Classification.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import os\n",
    "import matplotlib.pyplot as plt\n",
    "from keras.models import Sequential\n",
    "from keras.layers import Dense,Flatten,Dropout\n",
    "from keras.applications.mobilenet_v3 import MobileNetV3Small\n",
    "from keras.preprocessing.image import ImageDataGenerator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('classifier.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "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>img_dir</th>\n",
       "      <th>img_name</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>7253</td>\n",
       "      <td>7253</td>\n",
       "      <td>7253</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>18</td>\n",
       "      <td>1601</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>D:\\SAR Project Data\\S1A_IW_GRDH_1SDV_20191114T...</td>\n",
       "      <td>719.png</td>\n",
       "      <td>water</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>982</td>\n",
       "      <td>6</td>\n",
       "      <td>3611</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                  img_dir img_name  label\n",
       "count                                                7253     7253   7253\n",
       "unique                                                 18     1601      3\n",
       "top     D:\\SAR Project Data\\S1A_IW_GRDH_1SDV_20191114T...  719.png  water\n",
       "freq                                                  982        6   3611"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "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>img_dir</th>\n",
       "      <th>img_name</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1601</td>\n",
       "      <td>1601</td>\n",
       "      <td>1601</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>13</td>\n",
       "      <td>1601</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>D:\\SAR Project Data\\S1A_IW_GRDH_1SDV_20191121T...</td>\n",
       "      <td>266.png</td>\n",
       "      <td>water</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>571</td>\n",
       "      <td>1</td>\n",
       "      <td>810</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                  img_dir img_name  label\n",
       "count                                                1601     1601   1601\n",
       "unique                                                 13     1601      3\n",
       "top     D:\\SAR Project Data\\S1A_IW_GRDH_1SDV_20191121T...  266.png  water\n",
       "freq                                                  571        1    810"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfd = df.drop_duplicates('img_name','last')\n",
    "dfd.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-9-0c0f1bc238f0>:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  dfd['abs_path'] = (dfd['img_dir']+'\\\\'+dfd['img_name'])\n"
     ]
    }
   ],
   "source": [
    "dfd['abs_path'] = (dfd['img_dir']+'\\\\'+dfd['img_name'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x2274ba5afd0>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dfm = dfd.loc[dfd['label'] == 'land'].reset_index()\n",
    "i = 290\n",
    "\n",
    "i_p = os.path.join(dfm['img_dir'][i],dfm['img_name'][i])\n",
    "img = plt.imread(i_p)\n",
    "plt.imshow(img,cmap='gray')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "dg = ImageDataGenerator(brightness_range=[0.2,1.8]\n",
    "                        ,horizontal_flip=True,vertical_flip=True\n",
    "                        ,validation_split=0.25\n",
    "                        #,rotation_range=[90]\n",
    "                        #,zoom_range=[0.5,1]\n",
    "                       )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['abs_path'] = (df['img_dir']+'\\\\'+df['img_name'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 5440 validated image filenames belonging to 3 classes.\n",
      "Found 1813 validated image filenames belonging to 3 classes.\n"
     ]
    }
   ],
   "source": [
    "t_it = dg.flow_from_dataframe(dataframe=df\n",
    "                            ,x_col='abs_path'\n",
    "                            ,y_col='label'\n",
    "                            ,class_mode='categorical'\n",
    "                            ,shuffle=True\n",
    "                            ,target_size=(224,224)\n",
    "                            ,subset='training'\n",
    "                            ,batch_size=64\n",
    "                           )\n",
    "\n",
    "v_it = dg.flow_from_dataframe(dataframe=df\n",
    "                            ,x_col='abs_path'\n",
    "                            ,y_col='label'\n",
    "                            ,class_mode='categorical'\n",
    "                            ,shuffle=True\n",
    "                            ,target_size=(224,224)\n",
    "                            ,subset='validation'\n",
    "                            ,batch_size=64\n",
    "                           )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x2274f58c130>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(t_it.next()[0][9,:,:,0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:`input_shape` is undefined or non-square, or `rows` is not 224. Weights for input shape (224, 224) will be loaded as the default.\n",
      "Downloading data from https://storage.googleapis.com/tensorflow/keras-applications/mobilenet_v3/weights_mobilenet_v3_small_224_1.0_float_no_top.h5\n",
      "6701056/6698480 [==============================] - 3s 0us/step\n",
      "6709248/6698480 [==============================] - 3s 0us/step\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.engine.functional.Functional at 0x227510b2ac0>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "base = MobileNetV3Small(weights='imagenet',include_top=False,pooling='avg')\n",
    "base"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"MobilenetV3small\"\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_1 (InputLayer)            [(None, None, None,  0                                            \n",
      "__________________________________________________________________________________________________\n",
      "rescaling (Rescaling)           (None, None, None, 3 0           input_1[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "Conv (Conv2D)                   (None, None, None, 1 432         rescaling[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "Conv/BatchNorm (BatchNormalizat (None, None, None, 1 64          Conv[0][0]                       \n",
