FireDetection.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Fire Detection Using the MobileNetV2 Model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Importing the libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "id": "Ya705WIOmeVO"
   },
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "from tensorflow.keras.preprocessing.image import ImageDataGenerator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 37
    },
    "id": "CMhszMpwmgN_",
    "outputId": "58a72033-1989-4e7c-fe7c-40c4aa2fc81e"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2.9.1'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf.__version__"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Preprocessing the Training and Validation Data Sets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "11ozd2NnmisG",
    "outputId": "d53d38e4-49b5-43ea-f013-2192bfa1517c"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 1800 images belonging to 2 classes.\n",
      "Found 200 images belonging to 2 classes.\n"
     ]
    }
   ],
   "source": [
    "train_datagen = ImageDataGenerator(rescale=1./255, shear_range=0.2, zoom_range=0.2, horizontal_flip=True) \n",
    "training_set = train_datagen.flow_from_directory(\n",
    "        '/Users/aayushsubramaniam/Downloads/FIRE-SMOKE-DATASET/Train',\n",
    "        target_size=(224, 224),\n",
    "        batch_size=128,\n",
    "        shuffle=True,\n",
    "        class_mode='categorical')\n",
    "\n",
    "validation_datagen = ImageDataGenerator(rescale=1./255, shear_range=0.2, zoom_range=0.2, horizontal_flip=True) \n",
    "\n",
    "validation_set = validation_datagen.flow_from_directory(\n",
    "    '/Users/aayushsubramaniam/Downloads/FIRE-SMOKE-DATASET/Test',\n",
    "    target_size=(224,224),\n",
    "    batch_size=20,\n",
    "    class_mode='categorical',\n",
    "    shuffle=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The MobileNetV2 Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "id": "e11DT1fFrUg8"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:`input_shape` is undefined or non-square, or `rows` is not in [96, 128, 160, 192, 224]. Weights for input shape (224, 224) will be loaded as the default.\n",
      "Epoch 1/20\n",
      "14/14 [==============================] - ETA: 0s - loss: 6.0107 - acc: 0.7356WARNING: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, 14 batches). You may need to use the repeat() function when building your dataset.\n",
      "14/14 [==============================] - 68s 5s/step - loss: 6.0107 - acc: 0.7356 - val_loss: 0.2925 - val_acc: 0.8750\n",
      "Epoch 2/20\n",
      "14/14 [==============================] - 56s 4s/step - loss: 0.3387 - acc: 0.8995\n",
      "Epoch 3/20\n",
      "14/14 [==============================] - 55s 4s/step - loss: 0.1449 - acc: 0.9420\n",
      "Epoch 4/20\n",
      "14/14 [==============================] - 56s 4s/step - loss: 0.2311 - acc: 0.9145\n",
      "Epoch 5/20\n",
      "14/14 [==============================] - 56s 4s/step - loss: 0.2028 - acc: 0.9270\n",
      "Epoch 6/20\n",
      "14/14 [==============================] - 56s 4s/step - loss: 0.0707 - acc: 0.9743\n",
      "Epoch 7/20\n",
      "14/14 [==============================] - 56s 4s/step - loss: 0.0578 - acc: 0.9803\n",
      "Epoch 8/20\n",
      "14/14 [==============================] - 55s 4s/step - loss: 0.2676 - acc: 0.9318\n",
      "Epoch 9/20\n",
      "14/14 [==============================] - 90s 7s/step - loss: 0.1325 - acc: 0.9659\n",
      "Epoch 10/20\n",
      "14/14 [==============================] - 57s 4s/step - loss: 0.0366 - acc: 0.9827\n",
      "Epoch 11/20\n",
      "14/14 [==============================] - 53s 4s/step - loss: 0.0796 - acc: 0.9731\n",
      "Epoch 12/20\n",
      "14/14 [==============================] - 54s 4s/step - loss: 0.0193 - acc: 0.9928\n",
      "Epoch 13/20\n",
      "14/14 [==============================] - 54s 4s/step - loss: 0.3718 - acc: 0.9492\n",
      "Epoch 14/20\n",
      "14/14 [==============================] - 50s 3s/step - loss: 0.0246 - acc: 0.9905\n",
      "Epoch 15/20\n",
      "14/14 [==============================] - 30s 2s/step - loss: 0.0316 - acc: 0.9874\n",
      "Epoch 16/20\n",
      "14/14 [==============================] - 33s 2s/step - loss: 0.0487 - acc: 0.9803\n",
      "Epoch 17/20\n",
      "14/14 [==============================] - 37s 3s/step - loss: 0.0836 - acc: 0.9737\n",
      "Epoch 18/20\n",
      "14/14 [==============================] - 36s 2s/step - loss: 0.1740 - acc: 0.9641\n",
      "Epoch 19/20\n",
      "14/14 [==============================] - 34s 2s/step - loss: 0.0134 - acc: 0.9934\n",
      "Epoch 20/20\n",
      "14/14 [==============================] - 33s 3s/step - loss: 0.0166 - acc: 0.9934\n"
     ]
    }
   ],
   "source": [
    "from tensorflow.keras.applications import MobileNetV2\n",
    "from tensorflow.keras.preprocessing import image\n",
    "from tensorflow.keras.models import Model\n",
    "from tensorflow.keras.layers import Dense, GlobalAveragePooling2D, Input, Dropout\n",
    "input_tensor = Input(shape=(224, 224, 3)) #Keras Input Tensor Object\n",
    "base_model = MobileNetV2(input_tensor=input_tensor, weights='imagenet', include_top=False) # Returns a Keras Model Object\n",
    "x = base_model.output\n",
    "x = GlobalAveragePooling2D()(x)\n",
    "x = Dense(2048, activation='relu')(x)\n",
    "x = Dropout(0.25)(x)\n",
    "x = Dense(1024, activation='relu')(x)\n",
    "x = Dropout(0.2)(x)\n",
    "predictions = Dense(2, activation='softmax')(x)\n",
    "\n",
    "model = Model(inputs=base_model.input, outputs=predictions)\n",
    "for layer in base_model.layers:\n",
    "  layer.trainable = False\n",
    "model.compile(optimizer='rmsprop', loss='categorical_crossentropy', metrics=['acc'])\n",
    "\n",
    "history = model.fit(\n",
    "training_set,\n",
    "steps_per_epoch = 14,\n",
    "epochs = 20,\n",
    "validation_data = validation_set,\n",
    "validation_steps = 14)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "id": "PKnMfmAwqXi2"
   },
   "outputs": [],
   "source": [
    "for layer in model.layers[:249]:\n",
    "  layer.trainable = False\n",
    "for layer in model.layers[249:]:\n",
    "  layer.trainable = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "id": "vGIWpnA5HQHa"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Library/Frameworks/Python.framework/Versions/3.8/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The `lr` argument is deprecated, use `learning_rate` instead.\n",
      "  super(SGD, self).__init__(name, **kwargs)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/10\n",
      "14/14 [==============================] - ETA: 0s - loss: 0.0375 - acc: 0.9880WARNING: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, 14 batches). You may need to use the repeat() function when building your dataset.\n",
