From c4be80bc08a03f1fc554d5f125962a908879c09f Mon Sep 17 00:00:00 2001 From: Vedantadlak <94456041+Vedantadlak@users.noreply.github.com> Date: Sun, 5 Jun 2022 20:52:22 +0530 Subject: [PATCH 1/6] Add files via upload --- Assignment 1/211154-Assignment_1.ipynb | 336 +++++++++++++++++++++++++ 1 file changed, 336 insertions(+) create mode 100644 Assignment 1/211154-Assignment_1.ipynb diff --git a/Assignment 1/211154-Assignment_1.ipynb b/Assignment 1/211154-Assignment_1.ipynb new file mode 100644 index 0000000..1cec8ae --- /dev/null +++ b/Assignment 1/211154-Assignment_1.ipynb @@ -0,0 +1,336 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "RB2d1J1f1CF7" + }, + "source": [ + "### **Aim** \n", + "The motive of this assignment is to make predictions using **Linear Regression**. To make sure you truly understand how the underlying algorithm works, you are to implement it from scratch." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "a_S80lf6H4Xv" + }, + "source": [ + "### Generating the dataset \n", + "Run the cell below to create the dataset. It further splits the available data into training and testing. Please do not edit this cell.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": { + "id": "yX0zqXcHIQHP" + }, + "outputs": [], + "source": [ + "from sklearn import datasets\n", + "from sklearn.model_selection import train_test_split\n", + "\n", + "# Generate the data\n", + "X, y = datasets.make_regression(n_samples=100, n_features=5, noise=20, random_state=4)\n", + "\n", + "# Split the data\n", + "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=1234)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Zj4rrRXGJBXy" + }, + "source": [ + "### Visualizing the data \n", + "Use `matplotlib` to visualize the given data." + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": { + "id": "zxfi8dkBJOUi" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 48, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "%matplotlib inline\n", + "# Your code here\n", + "X.shape, y.shape\n", + "flat=X.flatten()\n", + "I=flat[::5]\n", + "II=flat[1::5]\n", + "III=flat[2::5]\n", + "IV=flat[3::5]\n", + "V=flat[4::5]\n", + "\n", + "\n", + "plt.scatter(I,y)\n", + "plt.scatter(II,y)\n", + "plt.scatter(III,y)\n", + "plt.scatter(IV,y)\n", + "plt.scatter(V,y)\n", + "\n", + "\n", + "\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "r7vndSBAJceF" + }, + "source": [ + "You should be able to see the linear relations between `y` and the features in vector `X`." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "b4I9Z3epNvBM" + }, + "source": [ + "### Gradient Descent Review \n", + "1. #### Cost function\n", + "Define the `cost function` to measure the difference between predictions and target outputs. Here, we are working with first degree polynomial, so derivatives are easy to calculate. ( Linear function `y = wx +b` ) \n", + "\n", + "$$Error = \\frac{1}{N}\\sum_{i=1}^N (y_i - \\overline{y}_i)^2 = \\frac{1}{N}\\sum_{i=1}^N (y_i - (x_iw+b))^2 $$ \n", + "\n", + " where `N` is the number of samples \n", + " \n", + "\n", + "\n", + "2. #### Compute the derivative\n", + "$$\\frac{\\delta Error}{\\delta w} = \\frac{2}{N}\\sum_{i=1}^N -x_i(y_i -(m x_i +b )) $$\n", + "$$\\frac{\\delta Error}{\\delta b} = \\frac{2}{N}\\sum_{i=1}^N -(y_i -(m x_i +b )) $$\n", + "3.

Update current parameters

\n", + "$$ w:= w- learning\\_rate \\cdot \\frac{\\delta Error}{\\delta w} $$ \n", + "$$ b:= b- learning\\_rate \\cdot \\frac{\\delta Error}{\\delta b} $$ \n", + "4.