      "__________________________________________________________________________________________________\n",
      "tf.__operators__.add (TFOpLambd (None, None, None, 1 0           Conv/BatchNorm[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "re_lu (ReLU)                    (None, None, None, 1 0           tf.__operators__.add[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "tf.math.multiply (TFOpLambda)   (None, None, None, 1 0           re_lu[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "multiply (Multiply)             (None, None, None, 1 0           tf.math.multiply[0][0]           \n",
      "                                                                 Conv/BatchNorm[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv/depthwise/pad (Ze (None, None, None, 1 0           multiply[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv/depthwise (Depthw (None, None, None, 1 144         expanded_conv/depthwise/pad[0][0]\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv/depthwise/BatchNo (None, None, None, 1 64          expanded_conv/depthwise[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "re_lu_1 (ReLU)                  (None, None, None, 1 0           expanded_conv/depthwise/BatchNorm\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv/squeeze_excite/Av (None, 16)           0           re_lu_1[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "reshape (Reshape)               (None, 1, 1, 16)     0           expanded_conv/squeeze_excite/AvgP\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv/squeeze_excite/Co (None, 1, 1, 8)      136         reshape[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv/squeeze_excite/Re (None, 1, 1, 8)      0           expanded_conv/squeeze_excite/Conv\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv/squeeze_excite/Co (None, 1, 1, 16)     144         expanded_conv/squeeze_excite/Relu\n",
      "__________________________________________________________________________________________________\n",
      "tf.__operators__.add_1 (TFOpLam (None, 1, 1, 16)     0           expanded_conv/squeeze_excite/Conv\n",
      "__________________________________________________________________________________________________\n",
      "re_lu_2 (ReLU)                  (None, 1, 1, 16)     0           tf.__operators__.add_1[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "tf.math.multiply_1 (TFOpLambda) (None, 1, 1, 16)     0           re_lu_2[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv/squeeze_excite/Mu (None, None, None, 1 0           re_lu_1[0][0]                    \n",
      "                                                                 tf.math.multiply_1[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv/project (Conv2D)  (None, None, None, 1 256         expanded_conv/squeeze_excite/Mul[\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv/project/BatchNorm (None, None, None, 1 64          expanded_conv/project[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_1/expand (Conv2D) (None, None, None, 7 1152        expanded_conv/project/BatchNorm[0\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_1/expand/BatchNor (None, None, None, 7 288         expanded_conv_1/expand[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "re_lu_3 (ReLU)                  (None, None, None, 7 0           expanded_conv_1/expand/BatchNorm[\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_1/depthwise/pad ( (None, None, None, 7 0           re_lu_3[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_1/depthwise (Dept (None, None, None, 7 648         expanded_conv_1/depthwise/pad[0][\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_1/depthwise/Batch (None, None, None, 7 288         expanded_conv_1/depthwise[0][0]  \n",
      "__________________________________________________________________________________________________\n",
      "re_lu_4 (ReLU)                  (None, None, None, 7 0           expanded_conv_1/depthwise/BatchNo\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_1/project (Conv2D (None, None, None, 2 1728        re_lu_4[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_1/project/BatchNo (None, None, None, 2 96          expanded_conv_1/project[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_2/expand (Conv2D) (None, None, None, 8 2112        expanded_conv_1/project/BatchNorm\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_2/expand/BatchNor (None, None, None, 8 352         expanded_conv_2/expand[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "re_lu_5 (ReLU)                  (None, None, None, 8 0           expanded_conv_2/expand/BatchNorm[\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_2/depthwise (Dept (None, None, None, 8 792         re_lu_5[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_2/depthwise/Batch (None, None, None, 8 352         expanded_conv_2/depthwise[0][0]  \n",
      "__________________________________________________________________________________________________\n",
      "re_lu_6 (ReLU)                  (None, None, None, 8 0           expanded_conv_2/depthwise/BatchNo\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_2/project (Conv2D (None, None, None, 2 2112        re_lu_6[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_2/project/BatchNo (None, None, None, 2 96          expanded_conv_2/project[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_2/Add (Add)       (None, None, None, 2 0           expanded_conv_1/project/BatchNorm\n",
      "                                                                 expanded_conv_2/project/BatchNorm\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_3/expand (Conv2D) (None, None, None, 9 2304        expanded_conv_2/Add[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_3/expand/BatchNor (None, None, None, 9 384         expanded_conv_3/expand[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "tf.__operators__.add_2 (TFOpLam (None, None, None, 9 0           expanded_conv_3/expand/BatchNorm[\n",
      "__________________________________________________________________________________________________\n",