      "14/14 [==============================] - 39s 3s/step - loss: 0.0375 - acc: 0.9880 - val_loss: 0.2506 - val_acc: 0.9600\n",
      "Epoch 2/10\n",
      "14/14 [==============================] - 34s 2s/step - loss: 0.0255 - acc: 0.9877\n",
      "Epoch 3/10\n",
      "14/14 [==============================] - 32s 2s/step - loss: 0.0291 - acc: 0.9880\n",
      "Epoch 4/10\n",
      "14/14 [==============================] - 32s 2s/step - loss: 0.0327 - acc: 0.9868\n",
      "Epoch 5/10\n",
      "14/14 [==============================] - 32s 2s/step - loss: 0.0306 - acc: 0.9886\n",
      "Epoch 6/10\n",
      "14/14 [==============================] - 32s 2s/step - loss: 0.0387 - acc: 0.9886\n",
      "Epoch 7/10\n",
      "14/14 [==============================] - 32s 2s/step - loss: 0.0323 - acc: 0.9868\n",
      "Epoch 8/10\n",
      "14/14 [==============================] - 32s 2s/step - loss: 0.0299 - acc: 0.9892\n",
      "Epoch 9/10\n",
      "14/14 [==============================] - 32s 2s/step - loss: 0.0339 - acc: 0.9898\n",
      "Epoch 10/10\n",
      "14/14 [==============================] - 33s 2s/step - loss: 0.0335 - acc: 0.9862\n"
     ]
    }
   ],
   "source": [
    "from tensorflow.keras.optimizers import SGD\n",
    "model.compile(optimizer=SGD(lr=0.0001, momentum=0.9), loss='categorical_crossentropy', metrics=['acc'])\n",
    "history = model.fit(\n",
    "training_set,\n",
    "steps_per_epoch = 14,\n",
    "epochs = 10,\n",
    "validation_data = validation_set,\n",
    "validation_steps = 14)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note: The Functions of Transfer Learning & Fine Tuning were performed\n",
    "\n",
    "References:\n",
    "\n",
    "\n",
    "1.   https://keras.io/api/applications/mobilenet/\n",
    "2.   https://keras.io/guides/transfer_learning/#freezing-layers-understanding-the-trainable-attribute\n",
    "3.   https://keras.io/api/applications/#usage-examples-for-image-classification-models\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Making a Single Prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "id": "LyfUj_og7CaC"
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from tensorflow.keras.preprocessing import image\n",
    "test_image = image.load_img('/Users/aayushsubramaniam/Downloads/picture.jpg', target_size = (224,224))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "id": "LyfUj_og7CaC"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1/1 [==============================] - 0s 393ms/step\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'Fire': 0, 'Neutral': 1}"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_image = image.img_to_array(test_image) \n",
    "test_image = np.expand_dims(test_image, axis = 0) \n",
    "results = model.predict(test_image/255.0)\n",
    "training_set.class_indices "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "class_name = ['Fire','Neutral']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This image most likely belongs to Fire with a 73.11 percent confidence.\n"
     ]
    }
   ],
   "source": [
    "score = tf.nn.softmax(results[0])\n",
    "print(\n",
    "    \"This image most likely belongs to {} with a {:.2f} percent confidence.\"\n",
    "    .format(class_name[np.argmax(score)], 100 * np.max(score))\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "id": "mSEp5aU_kq3U"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fire\n"
     ]
    }
   ],
   "source": [
    "print(prediction)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Saving the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"model\"\n",
      "__________________________________________________________________________________________________\n",
      " Layer (type)                   Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      " input_1 (InputLayer)           [(None, 224, 224, 3  0           []                               \n",
      "                                )]                                                                \n",
      "                                                                                                  \n",
      " Conv1 (Conv2D)                 (None, 112, 112, 32  864         ['input_1[0][0]']                \n",
      "                                )                                                                 \n",
      "                                                                                                  \n",
      " bn_Conv1 (BatchNormalization)  (None, 112, 112, 32  128         ['Conv1[0][0]']                  \n",
      "                                )                                                                 \n",
      "                                                                                                  \n",
      " Conv1_relu (ReLU)              (None, 112, 112, 32  0           ['bn_Conv1[0][0]']               \n",
      "                                )                                                                 \n",
      "                                                                                                  \n",
      " expanded_conv_depthwise (Depth  (None, 112, 112, 32  288        ['Conv1_relu[0][0]']             \n",
      " wiseConv2D)                    )                                                                 \n",
      "                                                                                                  \n",
      " expanded_conv_depthwise_BN (Ba  (None, 112, 112, 32  128        ['expanded_conv_depthwise[0][0]']\n",
      " tchNormalization)              )                                                                 \n",
      "                                                                                                  \n",
      " expanded_conv_depthwise_relu (  (None, 112, 112, 32  0          ['expanded_conv_depthwise_BN[0][0\n",
      " ReLU)                          )                                ]']                              \n",
      "                                                                                                  \n",
      " expanded_conv_project (Conv2D)  (None, 112, 112, 16  512        ['expanded_conv_depthwise_relu[0]\n",
      "                                )                                [0]']                            \n",
      "                                                                                                  \n",
      " expanded_conv_project_BN (Batc  (None, 112, 112, 16  64         ['expanded_conv_project[0][0]']  \n",
      " hNormalization)                )                                                                 \n",
      "                                                                                                  \n",
