{ "cells": [ { "cell_type": "markdown", "metadata": { "id": "view-in-github", "colab_type": "text" }, "source": [ "\"Open" ] }, { "cell_type": "markdown", "metadata": { "id": "U9rsT-6LVA-S" }, "source": [ "# Classification of Hurricane Damage\n", "\n", "Damage assessment after a natural disaster is a critical step in emergency response efforts. It allows responders to determine the scale of damage, allocate resources efficiently, and identify areas and communities in need of assistance. Damage assessments also help responders understand the degree of structural loss, the number of people displaced who need temporary housing, and the state of natural resources in the area. Overall, accurate and reliable damage assessments are key to informing response to natural disasters.\n", "\n", "Traditionally, damage assessment is done by ground survey which relies on resources that are often limited after a disaster. A physical damage assessment requires a large amount of time, access to transportation systems, and additional resources and logistics to support a team of assessors traveling to the area. However, remote sensing has facilitated more resource efficient assessments following a disaster. Remote sensing tools can now be used to detect damage, predict future damage, and analyze total loss. These tools can use geospatial techniques to identify coordinate locations of real-time imagery to determine immediate needs in exact places. This data can also be used after a disaster event to classify the extent of damage and identify patterns to better prepare communities in the future." ] }, { "cell_type": "markdown", "metadata": { "id": "Y_S8gobtVA-U" }, "source": [ "## Loading Data\n", "\n", "Within the directory there are four folders we're importing:\n", "\n", "**train_another** : the training data; 5000 images of each class\n", "\n", "**validation_another**: the testidation data; 1000 images of each class\n", "\n", "**test_another** : the unbalanced test data; 8000/1000 images of damaged/undamaged classes\n", "\n", "**test** : the balanced test data; 1000 images of each class" ] }, { "cell_type": "markdown", "metadata": { "id": "gIh73cDTVA-V" }, "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "_zxi6qblVA-V" }, "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "import keras as keras\n", "from keras.models import Sequential\n", "from keras.layers import Dense, Dropout\n", "from keras.utils.np_utils import to_categorical\n", "from matplotlib.pyplot import imread, imshow, subplots, show\n", "from sklearn import svm, datasets\n", "from sklearn.model_selection import train_test_split\n", "from sklearn.preprocessing import label_binarize\n", "from sklearn.multiclass import OneVsRestClassifier\n", "from sklearn import metrics" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "RDZClh2AVA-W", "outputId": "b3d4ecce-d1f4-4a7f-cc3f-2fb98fc8728f" }, "outputs": [ { "data": { "text/plain": [ "(128, 128, 3)" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#Testing a single image's shape to determine number of channels to import\n", "import skimage as skimage\n", "import os as os\n", "\n", "tr_path = 'D:/MUSA/MUSASpring/M650_Sensing/data_hurricane/train_another/damage/-93.6141_30.754263.jpeg'\n", "\n", "image_test = skimage.io.imread(tr_path)\n", "\n", "image_test.shape" ] }, { "cell_type": "markdown", "metadata": { "id": "3iA_UkPKVA-X" }, "source": [ "#### Training Set Import" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "9JxtweTzVA-X", "outputId": "52aab40f-f167-4f27-fa7f-0343d5e4bcbc" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Found 10000 files belonging to 2 classes.\n" ] } ], "source": [ "#Since the channels are 3, we can use keras to import into a dataset.\n", "tr_path = 'D:/MUSA/MUSASpring/M650_Sensing/data_hurricane/train_another/'\n", "\n", "#Use Keras to import data\n", "tr_dataset = keras.utils.image_dataset_from_directory(\n", " tr_path,\n", " labels=\"inferred\",\n", " label_mode=\"int\",\n", " class_names= ['no_damage', 'damage'],\n", " color_mode=\"rgb\",\n", " batch_size=32,\n", " image_size=(128, 128),\n", " shuffle=False,\n", " seed=None,\n", " validation_split=None,\n", " subset=None,\n", " interpolation=\"bilinear\",\n", " follow_links=False,\n", " crop_to_aspect_ratio=False,\n", ")\n", "\n", "#Convert keras dataset to numpy array\n", "tr_dataset = tr_dataset.unbatch()\n", "tr_images = np.asarray(list(tr_dataset.map(lambda x, y: x)))\n", "tr_labels = np.asarray(list(tr_dataset.map(lambda x, y: y)))\n" ] }, { "cell_type": "markdown", "metadata": { "id": "B3BYyoVXVA-Y" }, "source": [ "0: No Damage\n", "\n", "1: Damage" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "kbjkhh6wVA-Y", "outputId": "277e79f5-5bfa-400b-8ee3-0d1f113a464c" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0\n" ] }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.imshow(tr_images[0].astype('uint8'))\n", "print(tr_labels[5000])" ] }, { "cell_type": "markdown", "metadata": { "id": "dXdPeIVdVA-Y" }, "source": [ "The above image is in the damage folder as \"-93.55964_30.895018\", so the import is labeling them correctly." ] }, { "cell_type": "markdown", "metadata": { "id": "AmN0g-zsVA-Z" }, "source": [ "#### Validation Set Import" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "Tr9_KhmrVA-Z", "outputId": "c6dbfd5e-67c2-492c-ba40-3e1f7faa1339" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Found 2000 files belonging to 2 classes.\n" ] } ], "source": [ "#Since the channels are 3, we can use keras to import into a dataset.