      "re_lu_7 (ReLU)                  (None, None, None, 9 0           tf.__operators__.add_2[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "tf.math.multiply_2 (TFOpLambda) (None, None, None, 9 0           re_lu_7[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "multiply_1 (Multiply)           (None, None, None, 9 0           tf.math.multiply_2[0][0]         \n",
      "                                                                 expanded_conv_3/expand/BatchNorm[\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_3/depthwise/pad ( (None, None, None, 9 0           multiply_1[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_3/depthwise (Dept (None, None, None, 9 2400        expanded_conv_3/depthwise/pad[0][\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_3/depthwise/Batch (None, None, None, 9 384         expanded_conv_3/depthwise[0][0]  \n",
      "__________________________________________________________________________________________________\n",
      "tf.__operators__.add_3 (TFOpLam (None, None, None, 9 0           expanded_conv_3/depthwise/BatchNo\n",
      "__________________________________________________________________________________________________\n",
      "re_lu_8 (ReLU)                  (None, None, None, 9 0           tf.__operators__.add_3[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "tf.math.multiply_3 (TFOpLambda) (None, None, None, 9 0           re_lu_8[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "multiply_2 (Multiply)           (None, None, None, 9 0           tf.math.multiply_3[0][0]         \n",
      "                                                                 expanded_conv_3/depthwise/BatchNo\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_3/squeeze_excite/ (None, 96)           0           multiply_2[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "reshape_1 (Reshape)             (None, 1, 1, 96)     0           expanded_conv_3/squeeze_excite/Av\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_3/squeeze_excite/ (None, 1, 1, 24)     2328        reshape_1[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_3/squeeze_excite/ (None, 1, 1, 24)     0           expanded_conv_3/squeeze_excite/Co\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_3/squeeze_excite/ (None, 1, 1, 96)     2400        expanded_conv_3/squeeze_excite/Re\n",
      "__________________________________________________________________________________________________\n",
      "tf.__operators__.add_4 (TFOpLam (None, 1, 1, 96)     0           expanded_conv_3/squeeze_excite/Co\n",
      "__________________________________________________________________________________________________\n",
      "re_lu_9 (ReLU)                  (None, 1, 1, 96)     0           tf.__operators__.add_4[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "tf.math.multiply_4 (TFOpLambda) (None, 1, 1, 96)     0           re_lu_9[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_3/squeeze_excite/ (None, None, None, 9 0           multiply_2[0][0]                 \n",
      "                                                                 tf.math.multiply_4[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_3/project (Conv2D (None, None, None, 4 3840        expanded_conv_3/squeeze_excite/Mu\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_3/project/BatchNo (None, None, None, 4 160         expanded_conv_3/project[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_4/expand (Conv2D) (None, None, None, 2 9600        expanded_conv_3/project/BatchNorm\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_4/expand/BatchNor (None, None, None, 2 960         expanded_conv_4/expand[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "tf.__operators__.add_5 (TFOpLam (None, None, None, 2 0           expanded_conv_4/expand/BatchNorm[\n",
      "__________________________________________________________________________________________________\n",
      "re_lu_10 (ReLU)                 (None, None, None, 2 0           tf.__operators__.add_5[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "tf.math.multiply_5 (TFOpLambda) (None, None, None, 2 0           re_lu_10[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "multiply_3 (Multiply)           (None, None, None, 2 0           tf.math.multiply_5[0][0]         \n",
      "                                                                 expanded_conv_4/expand/BatchNorm[\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_4/depthwise (Dept (None, None, None, 2 6000        multiply_3[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_4/depthwise/Batch (None, None, None, 2 960         expanded_conv_4/depthwise[0][0]  \n",
      "__________________________________________________________________________________________________\n",
      "tf.__operators__.add_6 (TFOpLam (None, None, None, 2 0           expanded_conv_4/depthwise/BatchNo\n",
      "__________________________________________________________________________________________________\n",
      "re_lu_11 (ReLU)                 (None, None, None, 2 0           tf.__operators__.add_6[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "tf.math.multiply_6 (TFOpLambda) (None, None, None, 2 0           re_lu_11[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "multiply_4 (Multiply)           (None, None, None, 2 0           tf.math.multiply_6[0][0]         \n",
      "                                                                 expanded_conv_4/depthwise/BatchNo\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_4/squeeze_excite/ (None, 240)          0           multiply_4[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "reshape_2 (Reshape)             (None, 1, 1, 240)    0           expanded_conv_4/squeeze_excite/Av\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_4/squeeze_excite/ (None, 1, 1, 64)     15424       reshape_2[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_4/squeeze_excite/ (None, 1, 1, 64)     0           expanded_conv_4/squeeze_excite/Co\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_4/squeeze_excite/ (None, 1, 1, 240)    15600       expanded_conv_4/squeeze_excite/Re\n",
      "__________________________________________________________________________________________________\n",
      "tf.__operators__.add_7 (TFOpLam (None, 1, 1, 240)    0           expanded_conv_4/squeeze_excite/Co\n",
      "__________________________________________________________________________________________________\n",