      " block_1_expand (Conv2D)        (None, 112, 112, 96  1536        ['expanded_conv_project_BN[0][0]'\n",
      "                                )                                ]                                \n",
      "                                                                                                  \n",
      " block_1_expand_BN (BatchNormal  (None, 112, 112, 96  384        ['block_1_expand[0][0]']         \n",
      " ization)                       )                                                                 \n",
      "                                                                                                  \n",
      " block_1_expand_relu (ReLU)     (None, 112, 112, 96  0           ['block_1_expand_BN[0][0]']      \n",
      "                                )                                                                 \n",
      "                                                                                                  \n",
      " block_1_pad (ZeroPadding2D)    (None, 113, 113, 96  0           ['block_1_expand_relu[0][0]']    \n",
      "                                )                                                                 \n",
      "                                                                                                  \n",
      " block_1_depthwise (DepthwiseCo  (None, 56, 56, 96)  864         ['block_1_pad[0][0]']            \n",
      " nv2D)                                                                                            \n",
      "                                                                                                  \n",
      " block_1_depthwise_BN (BatchNor  (None, 56, 56, 96)  384         ['block_1_depthwise[0][0]']      \n",
      " malization)                                                                                      \n",
      "                                                                                                  \n",
      " block_1_depthwise_relu (ReLU)  (None, 56, 56, 96)   0           ['block_1_depthwise_BN[0][0]']   \n",
      "                                                                                                  \n",
      " block_1_project (Conv2D)       (None, 56, 56, 24)   2304        ['block_1_depthwise_relu[0][0]'] \n",
      "                                                                                                  \n",
      " block_1_project_BN (BatchNorma  (None, 56, 56, 24)  96          ['block_1_project[0][0]']        \n",
      " lization)                                                                                        \n",
      "                                                                                                  \n",
      " block_2_expand (Conv2D)        (None, 56, 56, 144)  3456        ['block_1_project_BN[0][0]']     \n",
      "                                                                                                  \n",
      " block_2_expand_BN (BatchNormal  (None, 56, 56, 144)  576        ['block_2_expand[0][0]']         \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " block_2_expand_relu (ReLU)     (None, 56, 56, 144)  0           ['block_2_expand_BN[0][0]']      \n",
      "                                                                                                  \n",
      " block_2_depthwise (DepthwiseCo  (None, 56, 56, 144)  1296       ['block_2_expand_relu[0][0]']    \n",
      " nv2D)                                                                                            \n",
      "                                                                                                  \n",
      " block_2_depthwise_BN (BatchNor  (None, 56, 56, 144)  576        ['block_2_depthwise[0][0]']      \n",
      " malization)                                                                                      \n",
      "                                                                                                  \n",
      " block_2_depthwise_relu (ReLU)  (None, 56, 56, 144)  0           ['block_2_depthwise_BN[0][0]']   \n",
      "                                                                                                  \n",
      " block_2_project (Conv2D)       (None, 56, 56, 24)   3456        ['block_2_depthwise_relu[0][0]'] \n",
      "                                                                                                  \n",
      " block_2_project_BN (BatchNorma  (None, 56, 56, 24)  96          ['block_2_project[0][0]']        \n",
      " lization)                                                                                        \n",
      "                                                                                                  \n",
      " block_2_add (Add)              (None, 56, 56, 24)   0           ['block_1_project_BN[0][0]',     \n",
      "                                                                  'block_2_project_BN[0][0]']     \n",
      "                                                                                                  \n",
      " block_3_expand (Conv2D)        (None, 56, 56, 144)  3456        ['block_2_add[0][0]']            \n",
      "                                                                                                  \n",
      " block_3_expand_BN (BatchNormal  (None, 56, 56, 144)  576        ['block_3_expand[0][0]']         \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " block_3_expand_relu (ReLU)     (None, 56, 56, 144)  0           ['block_3_expand_BN[0][0]']      \n",
      "                                                                                                  \n",
      " block_3_pad (ZeroPadding2D)    (None, 57, 57, 144)  0           ['block_3_expand_relu[0][0]']    \n",
      "                                                                                                  \n",
      " block_3_depthwise (DepthwiseCo  (None, 28, 28, 144)  1296       ['block_3_pad[0][0]']            \n",
      " nv2D)                                                                                            \n",
      "                                                                                                  \n",
      " block_3_depthwise_BN (BatchNor  (None, 28, 28, 144)  576        ['block_3_depthwise[0][0]']      \n",
      " malization)                                                                                      \n",
      "                                                                                                  \n",
      " block_3_depthwise_relu (ReLU)  (None, 28, 28, 144)  0           ['block_3_depthwise_BN[0][0]']   \n",
      "                                                                                                  \n",