\n", "val_path = 'D:/MUSA/MUSASpring/M650_Sensing/data_hurricane/validation_another/'\n", "\n", "#Use Keras to import data\n", "val_dataset = keras.utils.image_dataset_from_directory(\n", " val_path,\n", " labels=\"inferred\",\n", " label_mode=\"int\",\n", " class_names= ['no_damage', 'damage'],\n", " color_mode=\"rgb\",\n", " batch_size=32,\n", " image_size=(128, 128),\n", " shuffle=False,\n", " seed=None,\n", " validation_split=None,\n", " subset=None,\n", " interpolation=\"bilinear\",\n", " follow_links=False,\n", " crop_to_aspect_ratio=False,\n", ")\n", "\n", "#Convert keras dataset to numpy array\n", "val_dataset = val_dataset.unbatch()\n", "val_images = np.asarray(list(val_dataset.map(lambda x, y: x)))\n", "val_labels = np.asarray(list(val_dataset.map(lambda x, y: y)))" ] }, { "cell_type": "markdown", "metadata": { "id": "0fyKQeEnVA-Z" }, "source": [ "#### Testing Set Import\n", "\n", "There are two test sets for this data, one with imbalanced data (another_test) and one with balanced (test). \n", "\n", "These will be kept for final testing." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "ChpSxF78VA-a", "outputId": "be33639e-9703-47cf-9eab-c0a487aa8059" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Found 2000 files belonging to 2 classes.\n" ] } ], "source": [ "#Since the channels are 3, we can use keras to import into a dataset.\n", "test_path = 'D:/MUSA/MUSASpring/M650_Sensing/data_hurricane/test/'\n", "\n", "#Use Keras to import data\n", "test_dataset = keras.utils.image_dataset_from_directory(\n", " test_path,\n", " labels=\"inferred\",\n", " label_mode=\"int\",\n", " class_names= ['no_damage', 'damage'],\n", " color_mode=\"rgb\",\n", " batch_size=32,\n", " image_size=(128, 128),\n", " shuffle=False,\n", " seed=None,\n", " validation_split=None,\n", " subset=None,\n", " interpolation=\"bilinear\",\n", " follow_links=False,\n", " crop_to_aspect_ratio=False,\n", ")\n", "\n", "#Convert keras dataset to numpy array\n", "test_dataset = test_dataset.unbatch()\n", "test_images = np.asarray(list(test_dataset.map(lambda x, y: x)))\n", "test_labels = np.asarray(list(test_dataset.map(lambda x, y: y)))" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "-DDiE5kyVA-a", "outputId": "609ea499-71fd-4842-947b-b924b56877e6" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Found 9000 files belonging to 2 classes.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Users\\Beeel\\AppData\\Local\\Temp\\ipykernel_29012\\1909265154.py:24: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray.\n", " testPlus_images = np.asarray(list(testPlus_dataset.map(lambda x, y: x)))\n", "C:\\Users\\Beeel\\AppData\\Local\\Temp\\ipykernel_29012\\1909265154.py:25: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray.\n", " testPlus_labels = np.asarray(list(testPlus_dataset.map(lambda x, y: y)))\n" ] } ], "source": [ "#Since the channels are 3, we can use keras to import into a dataset.\n", "testPlus_path = 'D:/MUSA/MUSASpring/M650_Sensing/data_hurricane/test_another/'\n", "\n", "#Use Keras to import data\n", "testPlus_dataset = keras.utils.image_dataset_from_directory(\n", " testPlus_path,\n", " labels=\"inferred\",\n", " label_mode=\"int\",\n", " class_names= ['no_damage', 'damage'],\n", " color_mode=\"rgb\",\n", " batch_size=32,\n", " image_size=(128, 128),\n", " shuffle=False,\n", " seed=None,\n", " validation_split=None,\n", " subset=None,\n", " interpolation=\"bilinear\",\n", " follow_links=False,\n", " crop_to_aspect_ratio=False,\n", ")\n", "\n", "#Convert keras dataset to numpy array\n", "testPlus_plus_dataset = testPlus_dataset.unbatch()\n", "testPlus_images = np.asarray(list(testPlus_dataset.map(lambda x, y: x)))\n", "testPlus_labels = np.asarray(list(testPlus_dataset.map(lambda x, y: y)))" ] }, { "cell_type": "markdown", "metadata": { "id": "TA3WChoyVA-a" }, "source": [] }, { "cell_type": "markdown", "metadata": { "id": "YTL-jbhhVA-a" }, "source": [ "### Preprocessing Images\n", "\n", "We could add more data if we wanted to process via zoom, rotate, etc and add more images?" ] }, { "cell_type": "markdown", "metadata": { "id": "KMAfps4rVA-b" }, "source": [ "## Model 1: CNN\n", "\n", "We will develop our own CNN model using convolutional layers and fully connected layers, while incorporating other layers such as batch normalization, dropout, flattening, and others to help normalize the data" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "TryEqDbWVA-b" }, "outputs": [], "source": [ "#Split train data into train and test\n", "\n", "x_tr_train, x_tr_test, y_tr_train, y_tr_test = train_test_split(tr_images, tr_labels, test_size=0.5, random_state=0)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "M4392Mx2VA-b", "outputId": "09f86c64-f698-4fb0-a75f-7dd531581c4f" }, "outputs": [ { "data": { "text/plain": [ "(5000,)" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "y_tr_test.shape" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "c03e4vaLVA-b" }, "outputs": [], "source": [ "#convert labels to binary class matrices\n", "y_tr_train = to_categorical(y_tr_train)\n", "y_tr_test = to_categorical(y_tr_test)\n", "\n", "val_labels_cat = to_categorical(val_labels)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "D_Wq6hdKVA-c" }, "outputs": [], "source": [ "#Using a data generator to help batch the data\n", "\n", "from keras.utils import Sequence\n", "import numpy as np \n", "\n", "#Taken from https://stackoverflow.com/questions/62916904/failed-copying-input-tensor-from-cpu-to-gpu-in-order-to-run-gatherve-dst-tensor\n", "class DataGenerator(Sequence):\n", " def __init__(self, x_set, y_set, batch_size):\n", " self.x, self.y = x_set, y_set\n", " self.batch_size = batch_size\n", "\n", " def __len__(self):\n", " return int(np.ceil(len(self.x) / float(self.batch_size)))\n", "\n", " def __getitem__(self, idx):\n", " batch_x = self.x[idx * self.batch_size:(idx + 1) * self.batch_size]\n", " batch_y = self.y[idx * self.batch_size:(idx + 1) * self.batch_size]\n", " return batch_x, batch_y\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "wN8aEJ8wVA-c" }, "outputs": [], "source": [ "#Data split from training data\n", "train_tr_gen = DataGenerator(x_tr_train, y_tr_train, 32)\n", "test_tr_gen = DataGenerator(x_tr_test, y_tr_test, 32)\n", "\n", "#Data split from validation data\n", "val_gen = DataGenerator(val_images, val_labels_cat, 32)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "agD6x_N-VA-c", "outputId": "618ee9c1-6c05-4dbe-d7f7-57b915dccb6b" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Model: \"sequential\"\n", "_________________________________________________________________\n", " Layer (type) Output Shape Param # \n", "=================================================================\n", " conv2d (Conv2D) (None, 128, 128, 2) 56 \n", " \n", " max_pooling2d (MaxPooling2D (None, 64, 64, 2) 0 \n", " ) \n", " \n", " dropout (Dropout) (None, 64, 64, 2) 0 \n", " \n", " flatten (Flatten) (None, 8192) 0 \n", " \n", " dense (Dense) (None, 2) 16386 \n", " \n", "=================================================================\n", "Total params: 16,442\n", "Trainable params: 16,442\n", "Non-trainable params: 0\n", "_________________________________________________________________\n" ] }, { "data": { "image/png": "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", "text/plain": [ "" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#Compile model with Conv2D, MaxPooling2D, Dropout, Flatten, and Dense layers\n", "\n", "from keras.layers import Conv2D, MaxPooling2D, Dropout, Flatten, BatchNormalization, Dense\n", "from keras.utils import plot_model\n", "\n", "CNN_1 = Sequential()\n", "CNN_1.add(Conv2D(input_shape=(128,128,3), filters=2, kernel_size=(3, 3), padding = 'same', activation='relu'))\n", "CNN_1.add(MaxPooling2D(pool_size=(2, 2), strides=(2,2)))\n", "CNN_1.add(Dropout(0.25))\n", "CNN_1.add(Flatten())\n", "CNN_1.add(Dense(2, activation='softmax'))\n", "\n", "#summarize model\n", "CNN_1.summary()\n", "\n", "#plot model\n", "plot_model(CNN_1, to_file='model-plot_CNN_1.png', show_shapes=True, show_layer_names=True)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "uYmmpinwVA-d", "outputId": "1aa33ef7-b709-4b4a-c27b-77ed8d3042a5" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Epoch 1/25\n", "157/157 [==============================] - 8s 15ms/step - loss: 11.8859 - accuracy: 0.5666 - val_loss: 1.3104 - val_accuracy: 0.6806\n", "Epoch 2/25\n", "157/157 [==============================] - 2s 12ms/step - loss: 1.0986 - accuracy: 0.6864 - val_loss: 1.1512 - val_accuracy: 0.7324\n", "Epoch 3/25\n", "157/157 [==============================] - 2s 12ms/step - loss: 0.6137 - accuracy: 0.7754 - val_loss: 1.1388 - val_accuracy: 0.7306\n", "Epoch 4/25\n", "157/157 [==============================] - 2s 13ms/step - loss: 0.5015 - accuracy: 0.8026 - val_loss: 1.1733 - val_accuracy: 0.7502\n", "Epoch 5/25\n", "157/157 [==============================] - 2s 13ms/step - loss: 0.4591 - accuracy: 0.8302 - val_loss: 1.2880 - val_accuracy: 0.7716\n", "Epoch 6/25\n", "157/157 [==============================] - 2s 13ms/step - loss: 0.4555 - accuracy: 0.8286 - val_loss: 1.6106 - val_accuracy: 0.7952\n", "Epoch 7/25\n", "157/157 [==============================] - 2s 13ms/step - loss: 0.4202 - accuracy: 0.8562 - val_loss: 1.1282 - val_accuracy: 0.7016\n", "Epoch 8/25\n", "157/157 [==============================] - 2s 13ms/step - loss: 0.3989 - accuracy: 0.8544 - val_loss: 1.3395 - val_accuracy: 0.7722\n", "Epoch 9/25\n", "157/157 [==============================] - 2s 13ms/step - loss: 0.3834 - accuracy: 0.8654 - val_loss: 1.4391 - val_accuracy: 0.7800\n", "Epoch 10/25\n", "157/157 [==============================] - 2s 14ms/step - loss: 0.3641 - accuracy: 0.8696 - val_loss: 1.3654 - val_accuracy: 0.7642\n", "Epoch 11/25\n", "157/157 [==============================] - 3s 16ms/step - loss: 0.3576 - accuracy: 0.8758 - val_loss: 1.4493 - val_accuracy: 0.7798\n", "Epoch 12/25\n", "157/157 [==============================] - 2s 14ms/step - loss: 0.3545 - accuracy: 0.8814 - val_loss: 1.3514 - val_accuracy: 0.7630\n", "Epoch 13/25\n", "157/157 [==============================] - 2s 13ms/step - loss: 0.3307 - accuracy: 0.8912 - val_loss: 1.4576 - val_accuracy: 0.7738\n", "Epoch 14/25\n", "157/157 [==============================] - 2s 14ms/step - loss: 0.3095 - accuracy: 0.8960 - val_loss: 1.4748 - val_accuracy: 0.7722\n", "Epoch 15/25\n", "157/157 [==============================] - 2s 14ms/step - loss: 0.3405 - accuracy: 0.8880 - val_loss: 1.5791 - val_accuracy: 0.7692\n", "Epoch 16/25\n", "157/157 [==============================] - 2s 14ms/step - loss: 0.3153 - accuracy: 0.8980 - val_loss: 1.5197 - val_accuracy: 0.7696\n", "Epoch 17/25\n", "157/157 [==============================] - 2s 13ms/step - loss: 0.3250 - accuracy: 0.8934 - val_loss: 1.5964 - val_accuracy: 0.7776\n", "Epoch 18/25\n", "157/157 [==============================] - 2s 13ms/step - loss: 0.3336 - accuracy: 0.8966 - val_loss: 1.4293 - val_accuracy: 0.7536\n", "Epoch 19/25\n", "157/157 [==============================] - 2s 13ms/step - loss: 0.2934 - accuracy: 0.9010 - val_loss: 1.7426 - val_accuracy: 0.7798\n", "Epoch 20/25\n", "157/157 [==============================] - 2s 13ms/step - loss: 0.2894 - accuracy: 0.9046 - val_loss: 1.6385 - val_accuracy: 0.7784\n", "Epoch 21/25\n", "157/157 [==============================] - 2s 12ms/step - loss: 0.2737 - accuracy: 0.9124 - val_loss: 1.6586 - val_accuracy: 0.7774\n", "Epoch 22/25\n", "157/157 [==============================] - 2s 12ms/step - loss: 0.2845 - accuracy: 0.9090 - val_loss: 1.7883 - val_accuracy: 0.7810\n", "Epoch 23/25\n", "157/157 [==============================] - 2s 12ms/step - loss: 0.2931 - accuracy: 0.9066 - val_loss: 1.6111 - val_accuracy: 0.7788\n", "Epoch 24/25\n", "157/157 [==============================] - 2s 14ms/step - loss: 0.2692 - accuracy: 0.9116 - val_loss: 1.6400 - val_accuracy: 0.7798\n", "Epoch 25/25\n", "157/157 [==============================] - 3s 16ms/step - loss: 0.3027 - accuracy: 0.9076 - val_loss: 1.6000 - val_accuracy: 0.7626\n" ] } ], "source": [ "#compile model\n", "CNN_1.