      "re_lu_12 (ReLU)                 (None, 1, 1, 240)    0           tf.__operators__.add_7[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "tf.math.multiply_7 (TFOpLambda) (None, 1, 1, 240)    0           re_lu_12[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_4/squeeze_excite/ (None, None, None, 2 0           multiply_4[0][0]                 \n",
      "                                                                 tf.math.multiply_7[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_4/project (Conv2D (None, None, None, 4 9600        expanded_conv_4/squeeze_excite/Mu\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_4/project/BatchNo (None, None, None, 4 160         expanded_conv_4/project[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_4/Add (Add)       (None, None, None, 4 0           expanded_conv_3/project/BatchNorm\n",
      "                                                                 expanded_conv_4/project/BatchNorm\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_5/expand (Conv2D) (None, None, None, 2 9600        expanded_conv_4/Add[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_5/expand/BatchNor (None, None, None, 2 960         expanded_conv_5/expand[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "tf.__operators__.add_8 (TFOpLam (None, None, None, 2 0           expanded_conv_5/expand/BatchNorm[\n",
      "__________________________________________________________________________________________________\n",
      "re_lu_13 (ReLU)                 (None, None, None, 2 0           tf.__operators__.add_8[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "tf.math.multiply_8 (TFOpLambda) (None, None, None, 2 0           re_lu_13[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "multiply_5 (Multiply)           (None, None, None, 2 0           tf.math.multiply_8[0][0]         \n",
      "                                                                 expanded_conv_5/expand/BatchNorm[\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_5/depthwise (Dept (None, None, None, 2 6000        multiply_5[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_5/depthwise/Batch (None, None, None, 2 960         expanded_conv_5/depthwise[0][0]  \n",
      "__________________________________________________________________________________________________\n",
      "tf.__operators__.add_9 (TFOpLam (None, None, None, 2 0           expanded_conv_5/depthwise/BatchNo\n",
      "__________________________________________________________________________________________________\n",
      "re_lu_14 (ReLU)                 (None, None, None, 2 0           tf.__operators__.add_9[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "tf.math.multiply_9 (TFOpLambda) (None, None, None, 2 0           re_lu_14[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "multiply_6 (Multiply)           (None, None, None, 2 0           tf.math.multiply_9[0][0]         \n",
      "                                                                 expanded_conv_5/depthwise/BatchNo\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_5/squeeze_excite/ (None, 240)          0           multiply_6[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "reshape_3 (Reshape)             (None, 1, 1, 240)    0           expanded_conv_5/squeeze_excite/Av\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_5/squeeze_excite/ (None, 1, 1, 64)     15424       reshape_3[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_5/squeeze_excite/ (None, 1, 1, 64)     0           expanded_conv_5/squeeze_excite/Co\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_5/squeeze_excite/ (None, 1, 1, 240)    15600       expanded_conv_5/squeeze_excite/Re\n",
      "__________________________________________________________________________________________________\n",
      "tf.__operators__.add_10 (TFOpLa (None, 1, 1, 240)    0           expanded_conv_5/squeeze_excite/Co\n",
      "__________________________________________________________________________________________________\n",
      "re_lu_15 (ReLU)                 (None, 1, 1, 240)    0           tf.__operators__.add_10[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "tf.math.multiply_10 (TFOpLambda (None, 1, 1, 240)    0           re_lu_15[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_5/squeeze_excite/ (None, None, None, 2 0           multiply_6[0][0]                 \n",
      "                                                                 tf.math.multiply_10[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_5/project (Conv2D (None, None, None, 4 9600        expanded_conv_5/squeeze_excite/Mu\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_5/project/BatchNo (None, None, None, 4 160         expanded_conv_5/project[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_5/Add (Add)       (None, None, None, 4 0           expanded_conv_4/Add[0][0]        \n",
      "                                                                 expanded_conv_5/project/BatchNorm\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_6/expand (Conv2D) (None, None, None, 1 4800        expanded_conv_5/Add[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_6/expand/BatchNor (None, None, None, 1 480         expanded_conv_6/expand[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "tf.__operators__.add_11 (TFOpLa (None, None, None, 1 0           expanded_conv_6/expand/BatchNorm[\n",
      "__________________________________________________________________________________________________\n",
      "re_lu_16 (ReLU)                 (None, None, None, 1 0           tf.__operators__.add_11[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "tf.math.multiply_11 (TFOpLambda (None, None, None, 1 0           re_lu_16[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "multiply_7 (Multiply)           (None, None, None, 1 0           tf.math.multiply_11[0][0]        \n",
      "                                                                 expanded_conv_6/expand/BatchNorm[\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_6/depthwise (Dept (None, None, None, 1 3000        multiply_7[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_6/depthwise/Batch (None, None, None, 1 480         expanded_conv_6/depthwise[0][0]  \n",
      "__________________________________________________________________________________________________\n",
