ButterflyClassification.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "cOU1hF10xTSR",
    "outputId": "17f9d647-2dba-42df-c159-69451bc500a5"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--2021-01-19 11:31:53--  http://www.josiahwang.com/dataset/leedsbutterfly/leedsbutterfly_dataset_v1.0.zip\n",
      "Resolving www.josiahwang.com (www.josiahwang.com)... 143.95.240.28\n",
      "Connecting to www.josiahwang.com (www.josiahwang.com)|143.95.240.28|:80... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 476389461 (454M) [application/zip]\n",
      "Saving to: ‘leedsbutterfly_dataset_v1.0.zip’\n",
      "\n",
      "leedsbutterfly_data 100%[===================>] 454.32M  69.7MB/s    in 6.7s    \n",
      "\n",
      "2021-01-19 11:32:00 (67.4 MB/s) - ‘leedsbutterfly_dataset_v1.0.zip’ saved [476389461/476389461]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "!wget http://www.josiahwang.com/dataset/leedsbutterfly/leedsbutterfly_dataset_v1.0.zip"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "xGU1JVVhxm_i",
    "outputId": "0fc4e4c1-4e24-419e-d1e5-ba302ae64644"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Archive:  leedsbutterfly_dataset_v1.0.zip\n",
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     ]
    }
   ],
   "source": [
    "!unzip leedsbutterfly_dataset_v1.0.zip"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "id": "MiwnCkhIY5du"
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from tensorflow.keras.utils import to_categorical\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from sklearn.model_selection import train_test_split\n",
    "from tensorflow.keras.preprocessing.image import ImageDataGenerator\n",
    "from sklearn.preprocessing import OneHotEncoder\n",
    "from tensorflow.keras.applications import Xception\n",
    "from tensorflow.keras.layers import AveragePooling2D\n",
    "from tensorflow.keras.layers import Dropout\n",
    "from tensorflow.keras.layers import Flatten\n",
    "from tensorflow.keras.layers import Dense\n",
    "from tensorflow.keras.optimizers import Adam\n",
    "from tensorflow.keras.layers import Input\n",
    "from tensorflow.keras.models import Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "Eye_oZcMY8jd",
    "outputId": "a46ac28d-7ef4-41e9-c119-3c4820831cb2"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['007', '005', '001']\n"
     ]
    }
   ],
   "source": [
    "categories = []\n",
    "filenames = os.listdir(\"/content/leedsbutterfly/images\")\n",
    "for filename in filenames:\n",
    "        category = filename.split(\".\")[0]\n",
    "        categories.append(category[0:3])\n",
    "        \n",
    "print(categories[0:3])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 204
    },
    "id": "ADqMDCKfZDp4",
    "outputId": "2a0a3275-3502-4c81-de0c-0e3874f03ab4"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Image</th>\n",
       "      <th>Category</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0070007.png</td>\n",
       "      <td>007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0050090.png</td>\n",
       "      <td>005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0010037.png</td>\n",
       "      <td>001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0100025.png</td>\n",
       "      <td>010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0040159.png</td>\n",
       "      <td>004</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Image Category\n",
       "0  0070007.png      007\n",
       "1  0050090.png      005\n",
       "2  0010037.png      001\n",
       "3  0100025.png      010\n",
       "4  0040159.png      004"
      ]
     },
     "execution_count": 33,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame()\n",
    "df['Image'] = filenames\n",
    "df['Category'] = categories    \n",
    "\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "df9bKYCgZNG0",
    "outputId": "ea0066bc-1aa5-489c-a73a-9980788cd2ef"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "006    100\n",
       "002     93\n",
       "009     90\n",
       "004     90\n",
       "007     89\n",
       "005     88\n",
       "010     84\n",
       "001     82\n",
       "003     61\n",
       "008     55\n",
       "Name: Category, dtype: int64"
      ]
     },
     "execution_count": 34,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Category'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "id": "F7yC_xrJZWcl"
   },
   "outputs": [],
   "source": [
    "import cv2\n",
    "data=[]\n",
    "labels=[]\n",
    "filenames = os.listdir(\"/content/leedsbutterfly/images\")\n",
    "for filename in filenames:\n",
    "    label = int(str(filename)[:3])\n",
    "    image = cv2.imread('/content/leedsbutterfly/images/'+filename)\n",
    "    image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)\n",