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])\n", "\n", "#fit model\n", "history1 = CNN_1.fit(train_tr_gen, epochs=25, batch_size=16, validation_data=(test_tr_gen))" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "4UdxRpSJVA-d", "outputId": "8d881e91-9580-4e26-b946-914df3dacd46" }, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Test loss: 1.6308714151382446\n", "Test accuracy: 0.7684999704360962\n" ] } ], "source": [ "#Plot both loss and accuracy in subplot\n", "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(15,5))\n", "ax1.plot(history1.history['loss'])\n", "ax1.plot(history1.history['val_loss'])\n", "ax1.set_title('Training & Validation Loss')\n", "ax1.set_ylabel('loss')\n", "ax1.set_xlabel('epoch')\n", "ax1.legend(['train', 'validation'], loc='upper left')\n", "ax2.plot(history1.history['accuracy'])\n", "ax2.plot(history1.history['val_accuracy'])\n", "ax2.set_title('model accuracy')\n", "ax2.set_ylabel('accuracy')\n", "ax2.set_xlabel('epoch')\n", "ax2.legend(['train', 'validation'], loc='upper left')\n", "plt.show()\n", "\n", "#accuracy of model\n", "score1 = CNN_1.evaluate(val_gen, verbose=0)\n", "print('Test loss:', score1[0])\n", "print('Test accuracy:', score1[1])" ] }, { "cell_type": "markdown", "metadata": { "id": "0mXKwYDsVA-d" }, "source": [ "### Improving the model\n", "\n", "This basic model has lower accuracy and overfits to the test data, as you can see in the increasing loss over time for the validation set. We'll try to improve it through more normalization and adding filters to get certain signals." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "RJiWebNuVA-e", "outputId": "d551eedc-e4a1-47ae-c665-9566a10931b5" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Model: \"sequential_1\"\n", "_________________________________________________________________\n", " Layer (type) Output Shape Param # \n", "=================================================================\n", " conv2d_1 (Conv2D) (None, 128, 128, 2) 56 \n", " \n", " batch_normalization (BatchN (None, 128, 128, 2) 8 \n", " ormalization) \n", " \n", " max_pooling2d_1 (MaxPooling (None, 64, 64, 2) 0 \n", " 2D) \n", " \n", " dropout_1 (Dropout) (None, 64, 64, 2) 0 \n", " \n", " conv2d_2 (Conv2D) (None, 64, 64, 4) 76 \n", " \n", " batch_normalization_1 (Batc (None, 64, 64, 4) 16 \n", " hNormalization) \n", " \n", " dropout_2 (Dropout) (None, 64, 64, 4) 0 \n", " \n", " flatten_1 (Flatten) (None, 16384) 0 \n", " \n", " dense_1 (Dense) (None, 2) 32770 \n", " \n", "=================================================================\n", "Total params: 32,926\n", "Trainable params: 32,914\n", "Non-trainable params: 12\n", "_________________________________________________________________\n" ] }, { "data": { "image/png": "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", "text/plain": [ "" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "CNN_2 = Sequential()\n", "CNN_2.add(Conv2D(input_shape=(128,128,3), filters=2, kernel_size=(3, 3), padding = 'same', activation='relu'))\n", "CNN_2.add(BatchNormalization())\n", "CNN_2.add(MaxPooling2D(pool_size=(2, 2))) \n", "CNN_2.add(Dropout(0.25))\n", "CNN_2.add(Conv2D(input_shape=(64,64,3), filters=4, kernel_size=(3, 3), padding = 'same', activation='relu'))\n", "CNN_2.add(BatchNormalization())\n", "CNN_2.add(Dropout(0.25))\n", "CNN_2.add(Flatten())\n", "CNN_2.add(Dense(2, activation='softmax'))\n", "\n", "#summarize model\n", "CNN_2.summary()\n", "\n", "#plot model\n", "plot_model(CNN_2, to_file='model-plot_CNN_2.png', show_shapes=True, show_layer_names=True)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "S_u9-y6cVA-e", "outputId": "1b9a8fa8-1861-4fea-eb80-809275b554a1" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Epoch 1/25\n", "157/157 [==============================] - 3s 16ms/step - loss: 0.5375 - accuracy: 0.7872 - val_loss: 0.5842 - val_accuracy: 0.7648\n", "Epoch 2/25\n", "157/157 [==============================] - 2s 16ms/step - loss: 0.4393 - accuracy: 0.8224 - val_loss: 0.6033 - val_accuracy: 0.7818\n", "Epoch 3/25\n", "157/157 [==============================] - 2s 15ms/step - loss: 0.3772 - accuracy: 0.8516 - val_loss: 0.6539 - val_accuracy: 0.7908\n", "Epoch 4/25\n", "157/157 [==============================] - 2s 15ms/step - loss: 0.3461 - accuracy: 0.8658 - val_loss: 0.6242 - val_accuracy: 0.8020\n", "Epoch 5/25\n", "157/157 [==============================] - 2s 15ms/step - loss: 0.3003 - accuracy: 0.8818 - val_loss: 0.6927 - val_accuracy: 0.7608\n", "Epoch 6/25\n", "157/157 [==============================] - 2s 15ms/step - loss: 0.2779 - accuracy: 0.8976 - val_loss: 0.6409 - val_accuracy: 0.8122\n", "Epoch 7/25\n", "157/157 [==============================] - 2s 15ms/step - loss: 0.2544 - accuracy: 0.9022 - val_loss: 0.6555 - val_accuracy: 0.8038\n", "Epoch 8/25\n", "157/157 [==============================] - 2s 15ms/step - loss: 0.2353 - accuracy: 0.9078 - val_loss: 0.6320 - val_accuracy: 0.8178\n", "Epoch 9/25\n", "157/157 [==============================] - 2s 15ms/step - loss: 0.2093 - accuracy: 0.9220 - val_loss: 0.7508 - val_accuracy: 0.7986\n", "Epoch 10/25\n", "157/157 [==============================] - 2s 15ms/step - loss: 0.2106 - accuracy: 0.9222 - val_loss: 0.7425 - val_accuracy: 0.8146\n", "Epoch 11/25\n", "157/157 [==============================] - 2s 15ms/step - loss: 0.2041 - accuracy: 0.9278 - val_loss: 0.7434 - val_accuracy: 0.8034\n", "Epoch 12/25\n", "157/157 [==============================] - 2s 15ms/step - loss: 0.1770 - accuracy: 0.9354 - val_loss: 0.7097 - val_accuracy: 0.8160\n", "Epoch 13/25\n", "157/157 [==============================] - 2s 15ms/step - loss: 0.1778 - accuracy: 0.9362 - val_loss: 0.6709 - val_accuracy: 0.8246\n", "Epoch 14/25\n", "157/157 [==============================] - 2s 15ms/step - loss: 0.1868 - accuracy: 0.9336 - val_loss: 0.6961 - val_accuracy: 0.8368\n", "Epoch 15/25\n", "157/157 [==============================] - 2s 15ms/step - loss: 0.1756 - accuracy: 0.9402 - val_loss: 0.6748 - val_accuracy: 0.8518\n", "Epoch 16/25\n", "157/157 [==============================] - 3s 16ms/step - loss: 0.1617 - accuracy: 0.9422 - val_loss: 0.7009 - val_accuracy: 0.8576\n", "Epoch 17/25\n", "157/157 [==============================] - 2s 15ms/step - loss: 0.1549 - accuracy: 0.9452 - val_loss: 0.7384 - val_accuracy: 0.8312\n", "Epoch 18/25\n", "157/157 [==============================] - 2s 15ms/step - loss: 0.1466 - accuracy: 0.9432 - val_loss: 0.7026 - val_accuracy: 0.8380\n", "Epoch 19/25\n", "157/157 [==============================] - 2s 16ms/step - loss: 0.1427 - accuracy: 0.9472 - val_loss: 0.7185 - val_accuracy: 0.8364\n", "Epoch 20/25\n", "157/157 [==============================] - 2s 15ms/step - loss: 0.1534 - accuracy: 0.9440 - val_loss: 0.7279 - val_accuracy: 0.8592\n", "Epoch 21/25\n", "157/157 [==============================] - 2s 15ms/step - loss: 0.1263 - accuracy: 0.9564 - val_loss: 0.8118 - val_accuracy: 0.8694\n", "Epoch 22/25\n", "157/157 [==============================] - 2s 15ms/step - loss: 0.1128 - accuracy: 0.9598 - val_loss: 0.7396 - val_accuracy: 0.8432\n", "Epoch 23/25\n", "157/157 [==============================] - 2s 15ms/step - loss: 0.1170 - accuracy: 0.9600 - val_loss: 0.7614 - val_accuracy: 0.8328\n", "Epoch 24/25\n", "157/157 [==============================] - 2s 15ms/step - loss: 0.1270 - accuracy: 0.9562 - val_loss: 0.7810 - val_accuracy: 0.8104\n", "Epoch 25/25\n", "157/157 [==============================] - 2s 15ms/step - loss: 0.1352 - accuracy: 0.9566 - val_loss: 0.7686 - val_accuracy: 0.8274\n" ] } ], "source": [ "#compile model\n", "CNN_2.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])\n", "\n", "#fit model\n", "history2 = CNN_2.fit(train_tr_gen, epochs=25, batch_size=16, validation_data=(test_tr_gen))" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "iy96A4t4VA-e", "outputId": "4347c07a-d048-4a31-befd-f4a9aa04d7db" }, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Test loss: 0.7692603468894958\n", "Test accuracy: 0.8230000138282776\n" ] } ], "source": [ "#Plot both loss and accuracy in subplot\n", "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(15,5))\n", "ax1.plot(history2.history['loss'])\n", "ax1.plot(history2.history['val_loss'])\n", "ax1.set_title('Training & Validation Loss')\n", "ax1.set_ylabel('loss')\n", "ax1.set_xlabel('epoch')\n", "ax1.legend(['train', 'validation'], loc='upper left')\n", "ax2.plot(history2.history['accuracy'])\n", "ax2.plot(history2.history['val_accuracy'])\n", "ax2.set_title('model accuracy')\n", "ax2.set_ylabel('accuracy')\n", "ax2.set_xlabel('epoch')\n", "ax2.legend(['train', 'validation'], loc='upper left')\n", "plt.show()\n", "\n", "#accuracy of model\n", "score2 = CNN_2.evaluate(val_gen, verbose=0)\n", "print('Test loss:', score2[0])\n", "print('Test accuracy:', score2[1])" ] }, { "cell_type": "markdown", "metadata": { "id": "RfM65qREVA-f" }, "source": [ "### Data Augmentation\n", "\n", "Using BatchNormalization() helped reduce the diverging loss of the data sets. Two other methods available to us are data augmentation and weight regularization" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "hV8ltNKUVA-h" }, "outputs": [], "source": [ "from keras.preprocessing.image import ImageDataGenerator\n", "from matplotlib.pyplot import imread, imshow, subplots, show\n", "\n", "#Data augmentation\n", "datagen = ImageDataGenerator(\n", " rotation_range=40,\n", " zoom_range=0.2,\n", " fill_mode='nearest')\n", "\n", "datagen.fit(x_tr_train)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "RROfupTDVA-h", "outputId": "34fcbfbc-e380-4567-d234-fba66ec198a7" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Epoch 1/25\n", "157/157 [==============================] - 19s 121ms/step - loss: 0.4980 - accuracy: 0.8086 - val_loss: 0.5045 - val_accuracy: 0.7888\n", "Epoch 2/25\n", "157/157 [==============================] - 19s 120ms/step - loss: 0.4411 - accuracy: 0.8394 - val_loss: 0.3413 - val_accuracy: 0.8796\n", "Epoch 3/25\n", "157/157 [==============================] - 19s 118ms/step - loss: 0.4358 - accuracy: 0.8270 - val_loss: 0.5517 - val_accuracy: 0.8166\n", "Epoch 4/25\n", "157/157 [==============================] - 18s 117ms/step - loss: 0.4293 - accuracy: 0.8428 - val_loss: 0.3567 - val_accuracy: 0.8570\n", "Epoch 5/25\n", "157/157 [==============================] - 18s 116ms/step - loss: 0.3928 - accuracy: 0.8486 - val_loss: 0.3271 - val_accuracy: 0.8722\n", "Epoch 6/25\n", "157/157 [==============================] - 19s 118ms/step - loss: 0.3999 - accuracy: 0.8396 - val_loss: 0.3170 - val_accuracy: 0.8884\n", "Epoch 7/25\n", "157/157 [==============================] - 19s 119ms/step - loss: 0.3753 - accuracy: 0.8602 - val_loss: 0.3227 - val_accuracy: 0.8888\n", "Epoch 8/25\n", "157/157 [==============================] - 19s 121ms/step - loss: 0.3776 - accuracy: 0.8520 - val_loss: 0.3192 - val_accuracy: 0.8928\n", "Epoch 9/25\n", "157/157 [==============================] - 19s 119ms/step - loss: 0.3831 - accuracy: 0.8514 - val_loss: 0.3879 - val_accuracy: 0.8330\n", "Epoch 10/25\n", "157/157 [==============================] - 19s 120ms/step - loss: 0.3762 - accuracy: 0.8556 - val_loss: 0.3063 - val_accuracy: 0.8972\n", "Epoch 11/25\n", "157/157 [==============================] - 19s 119ms/step - loss: 0.3696 - accuracy: 0.8684 - val_loss: 0.5064 - val_accuracy: 0.8378\n", "Epoch 12/25\n", "157/157 [==============================] - 19s 122ms/step - loss: 0.3729 - accuracy: 0.8598 - val_loss: 0.3200 - val_accuracy: 0.8732\n", "Epoch 13/25\n", "157/157 [==============================] - 19s 119ms/step - loss: 0.3721 - accuracy: 0.8602 - val_loss: 0.3748 - val_accuracy: 0.8362\n", "Epoch 14/25\n", "157/157 [==============================] - 19s 121ms/step - loss: 0.3576 - accuracy: 0.8640 - val_loss: 0.3918 - val_accuracy: 0.8456\n", "Epoch 15/25\n", "157/157 [==============================] - 19s 119ms/step - loss: 0.3528 - accuracy: 0.8700 - val_loss: 0.2832 - val_accuracy: 0.8954\n", "Epoch 16/25\n", "157/157 [==============================] - 19s 119ms/step - loss: 0.3811 - accuracy: 0.8558 - val_loss: 0.3057 - val_accuracy: 0.8930\n", "Epoch 17/25\n", "157/157 [==============================] - 20s 125ms/step - loss: 0.3594 - accuracy: 0.8624 - val_loss: 0.2640 - val_accuracy: 0.8990\n", "Epoch 18/25\n", "157/157 [==============================] - 20s 125ms/step - loss: 0.3593 - accuracy: 0.8636 - val_loss: 0.2603 - val_accuracy: 0.9048\n", "Epoch 19/25\n", "157/157 [==============================] - 19s 122ms/step - loss: 0.3486 - accuracy: 0.8640 - val_loss: 0.3075 - val_accuracy: 0.8964\n", "Epoch 