.50      0.03      0.05        37\n",
      "\n",
      "    accuracy                           0.17       288\n",
      "   macro avg       0.18      0.14      0.07       288\n",
      "weighted avg       0.18      0.17      0.08       288\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\users\\shireen\\lib\\site-packages\\sklearn\\metrics\\_classification.py:1221: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import classification_report\n",
    "report = classification_report(new_Ytest_new, predictions_new)\n",
    "print(report)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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