    "    image = cv2.resize(image, (224, 224))\n",
    "    data.append(image)\n",
    "    labels.append(label)\n",
    "data = np.array(data) /255"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "fcu2BPmfZcws",
    "outputId": "e92be54d-ef99-40f8-916b-baf7ce1c0040"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(832, 224, 224, 3)"
      ]
     },
     "execution_count": 36,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "id": "8iQCJllSZfo2"
   },
   "outputs": [],
   "source": [
    "labels = np.array(labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "id": "cUBZW41ZZj2A"
   },
   "outputs": [],
   "source": [
    "labels = labels.reshape(len(labels),1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "FVut34eGZof_",
    "outputId": "7534f886-45b8-4408-fc8b-8767ccdfc0b7"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(832, 1)"
      ]
     },
     "execution_count": 39,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "labels.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "id": "Q_TdlnKNZpyf"
   },
   "outputs": [],
   "source": [
    "labels = OneHotEncoder().fit_transform(np.asarray(labels).reshape(len(labels),1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "id": "WCmqd9Z-Zr4v"
   },
   "outputs": [],
   "source": [
    "(trainX, testX, trainY, testY) = train_test_split(data, labels,test_size=0.2, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "id": "AlwhxNTnZt1p"
   },
   "outputs": [],
   "source": [
    "trainAug = ImageDataGenerator(rotation_range=15,fill_mode=\"nearest\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "GVWrBzPXZyhx",
    "outputId": "0f0e26f5-ba99-4cb0-f31a-6aba779a454d"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading data from https://storage.googleapis.com/tensorflow/keras-applications/xception/xception_weights_tf_dim_ordering_tf_kernels_notop.h5\n",
      "83689472/83683744 [==============================] - 0s 0us/step\n"
     ]
    }
   ],
   "source": [
    "baseModel = Xception(weights=\"imagenet\", include_top=False,input_tensor=Input(shape=(224, 224, 3)))\n",
    "headModel = baseModel.output\n",
    "headModel = AveragePooling2D(pool_size=(4, 4))(headModel)\n",
    "headModel = Flatten(name=\"flatten\")(headModel)\n",
    "headModel = Dense(64, activation=\"relu\")(headModel)\n",
    "headModel = Dropout(0.5)(headModel)\n",
    "headModel = Dense(10, activation=\"softmax\")(headModel)\n",
    "model = Model(inputs=baseModel.input, outputs=headModel)\n",
    "for layer in baseModel.layers:\n",
    "    layer.trainable = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "dyHBrhIpaGlM",
    "outputId": "9630fc8d-9ba0-46eb-aace-9be60ae35cf0"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"model_1\"\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_2 (InputLayer)            [(None, 224, 224, 3) 0                                            \n",
      "__________________________________________________________________________________________________\n",
      "block1_conv1 (Conv2D)           (None, 111, 111, 32) 864         input_2[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "block1_conv1_bn (BatchNormaliza (None, 111, 111, 32) 128         block1_conv1[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "block1_conv1_act (Activation)   (None, 111, 111, 32) 0           block1_conv1_bn[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block1_conv2 (Conv2D)           (None, 109, 109, 64) 18432       block1_conv1_act[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "block1_conv2_bn (BatchNormaliza (None, 109, 109, 64) 256         block1_conv2[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "block1_conv2_act (Activation)   (None, 109, 109, 64) 0           block1_conv2_bn[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block2_sepconv1 (SeparableConv2 (None, 109, 109, 128 8768        block1_conv2_act[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "block2_sepconv1_bn (BatchNormal (None, 109, 109, 128 512         block2_sepconv1[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block2_sepconv2_act (Activation (None, 109, 109, 128 0           block2_sepconv1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "block2_sepconv2 (SeparableConv2 (None, 109, 109, 128 17536       block2_sepconv2_act[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "block2_sepconv2_bn (BatchNormal (None, 109, 109, 128 512         block2_sepconv2[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "conv2d (Conv2D)                 (None, 55, 55, 128)  8192        block1_conv2_act[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "block2_pool (MaxPooling2D)      (None, 55, 55, 128)  0           block2_sepconv2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization (BatchNorma (None, 55, 55, 128)  512         conv2d[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "add (Add)                       (None, 55, 55, 128)  0           block2_pool[0][0]                \n",