20/25\n", "157/157 [==============================] - 19s 124ms/step - loss: 0.3529 - accuracy: 0.8588 - val_loss: 0.3338 - val_accuracy: 0.8994\n", "Epoch 21/25\n", "157/157 [==============================] - 19s 123ms/step - loss: 0.3375 - accuracy: 0.8720 - val_loss: 0.2749 - val_accuracy: 0.9056\n", "Epoch 22/25\n", "157/157 [==============================] - 19s 119ms/step - loss: 0.3456 - accuracy: 0.8634 - val_loss: 0.2676 - val_accuracy: 0.9024\n", "Epoch 23/25\n", "157/157 [==============================] - 19s 121ms/step - loss: 0.3400 - accuracy: 0.8690 - val_loss: 0.2741 - val_accuracy: 0.8856\n", "Epoch 24/25\n", "157/157 [==============================] - 19s 118ms/step - loss: 0.3501 - accuracy: 0.8648 - val_loss: 0.4772 - val_accuracy: 0.7860\n", "Epoch 25/25\n", "157/157 [==============================] - 19s 120ms/step - loss: 0.3477 - accuracy: 0.8694 - val_loss: 0.2709 - val_accuracy: 0.8908\n" ] } ], "source": [ "#Data and labels from training set into data generator for batching memory\n", "#aug_tr_train = DataGenerator(datagen, y_tr_train, 32)\n", "\n", "#fit model to augmented data\n", "history3 = CNN_2.fit(datagen.flow(x_tr_train, y_tr_train), epochs=25, batch_size=16, validation_data=(test_tr_gen))" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "gVBT6lK4VA-i", "outputId": "1f22e6ab-6359-4f05-fb25-9e9915ab4bad" }, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Test loss: 0.27099061012268066\n", "Test accuracy: 0.8970000147819519\n" ] } ], "source": [ "#Plot both loss and accuracy in subplot\n", "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(15,5))\n", "ax1.plot(history3.history['loss'])\n", "ax1.plot(history3.history['val_loss'])\n", "ax1.set_title('Training & Validation Loss')\n", "ax1.set_ylabel('loss')\n", "ax1.set_xlabel('epoch')\n", "ax1.legend(['train', 'validation'], loc='upper left')\n", "ax2.plot(history3.history['accuracy'])\n", "ax2.plot(history3.history['val_accuracy'])\n", "ax2.set_title('model accuracy')\n", "ax2.set_ylabel('accuracy')\n", "ax2.set_xlabel('epoch')\n", "ax2.legend(['train', 'validation'], loc='upper left')\n", "plt.show()\n", "\n", "#accuracy of model\n", "score3 = CNN_2.evaluate(val_gen, verbose=0)\n", "print('Test loss:', score3[0])\n", "print('Test accuracy:', score3[1])" ] }, { "cell_type": "markdown", "metadata": { "id": "TXf1BJIUVA-i" }, "source": [ "The CNN model started simply with one convolution layer as a benchmark for the data. and performed better than a coin-flip at 70% when tested against the validation set. However, the model is evidently overfit and continues to overfit with more epochs, and the accuracy can be improved. We improved the model's accuracy by adding an additional convolution layer and more filters, and improved its generalizability by adding Batch Normalization layers after each convolution. However, there was still a gap between the training set and the validation set, meaning the model was not generalizing as well as it could. Our most recent step was to add image augmentation to the training set. The images in the training set may be framed differently on average than the ones in the validation set, with the houses at different zoom levels or from certain angles. Adding rotation and zoom augmentations to the image has now made the validation set test perform a couple percentage points better, so the model has been made more generalizable.\n", "\n", "Next step is to improve the overall accuracy by adding more filters, convolutions, or hidden layers." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "4I-bxPaJVA-i", "outputId": "c5ef9370-9fd3-427a-a893-b36fd6b0e5f3" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Model: \"sequential_4\"\n", "_________________________________________________________________\n", " Layer (type) Output Shape Param # \n", "=================================================================\n", " conv2d_8 (Conv2D) (None, 128, 128, 4) 112 \n", " \n", " batch_normalization_7 (Batc (None, 128, 128, 4) 16 \n", " hNormalization) \n", " \n", " max_pooling2d_5 (MaxPooling (None, 64, 64, 4) 0 \n", " 2D) \n", " \n", " dropout_8 (Dropout) (None, 64, 64, 4) 0 \n", " \n", " conv2d_9 (Conv2D) (None, 64, 64, 4) 148 \n", " \n", " batch_normalization_8 (Batc (None, 64, 64, 4) 16 \n", " hNormalization) \n", " \n", " dropout_9 (Dropout) (None, 64, 64, 4) 0 \n", " \n", " flatten_4 (Flatten) (None, 16384) 0 \n", " \n", " dense_8 (Dense) (None, 128) 2097280 \n", " \n", " dense_9 (Dense) (None, 64) 8256 \n", " \n", " dense_10 (Dense) (None, 2) 130 \n", " \n", "=================================================================\n", "Total params: 2,105,958\n", "Trainable params: 2,105,942\n", "Non-trainable params: 16\n", "_________________________________________________________________\n" ] }, { "data": { "image/png": "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", "text/plain": [ "" ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "CNN_3 = Sequential()\n", "CNN_3.add(Conv2D(input_shape=(128,128,3), filters=8, kernel_size=(3, 3), padding = 'same', activation='relu'))\n", "CNN_3.add(BatchNormalization())\n", "CNN_3.add(MaxPooling2D(pool_size=(2, 2))) \n", "CNN_3.add(Dropout(0.25))\n", "CNN_3.add(Conv2D(input_shape=(64,64,3), filters=8, kernel_size=(3, 3), padding = 'same', activation='relu'))\n", "CNN_3.add(BatchNormalization())\n", "CNN_3.add(Dropout(0.25))\n", "CNN_3.add(Flatten())\n", "CNN_3.add(Dense(64, activation='relu'))\n", "CNN_3.add(Dense(2, activation='softmax'))\n", "\n", "#summarize model\n", "CNN_3.summary()\n", "\n", "#plot model\n", "plot_model(CNN_3, to_file='model-plot_CNN_3.png', show_shapes=True, show_layer_names=True)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "Tr9AzhYjVA-i" }, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": { "id": "FqoR839VVA-j" }, "source": [ "## Model 2: Transfer Learning\n", "\n", "Model 2: Transfer Learning with VGG16\n", "Next, we will implement a transfer learning technique and apply a pre-trained model to our dataset. We are using VGG16 here." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "W2HPk1jVVA-j" }, "outputs": [], "source": [ "from keras.applications import VGG16\n", "from keras.layers import Dense, Flatten\n", "from keras.models import Model\n", "from keras.utils import plot_model\n", "\n", "# loading VGG16 model\n", "vgg16 = VGG16(weights='imagenet', include_top=False, input_shape=(128, 128, 3))\n", "\n", "# freezin layers from pre-trained model\n", "for layer in vgg16.layers:\n", " layer.trainable = False\n", "\n", "# adding a few other layers just in case\n", "x = Flatten()(vgg16.output)\n", "x = Dense(256, activation='relu')(x)\n", "x = Dense(128, activation='relu')(x)\n", "predictions = Dense(2, activation='softmax')(x)\n", "\n", "# creating model\n", "model = Model(inputs=vgg16.input, outputs=predictions)\n", "\n", "# compiling model\n", "model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy'])" ] }, { "cell_type": "code", "source": [ "plot_model(model, \n", " show_shapes=True, \n", " show_layer_names=True\n", ")" ], "metadata": { "id": "cyB_GEuYVmpb" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "#fitting the model\n", "history2 = model.fit(\n", " x_tr_train, y_tr_train,\n", " epochs=10, batch_size=16,\n", " validation_data=(x_tr_test, y_tr_test),\n", " verbose=1\n", ")" ], "metadata": { "id": "WgPfuQ4KVmtc" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "#accuracy of model\n", "score1 = model.evaluate(x_tr_test, y_tr_test, verbose=0)\n", "print('Test loss:', score1[0])\n", "print('Test accuracy:', score1[1])\n", "\n", "#Plot both loss and accuracy in subplot\n", "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(15,5))\n", "ax1.plot(history2.history['loss'])\n", "ax1.plot(history2.history['val_loss'])\n", "ax1.set_title('Training & Validation Loss')\n", "ax1.set_ylabel('loss')\n", "ax1.set_xlabel('epoch')\n", "ax1.legend(['train', 'validation'], loc='upper left')\n", "ax2.plot(history2.history['accuracy'])\n", "ax2.plot(history2.history['val_accuracy'])\n", "ax2.set_title('Training & Validation Model Accuracy')\n", "ax2.set_ylabel('accuracy')\n", "ax2.set_xlabel('epoch')\n", "ax2.legend(['train', 'validation'], loc='upper left')\n", "plt.show()" ], "metadata": { "id": "JTMFf46bVmwv" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "y_pred = model.predict(x_tr_test)\n", "y_pred_classes = np.argmax(y_pred, axis=1)\n", "\n", "# get the true class labels for test data\n", "y_true_classes = np.argmax(y_tr_test, axis=1)" ], "metadata": { "id": "BYpa8O9mVmzZ" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "# find an index of a correct prediction\n", "correct_idx1 = np.where((y_pred_classes == 0) & (y_true_classes == 0))[0][0]\n", "correct_idx2 = np.where((y_pred_classes == 1) & (y_true_classes == 1))[0][1]\n", "\n", "# find an index of an incorrect prediction\n", "incorrect_idx1 = np.where((y_pred_classes == 0) & (y_true_classes == 1))[0][0]\n", "incorrect_idx2 = np.where((y_pred_classes == 1) & (y_true_classes == 0))[0][0]\n", "\n", "# plot the correct prediction\n", "plt.imshow(x_tr_test[correct_idx1].astype('uint8'))\n", "plt.title(\"True Label: No Damage | Predicted Label: No Damage\")\n", "plt.show()\n", " \n", "# plot the correct prediction\n", "plt.imshow(x_tr_test[correct_idx2].astype('uint8'))\n", "plt.title(\"True Label: Damage | Predicted Label: Damage\")\n", "plt.show()\n", "\n", "# plot the incorrect prediction\n", "plt.imshow(x_tr_test[incorrect_idx1].astype('uint8'))\n", "plt.title(\"True Label: No Damage | Predicted Label: Damage\")\n", "plt.show()\n", " \n", "# plot the incorrect prediction\n", "plt.imshow(x_tr_test[incorrect_idx2].astype('uint8'))\n", "plt.title(\"True Label: Damage | Predicted Label: No Damage\")\n", "plt.show()" ], "metadata": { "id": "Mpbvf_v-Vm1s" }, "execution_count": null, "outputs": [] }, { "cell_type": "markdown", "source": [ "We also started a transfer learning approach which implements a deep learning VGG16 model. Transfer learning allows us to build high-performance models for image classification by using models that have been previously trained on large dataset. We loaded the VGG16 model via Keras and leveraged the layers from the pre-trained model. We also added additional classification layers on top of the pre-trained mode in hopes of increasing the overall accuracy. So far, this method has been very successful. It has exceptionally high accuracy while running the epochs and an overall test accuracy rate of 0.93. However, we do run the risk of overfitting this model. we will consider different ways to reduce overfitting, including adding more dropout layers or implementing a variety of transformation methods, as we work through the rest of the project." ], "metadata": { "id": "UjiOmoVlVdxQ" } }, { "cell_type": "markdown", "metadata": { "id": "gn1ciOuvVA-j" }, "source": [ "## Model 3: ResNet\n", "\n", "Our final model is a residual neural network, which is an iteration of a convolutional neural network." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "HP5diW0rVA-j" }, "outputs": [], "source": [ "img_width = 128\n", "img_height = 128\n", "num_channels = 3\n", "num_classes = 2\n", "input_shape = 128, 128, 3" ] }, { "cell_type": "code", "source": [ "# Shapes of each label\n", "from keras.utils import to_categorical\n", "tr_y = to_categorical(train_y, num_classes=2)\n", "v_y = to_categorical(val_y, num_classes=2)\n", "te_y = to_categorical(test_y, num_classes=2)\n", "print(\"Shape of train images is: \", train_X.shape)\n", "print(\"Shape of validation images is: \", val_X.shape)\n", "print(\"Shape of test images is: \", test_X.shape)\n", "print(\"Shape of train labels is: \", tr_y.shape)\n", "print(\"Shape of validation labels is: \", v_y.shape)\n", "print(\"Shape of test labels is: \", te_y.shape)" ], "metadata": { "id": "bF-4pFdEWDEj" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "import tensorflow as tf\n", "from tensorflow.keras.layers import Input, Conv2D, MaxPooling2D, BatchNormalization, ReLU, Add, Flatten, Dense\n", "from tensorflow.keras.models import Model\n", "\n", "def