      "tf.__operators__.add_12 (TFOpLa (None, None, None, 1 0           expanded_conv_6/depthwise/BatchNo\n",
      "__________________________________________________________________________________________________\n",
      "re_lu_17 (ReLU)                 (None, None, None, 1 0           tf.__operators__.add_12[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "tf.math.multiply_12 (TFOpLambda (None, None, None, 1 0           re_lu_17[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "multiply_8 (Multiply)           (None, None, None, 1 0           tf.math.multiply_12[0][0]        \n",
      "                                                                 expanded_conv_6/depthwise/BatchNo\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_6/squeeze_excite/ (None, 120)          0           multiply_8[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "reshape_4 (Reshape)             (None, 1, 1, 120)    0           expanded_conv_6/squeeze_excite/Av\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_6/squeeze_excite/ (None, 1, 1, 32)     3872        reshape_4[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_6/squeeze_excite/ (None, 1, 1, 32)     0           expanded_conv_6/squeeze_excite/Co\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_6/squeeze_excite/ (None, 1, 1, 120)    3960        expanded_conv_6/squeeze_excite/Re\n",
      "__________________________________________________________________________________________________\n",
      "tf.__operators__.add_13 (TFOpLa (None, 1, 1, 120)    0           expanded_conv_6/squeeze_excite/Co\n",
      "__________________________________________________________________________________________________\n",
      "re_lu_18 (ReLU)                 (None, 1, 1, 120)    0           tf.__operators__.add_13[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "tf.math.multiply_13 (TFOpLambda (None, 1, 1, 120)    0           re_lu_18[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_6/squeeze_excite/ (None, None, None, 1 0           multiply_8[0][0]                 \n",
      "                                                                 tf.math.multiply_13[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_6/project (Conv2D (None, None, None, 4 5760        expanded_conv_6/squeeze_excite/Mu\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_6/project/BatchNo (None, None, None, 4 192         expanded_conv_6/project[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_7/expand (Conv2D) (None, None, None, 1 6912        expanded_conv_6/project/BatchNorm\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_7/expand/BatchNor (None, None, None, 1 576         expanded_conv_7/expand[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "tf.__operators__.add_14 (TFOpLa (None, None, None, 1 0           expanded_conv_7/expand/BatchNorm[\n",
      "__________________________________________________________________________________________________\n",
      "re_lu_19 (ReLU)                 (None, None, None, 1 0           tf.__operators__.add_14[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "tf.math.multiply_14 (TFOpLambda (None, None, None, 1 0           re_lu_19[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "multiply_9 (Multiply)           (None, None, None, 1 0           tf.math.multiply_14[0][0]        \n",
      "                                                                 expanded_conv_7/expand/BatchNorm[\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_7/depthwise (Dept (None, None, None, 1 3600        multiply_9[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_7/depthwise/Batch (None, None, None, 1 576         expanded_conv_7/depthwise[0][0]  \n",
      "__________________________________________________________________________________________________\n",
      "tf.__operators__.add_15 (TFOpLa (None, None, None, 1 0           expanded_conv_7/depthwise/BatchNo\n",
      "__________________________________________________________________________________________________\n",
      "re_lu_20 (ReLU)                 (None, None, None, 1 0           tf.__operators__.add_15[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "tf.math.multiply_15 (TFOpLambda (None, None, None, 1 0           re_lu_20[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "multiply_10 (Multiply)          (None, None, None, 1 0           tf.math.multiply_15[0][0]        \n",
      "                                                                 expanded_conv_7/depthwise/BatchNo\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_7/squeeze_excite/ (None, 144)          0           multiply_10[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "reshape_5 (Reshape)             (None, 1, 1, 144)    0           expanded_conv_7/squeeze_excite/Av\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_7/squeeze_excite/ (None, 1, 1, 40)     5800        reshape_5[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_7/squeeze_excite/ (None, 1, 1, 40)     0           expanded_conv_7/squeeze_excite/Co\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_7/squeeze_excite/ (None, 1, 1, 144)    5904        expanded_conv_7/squeeze_excite/Re\n",
      "__________________________________________________________________________________________________\n",
      "tf.__operators__.add_16 (TFOpLa (None, 1, 1, 144)    0           expanded_conv_7/squeeze_excite/Co\n",
      "__________________________________________________________________________________________________\n",
      "re_lu_21 (ReLU)                 (None, 1, 1, 144)    0           tf.__operators__.add_16[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "tf.math.multiply_16 (TFOpLambda (None, 1, 1, 144)    0           re_lu_21[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_7/squeeze_excite/ (None, None, None, 1 0           multiply_10[0][0]                \n",
      "                                                                 tf.math.multiply_16[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_7/project (Conv2D (None, None, None, 4 6912        expanded_conv_7/squeeze_excite/Mu\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_7/project/BatchNo (None, None, None, 4 192         expanded_conv_7/project[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_7/Add (Add)       (None, None, None, 4 0           expanded_conv_6/project/BatchNorm\n",