      "                                                                 batch_normalization[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "block3_sepconv1_act (Activation (None, 55, 55, 128)  0           add[0][0]                        \n",
      "__________________________________________________________________________________________________\n",
      "block3_sepconv1 (SeparableConv2 (None, 55, 55, 256)  33920       block3_sepconv1_act[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "block3_sepconv1_bn (BatchNormal (None, 55, 55, 256)  1024        block3_sepconv1[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block3_sepconv2_act (Activation (None, 55, 55, 256)  0           block3_sepconv1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "block3_sepconv2 (SeparableConv2 (None, 55, 55, 256)  67840       block3_sepconv2_act[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "block3_sepconv2_bn (BatchNormal (None, 55, 55, 256)  1024        block3_sepconv2[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_1 (Conv2D)               (None, 28, 28, 256)  32768       add[0][0]                        \n",
      "__________________________________________________________________________________________________\n",
      "block3_pool (MaxPooling2D)      (None, 28, 28, 256)  0           block3_sepconv2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_1 (BatchNor (None, 28, 28, 256)  1024        conv2d_1[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "add_1 (Add)                     (None, 28, 28, 256)  0           block3_pool[0][0]                \n",
      "                                                                 batch_normalization_1[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "block4_sepconv1_act (Activation (None, 28, 28, 256)  0           add_1[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "block4_sepconv1 (SeparableConv2 (None, 28, 28, 728)  188672      block4_sepconv1_act[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "block4_sepconv1_bn (BatchNormal (None, 28, 28, 728)  2912        block4_sepconv1[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block4_sepconv2_act (Activation (None, 28, 28, 728)  0           block4_sepconv1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "block4_sepconv2 (SeparableConv2 (None, 28, 28, 728)  536536      block4_sepconv2_act[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "block4_sepconv2_bn (BatchNormal (None, 28, 28, 728)  2912        block4_sepconv2[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_2 (Conv2D)               (None, 14, 14, 728)  186368      add_1[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "block4_pool (MaxPooling2D)      (None, 14, 14, 728)  0           block4_sepconv2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_2 (BatchNor (None, 14, 14, 728)  2912        conv2d_2[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "add_2 (Add)                     (None, 14, 14, 728)  0           block4_pool[0][0]                \n",
      "                                                                 batch_normalization_2[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "block5_sepconv1_act (Activation (None, 14, 14, 728)  0           add_2[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "block5_sepconv1 (SeparableConv2 (None, 14, 14, 728)  536536      block5_sepconv1_act[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "block5_sepconv1_bn (BatchNormal (None, 14, 14, 728)  2912        block5_sepconv1[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block5_sepconv2_act (Activation (None, 14, 14, 728)  0           block5_sepconv1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "block5_sepconv2 (SeparableConv2 (None, 14, 14, 728)  536536      block5_sepconv2_act[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "block5_sepconv2_bn (BatchNormal (None, 14, 14, 728)  2912        block5_sepconv2[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block5_sepconv3_act (Activation (None, 14, 14, 728)  0           block5_sepconv2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "block5_sepconv3 (SeparableConv2 (None, 14, 14, 728)  536536      block5_sepconv3_act[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "block5_sepconv3_bn (BatchNormal (None, 14, 14, 728)  2912        block5_sepconv3[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "add_3 (Add)                     (None, 14, 14, 728)  0           block5_sepconv3_bn[0][0]         \n",