resnet_block(input_data, filters, strides=1):\n", " x = Conv2D(filters, kernel_size=3, strides=strides, padding=\"same\")(input_data)\n", " x = BatchNormalization()(x)\n", " x = ReLU()(x)\n", " x = Conv2D(filters, kernel_size=3, strides=1, padding=\"same\")(x)\n", " x = BatchNormalization()(x)\n", "\n", " shortcut = input_data\n", " if strides > 1:\n", " shortcut = Conv2D(filters, kernel_size=1, strides=strides, padding=\"same\")(shortcut)\n", " shortcut = BatchNormalization()(shortcut)\n", "\n", " x = Add()([x, shortcut])\n", " x = ReLU()(x)\n", " return x\n", "\n", "def build_resnet(input_shape, num_classes):\n", " inputs = Input(shape=input_shape)\n", " x = Conv2D(64, kernel_size=7, strides=2, padding=\"same\")(inputs)\n", " x = BatchNormalization()(x)\n", " x = ReLU()(x)\n", " x = MaxPooling2D(pool_size=3, strides=2, padding=\"same\")(x)\n", "\n", " x = resnet_block(x, 64)\n", " x = resnet_block(x, 64)\n", " x = resnet_block(x, 64)\n", "\n", " x = resnet_block(x, 128, strides=2)\n", " x = resnet_block(x, 128)\n", " x = resnet_block(x, 128)\n", "\n", " x = resnet_block(x, 256, strides=2)\n", " x = resnet_block(x, 256)\n", " x = resnet_block(x, 256)\n", "\n", " x = resnet_block(x, 512, strides=2)\n", " x = resnet_block(x, 512)\n", " x = resnet_block(x, 512)\n", "\n", " x = Flatten()(x)\n", " outputs = Dense(num_classes, activation=\"softmax\")(x)\n", "\n", " model = Model(inputs, outputs)\n", " return model\n", "\n", "model = build_resnet(input_shape=(128, 128, 3), num_classes=num_classes)\n", "\n", "model.compile(loss=\"categorical_crossentropy\", optimizer=\"adam\", metrics=[\"accuracy\"])\n", "model.fit(train_X, tr_y, batch_size=32, epochs=10, validation_data=(val_X, v_y))" ], "metadata": { "id": "xZ11ctHZWDHs" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "model = build_resnet(input_shape=(128, 128, 3), num_classes=num_classes)\n" ], "metadata": { "id": "fGhFce_NWGCZ" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "model.compile(loss=\"categorical_crossentropy\", optimizer=\"adam\", metrics=[\"accuracy\"])\n", "model.fit(train_X, tr_y, batch_size=32, epochs=10, validation_data=(val_X, v_y))\n" ], "metadata": { "id": "V2Hd-P3TWGFC" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "# Apply to test data\n", "loss, accuracy = model.evaluate(test_X, te_y)\n", "# Print loss and accuracy scores rounded to 2 decimal places\n", "print(\"Test Loss:\", round(loss,2))\n", "print(\"Test Accuracy:\", round(accuracy,2))" ], "metadata": { "id": "EWIuUF9bWDKW" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "import tensorflow as tf\n", "from tensorflow.keras.layers import Input, Conv2D, MaxPooling2D, BatchNormalization, ReLU, Add, Flatten, Dense\n", "from tensorflow.keras.models import Model\n", "\n", "def resnet_block(input_data, filters, strides=1):\n", " x = Conv2D(filters, kernel_size=3, strides=strides, padding=\"same\")(input_data)\n", " x = BatchNormalization()(x)\n", " x = ReLU()(x)\n", " x = Conv2D(filters, kernel_size=3, strides=1, padding=\"same\")(x)\n", " x = BatchNormalization()(x)\n", "\n", " shortcut = input_data\n", " if strides > 1:\n", " shortcut = Conv2D(filters, kernel_size=1, strides=strides, padding=\"same\")(shortcut)\n", " shortcut = BatchNormalization()(shortcut)\n", "\n", " x = Add()([x, shortcut])\n", " x = ReLU()(x)\n", " return x\n", "\n", "def build_resnet(input_shape, num_classes):\n", " inputs = Input(shape=input_shape)\n", " x = Conv2D(64, kernel_size=7, strides=2, padding=\"same\")(inputs)\n", " x = BatchNormalization()(x)\n", " x = ReLU()(x)\n", " x = MaxPooling2D(pool_size=3, strides=2, padding=\"same\")(x)\n", "\n", " x = resnet_block(x, 64)\n", " x = resnet_block(x, 64)\n", " x = resnet_block(x, 64)\n", "\n", " x = resnet_block(x, 128, strides=2)\n", " x = resnet_block(x, 128)\n", " x = resnet_block(x, 128)\n", "\n", " x = resnet_block(x, 256, strides=2)\n", " x = resnet_block(x, 256)\n", " x = resnet_block(x, 256)\n", "\n", " x = resnet_block(x, 512, strides=2)\n", " x = resnet_block(x, 512)\n", " x = resnet_block(x, 512)\n", "\n", " x = Flatten()(x)\n", " outputs = Dense(num_classes, activation=\"softmax\")(x)\n", "\n", " model = Model(inputs, outputs)\n", " return model\n", "\n", "model = build_resnet(input_shape=(128, 128, 3), num_classes=num_classes)\n", "\n", "model.compile(loss=\"categorical_crossentropy\", optimizer=\"adam\", metrics=[\"accuracy\"])\n", "history = model.fit(train_X, tr_y, batch_size=32, epochs=10, validation_data=(val_X, v_y))" ], "metadata": { "id": "nXd165DOWDMn" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "# Apply to test data\n", "loss, accuracy = model.evaluate(test_X, te_y)\n", "# Print loss and accuracy scores rounded to 2 decimal places\n", "print(\"Test Loss:\", round(loss,2))\n", "print(\"Test Accuracy:\", round(accuracy,2))" ], "metadata": { "id": "YrhJOPHsWVIE" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "\n", "#Plot both loss and accuracy in subplot\n", "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(15,5))\n", "ax1.plot(history.history['loss'])\n", "ax1.plot(history.history['val_loss'])\n", "ax1.set_title('Training & Validation Loss')\n", "ax1.set_ylabel('loss')\n", "ax1.set_xlabel('epoch')\n", "ax1.legend(['train', 'validation'], loc='upper left')\n", "ax2.plot(history.history['accuracy'])\n", "ax2.plot(history.history['val_accuracy'])\n", "ax2.set_title('Training & Validation Model Accuracy')\n", "ax2.set_ylabel('accuracy')\n", "ax2.set_xlabel('epoch')\n", "ax2.legend(['train', 'validation'], loc='upper left')\n", "plt.show()" ], "metadata": { "id": "aeV56AixWVKl" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "from keras.utils import plot_model\n", "plot_model(model, to_file='ResNetmodel.png', show_shapes=True, rankdir='TB', dpi=50)" ], "metadata": { "id": "HIKhpguOWVPi" }, "execution_count": null, "outputs": [] } ], "metadata": { "kernelspec": { "display_name": "remoteSensing", "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": "3.9.16" }, "orig_nbformat": 4, "colab": { "provenance": [], "include_colab_link": true } }, "nbformat": 4, "nbformat_minor": 0 }