      "                                                                 expanded_conv_7/project/BatchNorm\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_8/expand (Conv2D) (None, None, None, 2 13824       expanded_conv_7/Add[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_8/expand/BatchNor (None, None, None, 2 1152        expanded_conv_8/expand[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "tf.__operators__.add_17 (TFOpLa (None, None, None, 2 0           expanded_conv_8/expand/BatchNorm[\n",
      "__________________________________________________________________________________________________\n",
      "re_lu_22 (ReLU)                 (None, None, None, 2 0           tf.__operators__.add_17[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "tf.math.multiply_17 (TFOpLambda (None, None, None, 2 0           re_lu_22[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "multiply_11 (Multiply)          (None, None, None, 2 0           tf.math.multiply_17[0][0]        \n",
      "                                                                 expanded_conv_8/expand/BatchNorm[\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_8/depthwise/pad ( (None, None, None, 2 0           multiply_11[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_8/depthwise (Dept (None, None, None, 2 7200        expanded_conv_8/depthwise/pad[0][\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_8/depthwise/Batch (None, None, None, 2 1152        expanded_conv_8/depthwise[0][0]  \n",
      "__________________________________________________________________________________________________\n",
      "tf.__operators__.add_18 (TFOpLa (None, None, None, 2 0           expanded_conv_8/depthwise/BatchNo\n",
      "__________________________________________________________________________________________________\n",
      "re_lu_23 (ReLU)                 (None, None, None, 2 0           tf.__operators__.add_18[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "tf.math.multiply_18 (TFOpLambda (None, None, None, 2 0           re_lu_23[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "multiply_12 (Multiply)          (None, None, None, 2 0           tf.math.multiply_18[0][0]        \n",
      "                                                                 expanded_conv_8/depthwise/BatchNo\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_8/squeeze_excite/ (None, 288)          0           multiply_12[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "reshape_6 (Reshape)             (None, 1, 1, 288)    0           expanded_conv_8/squeeze_excite/Av\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_8/squeeze_excite/ (None, 1, 1, 72)     20808       reshape_6[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_8/squeeze_excite/ (None, 1, 1, 72)     0           expanded_conv_8/squeeze_excite/Co\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_8/squeeze_excite/ (None, 1, 1, 288)    21024       expanded_conv_8/squeeze_excite/Re\n",
      "__________________________________________________________________________________________________\n",
      "tf.__operators__.add_19 (TFOpLa (None, 1, 1, 288)    0           expanded_conv_8/squeeze_excite/Co\n",
      "__________________________________________________________________________________________________\n",
      "re_lu_24 (ReLU)                 (None, 1, 1, 288)    0           tf.__operators__.add_19[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "tf.math.multiply_19 (TFOpLambda (None, 1, 1, 288)    0           re_lu_24[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_8/squeeze_excite/ (None, None, None, 2 0           multiply_12[0][0]                \n",
      "                                                                 tf.math.multiply_19[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_8/project (Conv2D (None, None, None, 9 27648       expanded_conv_8/squeeze_excite/Mu\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_8/project/BatchNo (None, None, None, 9 384         expanded_conv_8/project[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_9/expand (Conv2D) (None, None, None, 5 55296       expanded_conv_8/project/BatchNorm\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_9/expand/BatchNor (None, None, None, 5 2304        expanded_conv_9/expand[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "tf.__operators__.add_20 (TFOpLa (None, None, None, 5 0           expanded_conv_9/expand/BatchNorm[\n",
      "__________________________________________________________________________________________________\n",
      "re_lu_25 (ReLU)                 (None, None, None, 5 0           tf.__operators__.add_20[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "tf.math.multiply_20 (TFOpLambda (None, None, None, 5 0           re_lu_25[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "multiply_13 (Multiply)          (None, None, None, 5 0           tf.math.multiply_20[0][0]        \n",
      "                                                                 expanded_conv_9/expand/BatchNorm[\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_9/depthwise (Dept (None, None, None, 5 14400       multiply_13[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_9/depthwise/Batch (None, None, None, 5 2304        expanded_conv_9/depthwise[0][0]  \n",
      "__________________________________________________________________________________________________\n",
      "tf.__operators__.add_21 (TFOpLa (None, None, None, 5 0           expanded_conv_9/depthwise/BatchNo\n",
      "__________________________________________________________________________________________________\n",
      "re_lu_26 (ReLU)                 (None, None, None, 5 0           tf.__operators__.add_21[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "tf.math.multiply_21 (TFOpLambda (None, None, None, 5 0           re_lu_26[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "multiply_14 (Multiply)          (None, None, None, 5 0           tf.math.multiply_21[0][0]        \n",
      "                                                                 expanded_conv_9/depthwise/BatchNo\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_9/squeeze_excite/ (None, 576)          0           multiply_14[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "reshape_7 (Reshape)             (None, 1, 1, 576)    0           expanded_conv_9/squeeze_excite/Av\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_9/squeeze_excite/ (None, 1, 1, 144)    83088       reshape_7[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_9/squeeze_excite/ (None, 1, 1, 144)    0           expanded_conv_9/squeeze_excite/Co\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_9/squeeze_excite/ (None, 1, 1, 576)    83520       expanded_conv_9/squeeze_excite/Re\n",