      "                                                                 add_2[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "block6_sepconv1_act (Activation (None, 14, 14, 728)  0           add_3[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "block6_sepconv1 (SeparableConv2 (None, 14, 14, 728)  536536      block6_sepconv1_act[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "block6_sepconv1_bn (BatchNormal (None, 14, 14, 728)  2912        block6_sepconv1[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block6_sepconv2_act (Activation (None, 14, 14, 728)  0           block6_sepconv1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "block6_sepconv2 (SeparableConv2 (None, 14, 14, 728)  536536      block6_sepconv2_act[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "block6_sepconv2_bn (BatchNormal (None, 14, 14, 728)  2912        block6_sepconv2[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block6_sepconv3_act (Activation (None, 14, 14, 728)  0           block6_sepconv2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "block6_sepconv3 (SeparableConv2 (None, 14, 14, 728)  536536      block6_sepconv3_act[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "block6_sepconv3_bn (BatchNormal (None, 14, 14, 728)  2912        block6_sepconv3[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "add_4 (Add)                     (None, 14, 14, 728)  0           block6_sepconv3_bn[0][0]         \n",
      "                                                                 add_3[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "block7_sepconv1_act (Activation (None, 14, 14, 728)  0           add_4[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "block7_sepconv1 (SeparableConv2 (None, 14, 14, 728)  536536      block7_sepconv1_act[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "block7_sepconv1_bn (BatchNormal (None, 14, 14, 728)  2912        block7_sepconv1[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block7_sepconv2_act (Activation (None, 14, 14, 728)  0           block7_sepconv1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "block7_sepconv2 (SeparableConv2 (None, 14, 14, 728)  536536      block7_sepconv2_act[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "block7_sepconv2_bn (BatchNormal (None, 14, 14, 728)  2912        block7_sepconv2[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block7_sepconv3_act (Activation (None, 14, 14, 728)  0           block7_sepconv2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "block7_sepconv3 (SeparableConv2 (None, 14, 14, 728)  536536      block7_sepconv3_act[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "block7_sepconv3_bn (BatchNormal (None, 14, 14, 728)  2912        block7_sepconv3[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "add_5 (Add)                     (None, 14, 14, 728)  0           block7_sepconv3_bn[0][0]         \n",
      "                                                                 add_4[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "block8_sepconv1_act (Activation (None, 14, 14, 728)  0           add_5[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "block8_sepconv1 (SeparableConv2 (None, 14, 14, 728)  536536      block8_sepconv1_act[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "block8_sepconv1_bn (BatchNormal (None, 14, 14, 728)  2912        block8_sepconv1[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block8_sepconv2_act (Activation (None, 14, 14, 728)  0           block8_sepconv1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "block8_sepconv2 (SeparableConv2 (None, 14, 14, 728)  536536      block8_sepconv2_act[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "block8_sepconv2_bn (BatchNormal (None, 14, 14, 728)  2912        block8_sepconv2[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block8_sepconv3_act (Activation (None, 14, 14, 728)  0           block8_sepconv2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "block8_sepconv3 (SeparableConv2 (None, 14, 14, 728)  536536      block8_sepconv3_act[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "block8_sepconv3_bn (BatchNormal (None, 14, 14, 728)  2912        block8_sepconv3[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "add_6 (Add)                     (None, 14, 14, 728)  0           block8_sepconv3_bn[0][0]         \n",
      "                                                                 add_5[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "block9_sepconv1_act (Activation (None, 14, 14, 728)  0           add_6[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "block9_sepconv1 (SeparableConv2 (None, 14, 14, 728)  536536      block9_sepconv1_act[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "block9_sepconv1_bn (BatchNormal (None, 14, 14, 728)  2912        block9_sepconv1[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block9_sepconv2_act (Activation (None, 14, 14, 728)  0           block9_sepconv1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "block9_sepconv2 (SeparableConv2 (None, 14, 14, 728)  536536      block9_sepconv2_act[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "block9_sepconv2_bn (BatchNormal (None, 14, 14, 728)  2912        block9_sepconv2[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block9_sepconv3_act (Activation (None, 14, 14, 728)  0           block9_sepconv2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "block9_sepconv3 (SeparableConv2 (None, 14, 14, 728)  536536      block9_sepconv3_act[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "block9_sepconv3_bn (BatchNormal (None, 14, 14, 728)  2912        block9_sepconv3[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "add_7 (Add)                     (None, 14, 14, 728)  0           block9_sepconv3_bn[0][0]         \n",