      " block_3_project (Conv2D)       (None, 28, 28, 32)   4608        ['block_3_depthwise_relu[0][0]'] \n",
      "                                                                                                  \n",
      " block_3_project_BN (BatchNorma  (None, 28, 28, 32)  128         ['block_3_project[0][0]']        \n",
      " lization)                                                                                        \n",
      "                                                                                                  \n",
      " block_4_expand (Conv2D)        (None, 28, 28, 192)  6144        ['block_3_project_BN[0][0]']     \n",
      "                                                                                                  \n",
      " block_4_expand_BN (BatchNormal  (None, 28, 28, 192)  768        ['block_4_expand[0][0]']         \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " block_4_expand_relu (ReLU)     (None, 28, 28, 192)  0           ['block_4_expand_BN[0][0]']      \n",
      "                                                                                                  \n",
      " block_4_depthwise (DepthwiseCo  (None, 28, 28, 192)  1728       ['block_4_expand_relu[0][0]']    \n",
      " nv2D)                                                                                            \n",
      "                                                                                                  \n",
      " block_4_depthwise_BN (BatchNor  (None, 28, 28, 192)  768        ['block_4_depthwise[0][0]']      \n",
      " malization)                                                                                      \n",
      "                                                                                                  \n",
      " block_4_depthwise_relu (ReLU)  (None, 28, 28, 192)  0           ['block_4_depthwise_BN[0][0]']   \n",
      "                                                                                                  \n",
      " block_4_project (Conv2D)       (None, 28, 28, 32)   6144        ['block_4_depthwise_relu[0][0]'] \n",
      "                                                                                                  \n",
      " block_4_project_BN (BatchNorma  (None, 28, 28, 32)  128         ['block_4_project[0][0]']        \n",
      " lization)                                                                                        \n",
      "                                                                                                  \n",
      " block_4_add (Add)              (None, 28, 28, 32)   0           ['block_3_project_BN[0][0]',     \n",
      "                                                                  'block_4_project_BN[0][0]']     \n",
      "                                                                                                  \n",
      " block_5_expand (Conv2D)        (None, 28, 28, 192)  6144        ['block_4_add[0][0]']            \n",
      "                                                                                                  \n",
      " block_5_expand_BN (BatchNormal  (None, 28, 28, 192)  768        ['block_5_expand[0][0]']         \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " block_5_expand_relu (ReLU)     (None, 28, 28, 192)  0           ['block_5_expand_BN[0][0]']      \n",
      "                                                                                                  \n",
      " block_5_depthwise (DepthwiseCo  (None, 28, 28, 192)  1728       ['block_5_expand_relu[0][0]']    \n",
      " nv2D)                                                                                            \n",
      "                                                                                                  \n",
      " block_5_depthwise_BN (BatchNor  (None, 28, 28, 192)  768        ['block_5_depthwise[0][0]']      \n",
      " malization)                                                                                      \n",
      "                                                                                                  \n",
      " block_5_depthwise_relu (ReLU)  (None, 28, 28, 192)  0           ['block_5_depthwise_BN[0][0]']   \n",
      "                                                                                                  \n",
      " block_5_project (Conv2D)       (None, 28, 28, 32)   6144        ['block_5_depthwise_relu[0][0]'] \n",
      "                                                                                                  \n",
      " block_5_project_BN (BatchNorma  (None, 28, 28, 32)  128         ['block_5_project[0][0]']        \n",
      " lization)                                                                                        \n",
      "                                                                                                  \n",
      " block_5_add (Add)              (None, 28, 28, 32)   0           ['block_4_add[0][0]',            \n",
      "                                                                  'block_5_project_BN[0][0]']     \n",
      "                                                                                                  \n",
      " block_6_expand (Conv2D)        (None, 28, 28, 192)  6144        ['block_5_add[0][0]']            \n",
      "                                                                                                  \n",
      " block_6_expand_BN (BatchNormal  (None, 28, 28, 192)  768        ['block_6_expand[0][0]']         \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " block_6_expand_relu (ReLU)     (None, 28, 28, 192)  0           ['block_6_expand_BN[0][0]']      \n",
      "                                                                                                  \n",
      " block_6_pad (ZeroPadding2D)    (None, 29, 29, 192)  0           ['block_6_expand_relu[0][0]']    \n",
      "                                                                                                  \n",
      " block_6_depthwise (DepthwiseCo  (None, 14, 14, 192)  1728       ['block_6_pad[0][0]']            \n",
      " nv2D)                                                                                            \n",
      "                                                                                                  \n",
      " block_6_depthwise_BN (BatchNor  (None, 14, 14, 192)  768        ['block_6_depthwise[0][0]']      \n",
      " malization)                                                                                      \n",
      "                                                                                                  \n",
      " block_6_depthwise_relu (ReLU)  (None, 14, 14, 192)  0           ['block_6_depthwise_BN[0][0]']   \n",