      "__________________________________________________________________________________________________\n",
      "tf.__operators__.add_22 (TFOpLa (None, 1, 1, 576)    0           expanded_conv_9/squeeze_excite/Co\n",
      "__________________________________________________________________________________________________\n",
      "re_lu_27 (ReLU)                 (None, 1, 1, 576)    0           tf.__operators__.add_22[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "tf.math.multiply_22 (TFOpLambda (None, 1, 1, 576)    0           re_lu_27[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_9/squeeze_excite/ (None, None, None, 5 0           multiply_14[0][0]                \n",
      "                                                                 tf.math.multiply_22[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_9/project (Conv2D (None, None, None, 9 55296       expanded_conv_9/squeeze_excite/Mu\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_9/project/BatchNo (None, None, None, 9 384         expanded_conv_9/project[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_9/Add (Add)       (None, None, None, 9 0           expanded_conv_8/project/BatchNorm\n",
      "                                                                 expanded_conv_9/project/BatchNorm\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_10/expand (Conv2D (None, None, None, 5 55296       expanded_conv_9/Add[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_10/expand/BatchNo (None, None, None, 5 2304        expanded_conv_10/expand[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "tf.__operators__.add_23 (TFOpLa (None, None, None, 5 0           expanded_conv_10/expand/BatchNorm\n",
      "__________________________________________________________________________________________________\n",
      "re_lu_28 (ReLU)                 (None, None, None, 5 0           tf.__operators__.add_23[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "tf.math.multiply_23 (TFOpLambda (None, None, None, 5 0           re_lu_28[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "multiply_15 (Multiply)          (None, None, None, 5 0           tf.math.multiply_23[0][0]        \n",
      "                                                                 expanded_conv_10/expand/BatchNorm\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_10/depthwise (Dep (None, None, None, 5 14400       multiply_15[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_10/depthwise/Batc (None, None, None, 5 2304        expanded_conv_10/depthwise[0][0] \n",
      "__________________________________________________________________________________________________\n",
      "tf.__operators__.add_24 (TFOpLa (None, None, None, 5 0           expanded_conv_10/depthwise/BatchN\n",
      "__________________________________________________________________________________________________\n",
      "re_lu_29 (ReLU)                 (None, None, None, 5 0           tf.__operators__.add_24[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "tf.math.multiply_24 (TFOpLambda (None, None, None, 5 0           re_lu_29[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "multiply_16 (Multiply)          (None, None, None, 5 0           tf.math.multiply_24[0][0]        \n",
      "                                                                 expanded_conv_10/depthwise/BatchN\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_10/squeeze_excite (None, 576)          0           multiply_16[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "reshape_8 (Reshape)             (None, 1, 1, 576)    0           expanded_conv_10/squeeze_excite/A\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_10/squeeze_excite (None, 1, 1, 144)    83088       reshape_8[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_10/squeeze_excite (None, 1, 1, 144)    0           expanded_conv_10/squeeze_excite/C\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_10/squeeze_excite (None, 1, 1, 576)    83520       expanded_conv_10/squeeze_excite/R\n",
      "__________________________________________________________________________________________________\n",
      "tf.__operators__.add_25 (TFOpLa (None, 1, 1, 576)    0           expanded_conv_10/squeeze_excite/C\n",
      "__________________________________________________________________________________________________\n",
      "re_lu_30 (ReLU)                 (None, 1, 1, 576)    0           tf.__operators__.add_25[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "tf.math.multiply_25 (TFOpLambda (None, 1, 1, 576)    0           re_lu_30[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_10/squeeze_excite (None, None, None, 5 0           multiply_16[0][0]                \n",
      "                                                                 tf.math.multiply_25[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_10/project (Conv2 (None, None, None, 9 55296       expanded_conv_10/squeeze_excite/M\n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_10/project/BatchN (None, None, None, 9 384         expanded_conv_10/project[0][0]   \n",
      "__________________________________________________________________________________________________\n",
      "expanded_conv_10/Add (Add)      (None, None, None, 9 0           expanded_conv_9/Add[0][0]        \n",
      "                                                                 expanded_conv_10/project/BatchNor\n",
      "__________________________________________________________________________________________________\n",
      "Conv_1 (Conv2D)                 (None, None, None, 5 55296       expanded_conv_10/Add[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "Conv_1/BatchNorm (BatchNormaliz (None, None, None, 5 2304        Conv_1[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "tf.__operators__.add_26 (TFOpLa (None, None, None, 5 0           Conv_1/BatchNorm[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "re_lu_31 (ReLU)                 (None, None, None, 5 0           tf.__operators__.add_26[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "tf.math.multiply_26 (TFOpLambda (None, None, None, 5 0           re_lu_31[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "multiply_17 (Multiply)          (None, None, None, 5 0           tf.math.multiply_26[0][0]        \n",