      "                                                                 add_6[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "block10_sepconv1_act (Activatio (None, 14, 14, 728)  0           add_7[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "block10_sepconv1 (SeparableConv (None, 14, 14, 728)  536536      block10_sepconv1_act[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "block10_sepconv1_bn (BatchNorma (None, 14, 14, 728)  2912        block10_sepconv1[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "block10_sepconv2_act (Activatio (None, 14, 14, 728)  0           block10_sepconv1_bn[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "block10_sepconv2 (SeparableConv (None, 14, 14, 728)  536536      block10_sepconv2_act[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "block10_sepconv2_bn (BatchNorma (None, 14, 14, 728)  2912        block10_sepconv2[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "block10_sepconv3_act (Activatio (None, 14, 14, 728)  0           block10_sepconv2_bn[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "block10_sepconv3 (SeparableConv (None, 14, 14, 728)  536536      block10_sepconv3_act[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "block10_sepconv3_bn (BatchNorma (None, 14, 14, 728)  2912        block10_sepconv3[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "add_8 (Add)                     (None, 14, 14, 728)  0           block10_sepconv3_bn[0][0]        \n",
      "                                                                 add_7[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "block11_sepconv1_act (Activatio (None, 14, 14, 728)  0           add_8[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "block11_sepconv1 (SeparableConv (None, 14, 14, 728)  536536      block11_sepconv1_act[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "block11_sepconv1_bn (BatchNorma (None, 14, 14, 728)  2912        block11_sepconv1[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "block11_sepconv2_act (Activatio (None, 14, 14, 728)  0           block11_sepconv1_bn[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "block11_sepconv2 (SeparableConv (None, 14, 14, 728)  536536      block11_sepconv2_act[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "block11_sepconv2_bn (BatchNorma (None, 14, 14, 728)  2912        block11_sepconv2[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "block11_sepconv3_act (Activatio (None, 14, 14, 728)  0           block11_sepconv2_bn[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "block11_sepconv3 (SeparableConv (None, 14, 14, 728)  536536      block11_sepconv3_act[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "block11_sepconv3_bn (BatchNorma (None, 14, 14, 728)  2912        block11_sepconv3[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "add_9 (Add)                     (None, 14, 14, 728)  0           block11_sepconv3_bn[0][0]        \n",
      "                                                                 add_8[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "block12_sepconv1_act (Activatio (None, 14, 14, 728)  0           add_9[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "block12_sepconv1 (SeparableConv (None, 14, 14, 728)  536536      block12_sepconv1_act[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "block12_sepconv1_bn (BatchNorma (None, 14, 14, 728)  2912        block12_sepconv1[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "block12_sepconv2_act (Activatio (None, 14, 14, 728)  0           block12_sepconv1_bn[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "block12_sepconv2 (SeparableConv (None, 14, 14, 728)  536536      block12_sepconv2_act[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "block12_sepconv2_bn (BatchNorma (None, 14, 14, 728)  2912        block12_sepconv2[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "block12_sepconv3_act (Activatio (None, 14, 14, 728)  0           block12_sepconv2_bn[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "block12_sepconv3 (SeparableConv (None, 14, 14, 728)  536536      block12_sepconv3_act[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "block12_sepconv3_bn (BatchNorma (None, 14, 14, 728)  2912        block12_sepconv3[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "add_10 (Add)                    (None, 14, 14, 728)  0           block12_sepconv3_bn[0][0]        \n",