      "                                                                                                  \n",
      " block_6_project (Conv2D)       (None, 14, 14, 64)   12288       ['block_6_depthwise_relu[0][0]'] \n",
      "                                                                                                  \n",
      " block_6_project_BN (BatchNorma  (None, 14, 14, 64)  256         ['block_6_project[0][0]']        \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " lization)                                                                                        \n",
      "                                                                                                  \n",
      " block_7_expand (Conv2D)        (None, 14, 14, 384)  24576       ['block_6_project_BN[0][0]']     \n",
      "                                                                                                  \n",
      " block_7_expand_BN (BatchNormal  (None, 14, 14, 384)  1536       ['block_7_expand[0][0]']         \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " block_7_expand_relu (ReLU)     (None, 14, 14, 384)  0           ['block_7_expand_BN[0][0]']      \n",
      "                                                                                                  \n",
      " block_7_depthwise (DepthwiseCo  (None, 14, 14, 384)  3456       ['block_7_expand_relu[0][0]']    \n",
      " nv2D)                                                                                            \n",
      "                                                                                                  \n",
      " block_7_depthwise_BN (BatchNor  (None, 14, 14, 384)  1536       ['block_7_depthwise[0][0]']      \n",
      " malization)                                                                                      \n",
      "                                                                                                  \n",
      " block_7_depthwise_relu (ReLU)  (None, 14, 14, 384)  0           ['block_7_depthwise_BN[0][0]']   \n",
      "                                                                                                  \n",
      " block_7_project (Conv2D)       (None, 14, 14, 64)   24576       ['block_7_depthwise_relu[0][0]'] \n",
      "                                                                                                  \n",
      " block_7_project_BN (BatchNorma  (None, 14, 14, 64)  256         ['block_7_project[0][0]']        \n",
      " lization)                                                                                        \n",
      "                                                                                                  \n",
      " block_7_add (Add)              (None, 14, 14, 64)   0           ['block_6_project_BN[0][0]',     \n",
      "                                                                  'block_7_project_BN[0][0]']     \n",
      "                                                                                                  \n",
      " block_8_expand (Conv2D)        (None, 14, 14, 384)  24576       ['block_7_add[0][0]']            \n",
      "                                                                                                  \n",
      " block_8_expand_BN (BatchNormal  (None, 14, 14, 384)  1536       ['block_8_expand[0][0]']         \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " block_8_expand_relu (ReLU)     (None, 14, 14, 384)  0           ['block_8_expand_BN[0][0]']      \n",
      "                                                                                                  \n",
      " block_8_depthwise (DepthwiseCo  (None, 14, 14, 384)  3456       ['block_8_expand_relu[0][0]']    \n",
      " nv2D)                                                                                            \n",
      "                                                                                                  \n",
      " block_8_depthwise_BN (BatchNor  (None, 14, 14, 384)  1536       ['block_8_depthwise[0][0]']      \n",
      " malization)                                                                                      \n",
      "                                                                                                  \n",
      " block_8_depthwise_relu (ReLU)  (None, 14, 14, 384)  0           ['block_8_depthwise_BN[0][0]']   \n",
      "                                                                                                  \n",
      " block_8_project (Conv2D)       (None, 14, 14, 64)   24576       ['block_8_depthwise_relu[0][0]'] \n",
      "                                                                                                  \n",
      " block_8_project_BN (BatchNorma  (None, 14, 14, 64)  256         ['block_8_project[0][0]']        \n",
      " lization)                                                                                        \n",
      "                                                                                                  \n",
      " block_8_add (Add)              (None, 14, 14, 64)   0           ['block_7_add[0][0]',            \n",
      "                                                                  'block_8_project_BN[0][0]']     \n",
      "                                                                                                  \n",
      " block_9_expand (Conv2D)        (None, 14, 14, 384)  24576       ['block_8_add[0][0]']            \n",
      "                                                                                                  \n",
      " block_9_expand_BN (BatchNormal  (None, 14, 14, 384)  1536       ['block_9_expand[0][0]']         \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " block_9_expand_relu (ReLU)     (None, 14, 14, 384)  0           ['block_9_expand_BN[0][0]']      \n",
      "                                                                                                  \n",
      " block_9_depthwise (DepthwiseCo  (None, 14, 14, 384)  3456       ['block_9_expand_relu[0][0]']    \n",
      " nv2D)                                                                                            \n",
      "                                                                                                  \n",
      " block_9_depthwise_BN (BatchNor  (None, 14, 14, 384)  1536       ['block_9_depthwise[0][0]']      \n",
      " malization)                                                                                      \n",
      "                                                                                                  \n",
      " block_9_depthwise_relu (ReLU)  (None, 14, 14, 384)  0           ['block_9_depthwise_BN[0][0]']   \n",
      "                                                                                                  \n",