      "                                                                 Conv_1/BatchNorm[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "Conv_2 (Conv2D)                 (None, None, None, 1 590848      multiply_17[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "tf.__operators__.add_27 (TFOpLa (None, None, None, 1 0           Conv_2[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "re_lu_32 (ReLU)                 (None, None, None, 1 0           tf.__operators__.add_27[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "tf.math.multiply_27 (TFOpLambda (None, None, None, 1 0           re_lu_32[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "multiply_18 (Multiply)          (None, None, None, 1 0           tf.math.multiply_27[0][0]        \n",
      "                                                                 Conv_2[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "avg_pool (GlobalAveragePooling2 (None, 1024)         0           multiply_18[0][0]                \n",
      "==================================================================================================\n",
      "Total params: 1,529,968\n",
      "Trainable params: 1,517,856\n",
      "Non-trainable params: 12,112\n",
      "__________________________________________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "base.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "mdl = Sequential([\n",
    "    base\n",
    "    ,Dropout(0.6)\n",
    "    ,Dense(128,activation='relu')\n",
    "    ,Dropout(0.6)\n",
    "    ,Dense(64,activation='relu')\n",
    "    ,Dense(25,activation='relu')\n",
    "    ,Dropout(0.5)\n",
    "    ,Dense(3,activation='softmax')\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential_1\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "MobilenetV3small (Functional (None, 1024)              1529968   \n",
      "_________________________________________________________________\n",
      "dropout_3 (Dropout)          (None, 1024)              0         \n",
      "_________________________________________________________________\n",
      "dense_4 (Dense)              (None, 128)               131200    \n",
      "_________________________________________________________________\n",
      "dropout_4 (Dropout)          (None, 128)               0         \n",
      "_________________________________________________________________\n",
      "dense_5 (Dense)              (None, 64)                8256      \n",
      "_________________________________________________________________\n",
      "dense_6 (Dense)              (None, 25)                1625      \n",
      "_________________________________________________________________\n",
      "dropout_5 (Dropout)          (None, 25)                0         \n",
      "_________________________________________________________________\n",
      "dense_7 (Dense)              (None, 3)                 78        \n",
      "=================================================================\n",
      "Total params: 1,671,127\n",
      "Trainable params: 141,159\n",
      "Non-trainable params: 1,529,968\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "mdl.layers[0].trainable = False\n",
    "mdl.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/2\n",
      "85/85 [==============================] - 329s 4s/step - loss: 0.2724 - acc: 0.9183 - val_loss: 0.1357 - val_acc: 0.9643\n",
      "Epoch 2/2\n",
      "85/85 [==============================] - 205s 2s/step - loss: 0.2231 - acc: 0.9399 - val_loss: 0.1228 - val_acc: 0.9648\n"
     ]
    }
   ],
   "source": [
    "mdl.compile(optimizer='adam',loss='categorical_crossentropy',metrics=['acc'])\n",
    "\n",
    "h = mdl.fit_generator(generator=t_it\n",
    "                  ,validation_data=v_it\n",
    "                  ,validation_steps=v_it.n//v_it.batch_size\n",
    "                  ,steps_per_epoch=t_it.n//t_it.batch_size\n",
    "                  ,epochs=2\n",
    "                 )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'loss': [0.26211515069007874, 0.21785402297973633],\n",
       " 'acc': [0.9246323704719543, 0.9367647171020508],\n",
       " 'val_loss': [0.13571400940418243, 0.12280677258968353],\n",
       " 'val_acc': [0.9642857313156128, 0.96484375]}"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "h.history"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "28/28 [==============================] - 37s 1s/step - loss: 0.1204 - acc: 0.9688\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[0.1204090490937233, 0.96875]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mdl.evaluate_generator(generator=v_it,verbose=1,steps=v_it.n//v_it.batch_size)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['loss', 'acc']"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mdl.metrics_names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Function `_wrapped_model` contains input name(s) MobilenetV3small_input with unsupported characters which will be renamed to mobilenetv3small_input in the SavedModel.\n",
      "C:\\Users\\Tabish\\AppData\\Roaming\\Python\\Python39\\site-packages\\keras\\utils\\generic_utils.py:494: CustomMaskWarning: Custom mask layers require a config and must override get_config. When loading, the custom mask layer must be passed to the custom_objects argument.\n",
      "  warnings.warn('Custom mask layers require a config and must override '\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: .\\lw_clf\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: .\\lw_clf\\assets\n"
     ]
    }
   ],
   "source": [
    "mdl.save('.\\\\lw_clf')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3.9663281e-02 9.6032172e-01 1.5005204e-05] [0. 1. 0.]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for x in t_it:\n",
    "    plt.imshow(x[0][9,:,:,0])\n",
    "    print(mdl.predict(x[0])[9],x[1][9])\n",
    "    break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'l_w': 0, 'land': 1, 'water': 2}"
      ]
     },
     "execution_count": 81,
     "metadata": {},
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