      "                                                                 add_9[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "block13_sepconv1_act (Activatio (None, 14, 14, 728)  0           add_10[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "block13_sepconv1 (SeparableConv (None, 14, 14, 728)  536536      block13_sepconv1_act[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "block13_sepconv1_bn (BatchNorma (None, 14, 14, 728)  2912        block13_sepconv1[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "block13_sepconv2_act (Activatio (None, 14, 14, 728)  0           block13_sepconv1_bn[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "block13_sepconv2 (SeparableConv (None, 14, 14, 1024) 752024      block13_sepconv2_act[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "block13_sepconv2_bn (BatchNorma (None, 14, 14, 1024) 4096        block13_sepconv2[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_3 (Conv2D)               (None, 7, 7, 1024)   745472      add_10[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "block13_pool (MaxPooling2D)     (None, 7, 7, 1024)   0           block13_sepconv2_bn[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_3 (BatchNor (None, 7, 7, 1024)   4096        conv2d_3[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "add_11 (Add)                    (None, 7, 7, 1024)   0           block13_pool[0][0]               \n",
      "                                                                 batch_normalization_3[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "block14_sepconv1 (SeparableConv (None, 7, 7, 1536)   1582080     add_11[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "block14_sepconv1_bn (BatchNorma (None, 7, 7, 1536)   6144        block14_sepconv1[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "block14_sepconv1_act (Activatio (None, 7, 7, 1536)   0           block14_sepconv1_bn[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "block14_sepconv2 (SeparableConv (None, 7, 7, 2048)   3159552     block14_sepconv1_act[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "block14_sepconv2_bn (BatchNorma (None, 7, 7, 2048)   8192        block14_sepconv2[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "block14_sepconv2_act (Activatio (None, 7, 7, 2048)   0           block14_sepconv2_bn[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_1 (AveragePoo (None, 1, 1, 2048)   0           block14_sepconv2_act[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "flatten (Flatten)               (None, 2048)         0           average_pooling2d_1[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "dense_2 (Dense)                 (None, 64)           131136      flatten[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "dropout_1 (Dropout)             (None, 64)           0           dense_2[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "dense_3 (Dense)                 (None, 10)           650         dropout_1[0][0]                  \n",
      "==================================================================================================\n",
      "Total params: 20,993,266\n",
      "Trainable params: 131,786\n",
      "Non-trainable params: 20,861,480\n",
      "__________________________________________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "Scn9kFwNaJiH",
    "outputId": "669a741b-f9d2-4e93-85ae-2fdee7339d12"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/training.py:1844: UserWarning: `Model.fit_generator` is deprecated and will be removed in a future version. Please use `Model.fit`, which supports generators.\n",
      "  warnings.warn('`Model.fit_generator` is deprecated and '\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/25\n",
      "83/83 [==============================] - ETA: 0s - loss: 1.7178 - accuracy: 0.4135WARNING:tensorflow:Your input ran out of data; interrupting training. Make sure that your dataset or generator can generate at least `steps_per_epoch * epochs` batches (in this case, 20 batches). You may need to use the repeat() function when building your dataset.\n",
      "83/83 [==============================] - 12s 113ms/step - loss: 1.7117 - accuracy: 0.4161 - val_loss: 0.3524 - val_accuracy: 0.9521\n",
      "Epoch 2/25\n",
      "83/83 [==============================] - 7s 86ms/step - loss: 0.5578 - accuracy: 0.8338\n",
      "Epoch 3/25\n",
      "83/83 [==============================] - 7s 86ms/step - loss: 0.3541 - accuracy: 0.8971\n",
      "Epoch 4/25\n",
      "83/83 [==============================] - 7s 86ms/step - loss: 0.2991 - accuracy: 0.9105\n",