      " block_9_project (Conv2D)       (None, 14, 14, 64)   24576       ['block_9_depthwise_relu[0][0]'] \n",
      "                                                                                                  \n",
      " block_9_project_BN (BatchNorma  (None, 14, 14, 64)  256         ['block_9_project[0][0]']        \n",
      " lization)                                                                                        \n",
      "                                                                                                  \n",
      " block_9_add (Add)              (None, 14, 14, 64)   0           ['block_8_add[0][0]',            \n",
      "                                                                  'block_9_project_BN[0][0]']     \n",
      "                                                                                                  \n",
      " block_10_expand (Conv2D)       (None, 14, 14, 384)  24576       ['block_9_add[0][0]']            \n",
      "                                                                                                  \n",
      " block_10_expand_BN (BatchNorma  (None, 14, 14, 384)  1536       ['block_10_expand[0][0]']        \n",
      " lization)                                                                                        \n",
      "                                                                                                  \n",
      " block_10_expand_relu (ReLU)    (None, 14, 14, 384)  0           ['block_10_expand_BN[0][0]']     \n",
      "                                                                                                  \n",
      " block_10_depthwise (DepthwiseC  (None, 14, 14, 384)  3456       ['block_10_expand_relu[0][0]']   \n",
      " onv2D)                                                                                           \n",
      "                                                                                                  \n",
      " block_10_depthwise_BN (BatchNo  (None, 14, 14, 384)  1536       ['block_10_depthwise[0][0]']     \n",
      " rmalization)                                                                                     \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                                                                                  \n",
      " block_10_depthwise_relu (ReLU)  (None, 14, 14, 384)  0          ['block_10_depthwise_BN[0][0]']  \n",
      "                                                                                                  \n",
      " block_10_project (Conv2D)      (None, 14, 14, 96)   36864       ['block_10_depthwise_relu[0][0]']\n",
      "                                                                                                  \n",
      " block_10_project_BN (BatchNorm  (None, 14, 14, 96)  384         ['block_10_project[0][0]']       \n",
      " alization)                                                                                       \n",
      "                                                                                                  \n",
      " block_11_expand (Conv2D)       (None, 14, 14, 576)  55296       ['block_10_project_BN[0][0]']    \n",
      "                                                                                                  \n",
      " block_11_expand_BN (BatchNorma  (None, 14, 14, 576)  2304       ['block_11_expand[0][0]']        \n",
      " lization)                                                                                        \n",
      "                                                                                                  \n",
      " block_11_expand_relu (ReLU)    (None, 14, 14, 576)  0           ['block_11_expand_BN[0][0]']     \n",
      "                                                                                                  \n",
      " block_11_depthwise (DepthwiseC  (None, 14, 14, 576)  5184       ['block_11_expand_relu[0][0]']   \n",
      " onv2D)                                                                                           \n",
      "                                                                                                  \n",
      " block_11_depthwise_BN (BatchNo  (None, 14, 14, 576)  2304       ['block_11_depthwise[0][0]']     \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " block_11_depthwise_relu (ReLU)  (None, 14, 14, 576)  0          ['block_11_depthwise_BN[0][0]']  \n",
      "                                                                                                  \n",
      " block_11_project (Conv2D)      (None, 14, 14, 96)   55296       ['block_11_depthwise_relu[0][0]']\n",
      "                                                                                                  \n",
      " block_11_project_BN (BatchNorm  (None, 14, 14, 96)  384         ['block_11_project[0][0]']       \n",
      " alization)                                                                                       \n",
      "                                                                                                  \n",
      " block_11_add (Add)             (None, 14, 14, 96)   0           ['block_10_project_BN[0][0]',    \n",
      "                                                                  'block_11_project_BN[0][0]']    \n",
      "                                                                                                  \n",
      " block_12_expand (Conv2D)       (None, 14, 14, 576)  55296       ['block_11_add[0][0]']           \n",
      "                                                                                                  \n",
      " block_12_expand_BN (BatchNorma  (None, 14, 14, 576)  2304       ['block_12_expand[0][0]']        \n",
      " lization)                                                                                        \n",
      "                                                                                                  \n",
      " block_12_expand_relu (ReLU)    (None, 14, 14, 576)  0           ['block_12_expand_BN[0][0]']     \n",
      "                                                                                                  \n",
      " block_12_depthwise (DepthwiseC  (None, 14, 14, 576)  5184       ['block_12_expand_relu[0][0]']   \n",
      " onv2D)                                                                                           \n",
      "                                                                                                  \n",
      " block_12_depthwise_BN (BatchNo  (None, 14, 14, 576)  2304       ['block_12_depthwise[0][0]']     \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " block_12_depthwise_relu (ReLU)  (None, 14, 14, 576)  0          ['block_12_depthwise_BN[0][0]']  \n",
      "                                                                                                  \n",
      " block_12_project (Conv2D)      (None, 14, 14, 96)   55296       ['block_12_depthwise_relu[0][0]']\n",
      "                                                                                                  \n",
      " block_12_project_BN (BatchNorm  (None, 14, 14, 96)  384         ['block_12_project[0][0]']       \n",
      " alization)                                                                                       \n",
      "                                                                                                  \n",
      " block_12_add (Add)             (None, 14, 14, 96)   0           ['block_11_add[0][0]',           \n",
      "                                                                  'block_12_project_BN[0][0]']    \n",
      "                                                                                                  \n",
      " block_13_expand (Conv2D)       (None, 14, 14, 576)  55296       ['block_12_add[0][0]']           \n",
      "                                                                                                  \n",
      " block_13_expand_BN (BatchNorma  (None, 14, 14, 576)  2304       ['block_13_expand[0][0]']        \n",
      " lization)                                                                                        \n",
      "                                                                                                  \n",
      " block_13_expand_relu (ReLU)    (None, 14, 14, 576)  0           ['block_13_expand_BN[0][0]']     \n",
      "                                                                                                  \n",
      " block_13_pad (ZeroPadding2D)   (None, 15, 15, 576)  0           ['block_13_expand_relu[0][0]']   \n",
      "                                                                                                  \n",
      " block_13_depthwise (DepthwiseC  (None, 7, 7, 576)   5184        ['block_13_pad[0][0]']           \n",
      " onv2D)                                                                                           \n",
      "                                                                                                  \n",
      " block_13_depthwise_BN (BatchNo  (None, 7, 7, 576)   2304        ['block_13_depthwise[0][0]']     \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " block_13_depthwise_relu (ReLU)  (None, 7, 7, 576)   0           ['block_13_depthwise_BN[0][0]']  \n",
      "                                                                                                  \n",
      " block_13_project (Conv2D)      (None, 7, 7, 160)    92160       ['block_13_depthwise_relu[0][0]']\n",
      "                                                                                                  \n",
      " block_13_project_BN (BatchNorm  (None, 7, 7, 160)   640         ['block_13_project[0][0]']       \n",
      " alization)                                                                                       \n",
      "                                                                                                  \n",
      " block_14_expand (Conv2D)       (None, 7, 7, 960)    153600      ['block_13_project_BN[0][0]']    \n",
      "                                                                                                  \n",
      " block_14_expand_BN (BatchNorma  (None, 7, 7, 960)   3840        ['block_14_expand[0][0]']        \n",
      " lization)                                                                                        \n",
      "                                                                                                  \n",
      " block_14_expand_relu (ReLU)    (None, 7, 7, 960)    0           ['block_14_expand_BN[0][0]']     \n",
      "                                                                                                  \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " block_14_depthwise (DepthwiseC  (None, 7, 7, 960)   8640        ['block_14_expand_relu[0][0]']   \n",
      " onv2D)                                                                                           \n",
      "                                                                                                  \n",
      " block_14_depthwise_BN (BatchNo  (None, 7, 7, 960)   3840        ['block_14_depthwise[0][0]']     \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " block_14_depthwise_relu (ReLU)  (None, 7, 7, 960)   0           ['block_14_depthwise_BN[0][0]']  \n",
      "                                                                                                  \n",
      " block_14_project (Conv2D)      (None, 7, 7, 160)    153600      ['block_14_depthwise_relu[0][0]']\n",
      "                                                                                                  \n",
      " block_14_project_BN (BatchNorm  (None, 7, 7, 160)   640         ['block_14_project[0][0]']       \n",
      " alization)                                                                                       \n",
      "                                                                                                  \n",
      " block_14_add (Add)             (None, 7, 7, 160)    0           ['block_13_project_BN[0][0]',    \n",
      "                                                                  'block_14_project_BN[0][0]']    \n",
      "                                                                                                  \n",
      " block_15_expand (Conv2D)       (None, 7, 7, 960)    153600      ['block_14_add[0][0]']           \n",
      "                                                                                                  \n",
      " block_15_expand_BN (BatchNorma  (None, 7, 7, 960)   3840        ['block_15_expand[0][0]']        \n",
      " lization)                                                                                        \n",
      "                                                                                                  \n",
      " block_15_expand_relu (ReLU)    (None, 7, 7, 960)    0           ['block_15_expand_BN[0][0]']     \n",
      "                                                                                                  \n",
      " block_15_depthwise (DepthwiseC  (None, 7, 7, 960)   8640        ['block_15_expand_relu[0][0]']   \n",
      " onv2D)                                                                                           \n",
      "                                                                                                  \n",