      "Epoch 5/25\n",
      "83/83 [==============================] - 7s 86ms/step - loss: 0.2256 - accuracy: 0.9358\n",
      "Epoch 6/25\n",
      "83/83 [==============================] - 7s 85ms/step - loss: 0.1755 - accuracy: 0.9601\n",
      "Epoch 7/25\n",
      "83/83 [==============================] - 7s 85ms/step - loss: 0.1902 - accuracy: 0.9464\n",
      "Epoch 8/25\n",
      "83/83 [==============================] - 7s 85ms/step - loss: 0.1431 - accuracy: 0.9657\n",
      "Epoch 9/25\n",
      "83/83 [==============================] - 7s 86ms/step - loss: 0.1389 - accuracy: 0.9580\n",
      "Epoch 10/25\n",
      "83/83 [==============================] - 7s 86ms/step - loss: 0.1896 - accuracy: 0.9423\n",
      "Epoch 11/25\n",
      "83/83 [==============================] - 7s 86ms/step - loss: 0.1204 - accuracy: 0.9666\n",
      "Epoch 12/25\n",
      "83/83 [==============================] - 7s 86ms/step - loss: 0.1232 - accuracy: 0.9613\n",
      "Epoch 13/25\n",
      "83/83 [==============================] - 7s 86ms/step - loss: 0.0780 - accuracy: 0.9835\n",
      "Epoch 14/25\n",
      "83/83 [==============================] - 7s 86ms/step - loss: 0.0850 - accuracy: 0.9700\n",
      "Epoch 15/25\n",
      "83/83 [==============================] - 7s 85ms/step - loss: 0.0941 - accuracy: 0.9772\n",
      "Epoch 16/25\n",
      "83/83 [==============================] - 7s 86ms/step - loss: 0.0739 - accuracy: 0.9816\n",
      "Epoch 17/25\n",
      "83/83 [==============================] - 7s 86ms/step - loss: 0.0654 - accuracy: 0.9846\n",
      "Epoch 18/25\n",
      "83/83 [==============================] - 7s 86ms/step - loss: 0.1033 - accuracy: 0.9683\n",
      "Epoch 19/25\n",
      "83/83 [==============================] - 7s 86ms/step - loss: 0.0877 - accuracy: 0.9795\n",
      "Epoch 20/25\n",
      "83/83 [==============================] - 7s 86ms/step - loss: 0.0637 - accuracy: 0.9836\n",
      "Epoch 21/25\n",
      "83/83 [==============================] - 7s 86ms/step - loss: 0.0520 - accuracy: 0.9886\n",
      "Epoch 22/25\n",
      "83/83 [==============================] - 7s 86ms/step - loss: 0.0834 - accuracy: 0.9775\n",
      "Epoch 23/25\n",
      "83/83 [==============================] - 7s 86ms/step - loss: 0.0699 - accuracy: 0.9777\n",
      "Epoch 24/25\n",
      "83/83 [==============================] - 7s 86ms/step - loss: 0.0682 - accuracy: 0.9779\n",
      "Epoch 25/25\n",
      "83/83 [==============================] - 7s 87ms/step - loss: 0.0603 - accuracy: 0.9823\n"
     ]
    }
   ],
   "source": [
    "model.compile(loss = 'categorical_crossentropy', optimizer = Adam(lr=1e-3),\n",
    "    metrics=[\"accuracy\"])\n",
    "H = model.fit_generator(\n",
    "    trainAug.flow(trainX, trainY.toarray(), batch_size=8),\n",
    "    steps_per_epoch=len(trainX) // 8,\n",
    "    validation_data=(testX, testY.toarray()),\n",
    "    validation_steps=len(testX) // 8,\n",
    "    epochs=25)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "id": "sdls53BRbZPv"
   },
   "outputs": [],
   "source": [
    "y_pred = model.predict(testX)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "3vb9IIjOcdy0",
    "outputId": "b0caa5c7-f3d2-4796-930b-6468072c2756"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([7, 1, 3, 5, 5, 9, 4, 3, 2, 5, 7, 6, 3, 1, 1, 6, 0, 9, 4, 9, 7, 8,\n",
       "       0, 2, 9, 5, 6, 2, 3, 5, 4, 8, 8, 9, 1, 3, 4, 3, 9, 5, 5, 4, 2, 7,\n",
       "       3, 3, 6, 3, 4, 0, 6, 0, 5, 9, 8, 4, 8, 9, 5, 5, 2, 4, 3, 9, 3, 1,\n",
       "       3, 9, 5, 6, 1, 7, 6, 4, 8, 8, 1, 6, 3, 3, 9, 2, 7, 8, 0, 1, 4, 9,\n",
       "       8, 2, 4, 7, 3, 4, 5, 5, 7, 2, 9, 0, 5, 5, 6, 4, 7, 5, 6, 6, 3, 6,\n",
       "       7, 7, 6, 6, 2, 2, 2, 8, 6, 0, 2, 6, 8, 8, 8, 7, 4, 4, 9, 2, 7, 1,\n",
       "       1, 7, 6, 0, 6, 7, 8, 5, 0, 1, 6, 3, 1, 3, 5, 8, 0, 5, 3, 9, 3, 5,\n",
       "       6, 2, 3, 3, 0, 0, 9, 1, 1, 5, 4, 6, 6])"
      ]
     },
     "execution_count": 48,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_pred = np.argmax(y_pred, axis=1)\n",
    "y_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "vT7rV3JybiTr",
    "outputId": "043c894f-e111-4245-fb05-a90a97c8a205"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy : 0.9880239520958084\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import accuracy_score\n",
    "acc = accuracy_score(testY.toarray().argmax(axis=1), y_pred)\n",
    "print('Accuracy :',acc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "ryL-S7wPcA8-"
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "accelerator": "GPU",
  "colab": {
   "name": "ButterflyClassification.ipynb",
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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 },
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