      " block_15_depthwise_BN (BatchNo  (None, 7, 7, 960)   3840        ['block_15_depthwise[0][0]']     \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " block_15_depthwise_relu (ReLU)  (None, 7, 7, 960)   0           ['block_15_depthwise_BN[0][0]']  \n",
      "                                                                                                  \n",
      " block_15_project (Conv2D)      (None, 7, 7, 160)    153600      ['block_15_depthwise_relu[0][0]']\n",
      "                                                                                                  \n",
      " block_15_project_BN (BatchNorm  (None, 7, 7, 160)   640         ['block_15_project[0][0]']       \n",
      " alization)                                                                                       \n",
      "                                                                                                  \n",
      " block_15_add (Add)             (None, 7, 7, 160)    0           ['block_14_add[0][0]',           \n",
      "                                                                  'block_15_project_BN[0][0]']    \n",
      "                                                                                                  \n",
      " block_16_expand (Conv2D)       (None, 7, 7, 960)    153600      ['block_15_add[0][0]']           \n",
      "                                                                                                  \n",
      " block_16_expand_BN (BatchNorma  (None, 7, 7, 960)   3840        ['block_16_expand[0][0]']        \n",
      " lization)                                                                                        \n",
      "                                                                                                  \n",
      " block_16_expand_relu (ReLU)    (None, 7, 7, 960)    0           ['block_16_expand_BN[0][0]']     \n",
      "                                                                                                  \n",
      " block_16_depthwise (DepthwiseC  (None, 7, 7, 960)   8640        ['block_16_expand_relu[0][0]']   \n",
      " onv2D)                                                                                           \n",
      "                                                                                                  \n",
      " block_16_depthwise_BN (BatchNo  (None, 7, 7, 960)   3840        ['block_16_depthwise[0][0]']     \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " block_16_depthwise_relu (ReLU)  (None, 7, 7, 960)   0           ['block_16_depthwise_BN[0][0]']  \n",
      "                                                                                                  \n",
      " block_16_project (Conv2D)      (None, 7, 7, 320)    307200      ['block_16_depthwise_relu[0][0]']\n",
      "                                                                                                  \n",
      " block_16_project_BN (BatchNorm  (None, 7, 7, 320)   1280        ['block_16_project[0][0]']       \n",
      " alization)                                                                                       \n",
      "                                                                                                  \n",
      " Conv_1 (Conv2D)                (None, 7, 7, 1280)   409600      ['block_16_project_BN[0][0]']    \n",
      "                                                                                                  \n",
      " Conv_1_bn (BatchNormalization)  (None, 7, 7, 1280)  5120        ['Conv_1[0][0]']                 \n",
      "                                                                                                  \n",
      " out_relu (ReLU)                (None, 7, 7, 1280)   0           ['Conv_1_bn[0][0]']              \n",
      "                                                                                                  \n",
      " global_average_pooling2d (Glob  (None, 1280)        0           ['out_relu[0][0]']               \n",
      " alAveragePooling2D)                                                                              \n",
      "                                                                                                  \n",
      " dense (Dense)                  (None, 2048)         2623488     ['global_average_pooling2d[0][0]'\n",
      "                                                                 ]                                \n",
      "                                                                                                  \n",
      " dropout (Dropout)              (None, 2048)         0           ['dense[0][0]']                  \n",
      "                                                                                                  \n",
      " dense_1 (Dense)                (None, 1024)         2098176     ['dropout[0][0]']                \n",
      "                                                                                                  \n",
      " dropout_1 (Dropout)            (None, 1024)         0           ['dense_1[0][0]']                \n",
      "                                                                                                  \n",
      " dense_2 (Dense)                (None, 2)            2050        ['dropout_1[0][0]']              \n",
      "                                                                                                  \n",
      "==================================================================================================\n",
      "Total params: 6,981,698\n",
      "Trainable params: 0\n",
      "Non-trainable params: 6,981,698\n",
      "__________________________________________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "new_model = tf.keras.models.load_model('FireDetection.pb')\n",
    "\n",
    "new_model.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Tensorflow - Lite"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "id": "C5Uq2z9KphLN"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 52). These functions will not be directly callable after loading.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: /var/folders/dq/th4jrf_53n14t3xrph6gtdjh0000gn/T/tmpxph9hkxs/assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: /var/folders/dq/th4jrf_53n14t3xrph6gtdjh0000gn/T/tmpxph9hkxs/assets\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "7234880"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "converter = tf.lite.TFLiteConverter.from_keras_model(model)\n",
    "converter.optimizations = [tf.lite.Optimize.DEFAULT]\n",
    "tflite_model = converter.convert()\n",
    "open('FireDetection.tflite','wb').write(tflite_model)"
   ]
  }
 ],
 "metadata": {
  "colab": {
   "name": "FireDetection.ipynb",
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
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}