Repeat until it fits good enough

\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "kBtUcOVnJu-I" + }, + "source": [ + "### Model definition\n", + "\n", + "Complete the functions in the class below. Hints provided at appropriate places." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "id": "dGnFNPJx3I28" + }, + "outputs": [], + "source": [ + "import numpy as np\n", + "\n", + "class LinearRegression:\n", + "\n", + " # The __init__ is called when we make any object of our class. Here, you are to specify the default values for \n", + " # Learning Rate, Number of Iterations, Weights and Biases. It doesn't return anything.\n", + " # Hint: Google what a `self pointer` is and figure out how it can be used here.\n", + " def __init__(self, lr=0.001, n_iters=1000,coef_=np.random.randn(5,1),intercept_=0):\n", + " # Your code here\n", + " self.lr = lr\n", + " self.n_iters=1000\n", + " self.coef_ = np.random.random()\n", + " self.intercept_ = np.random.random()\n", + "\n", + " \n", + "\n", + "\n", + " # The following function would be the heart of the model. This is where the training would happen. \n", + " # You're supposed to iterate and keep on updating the weights and biases according to the steps of Gradient Descent.\n", + " def fit(self, X, y):\n", + " # Gradient Descent code goes here\n", + "\n", + " def fit(self, X, y):\n", + " self._X = X \n", + " self._y = y\n", + " \n", + " \n", + " \n", + " \n", + " errors = []\n", + " \n", + " \n", + " for i in range(self.n_iters):\n", + " self.gradient_decend()\n", + " errors.append(self.error())\n", + " return errors\n", + " \n", + " def gradient_decend(self):\n", + " \n", + " d_coef, d_intercept = self.gradient()\n", + " self.coef_ -= d_coef * self.lr\n", + " self.intercept_ -= d_intercept * self.lr\n", + " \n", + " def gradient(self):\n", + " yh = self.predict(self._X) \n", + " \n", + " d_coef = ((yh - self._y) * self._X).mean()\n", + " d_intercept = (yh - self._y).mean()\n", + " \n", + " return d_coef, d_intercept\n", + " \n", + " \n", + " # This function will be called after our model has been trained and we are predicting on unseen data\n", + " # What is our prediction? Just return that\n", + " def predict(self, X):\n", + " # Code goes here\n", + " return X * self.coef_ + self.intercept_\n", + " \n", + " \n", + "\n", + " " + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "EvyInkTKPn7W" + }, + "source": [ + "### Initializing, Training & Predictions" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "id": "nvItUpAkHTiv" + }, + "outputs": [], + "source": [ + "# Now, we make an object of our custom class.\n", + "regressor = LinearRegression() # You may pass the custom parameters or let the default values take it ahead\n", + "\n", + "# Call the fit method on the object to train (pass appropriate part of dataset)\n", + "regressor.fit(X_train, y_train)\n", + "\n", + "\n", + "# Now, let's see our what our model predicts\n", + "predictions = regressor.predict(X_test) # pass appropriate part of dataset" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "tzK6cq8eRD4Q" + }, + "source": [ + "### Evaluate the model \n", + "\n", + "Return [Mean Squared Error](https://en.wikipedia.org/wiki/Mean_squared_error) & [R2 Score](https://www.ncl.ac.uk/webtemplate/ask-assets/external/maths-resources/statistics/regression-and-correlation/coefficient-of-determination-r-squared.html#:~:text=%C2%AFy) from the functions below." + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": { + "id": "WqkrvDzcRF5m" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MSE: 4094.932568975969\n", + "Accuracy: -3980476.886391359\n" + ] + } + ], + "source": [ + " def mean_squared_error(y_true,y_pred):\n", + " # return the mean squared error\n", + " return np.mean(np.square(np.subtract(y_true,y_pred)))\n", + " \n", + "def r2_score(y_true, y_pred):\n", + " # return the r2 score\n", + " return 1-((np.sum(np.square(y_true-y_pred)))/(np.sum(np.square(y_true-(np.mean(y_true))))))\n", + " \n", + "\n", + "mse = mean_squared_error(predictions,y_test) # Pass appropriate parts of dataset\n", + "print(\"MSE:\", mse)\n", + "\n", + "accu = r2_score(predictions,y_test) # Pass appropriate parts of dataset\n", + "print(\"Accuracy:\", accu)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "colab": { + "collapsed_sections": [], + "name": "Copy of CV with TF: Assignment 1.ipynb", + "provenance": [ + { + "file_id": "1lHTeY0ieI9TWcR88yhQV1EwsX7n5PSJq", + "timestamp": 1653960498237 + }, + { + "file_id": "1DG_xMAsAlibZtSw7T_p6dzV8CRejNM9o", + "timestamp": 1653919622477 + } + ] + }, + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "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": "3.10.2" + } + }, + "nbformat": 4, + "nbformat_minor": 1 +} From 0cba626f7f18adc571111ac04ff9db3f6fd59e85 Mon Sep 17 00:00:00 2001 From: Vedantadlak <94456041+Vedantadlak@users.noreply.github.com> Date: Sat, 11 Jun 2022 00:31:05 +0530 Subject: [PATCH 2/6] Rename 211154-Assignment_1.ipynb to A1_211154.ipynb --- Assignment 1/{211154-Assignment_1.ipynb => A1_211154.ipynb} | 0 1 file changed, 0 insertions(+), 0 deletions(-) rename Assignment 1/{211154-Assignment_1.ipynb => A1_211154.ipynb} (100%) diff --git a/Assignment 1/211154-Assignment_1.ipynb b/Assignment 1/A1_211154.ipynb similarity index 100% rename from Assignment 1/211154-Assignment_1.ipynb rename to Assignment 1/A1_211154.ipynb From cb86722577f98fbcc64bf3955eea9c15a26f1fc1 Mon Sep 17 00:00:00 2001 From: Vedantadlak <94456041+Vedantadlak@users.noreply.github.com> Date: Thu, 16 Jun 2022 16:07:59 +0530 Subject: [PATCH 3/6] Add files via upload --- Assignment 2/A2_211154.ipynb | 840 +++++++++++++++++++++++++++++++++++ 1 file changed, 840 insertions(+) create mode 100644 Assignment 2/A2_211154.ipynb diff --git a/Assignment 2/A2_211154.ipynb b/Assignment 2/A2_211154.ipynb new file mode 100644 index 0000000..14cf1de --- /dev/null +++ b/Assignment 2/A2_211154.ipynb @@ -0,0 +1,840 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "UxcaEbrCy1g_" + }, + "source": [ + "# Assigment 2: Deep Learning" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "h2JON-_Oy79w" + }, + "source": [ + "## Generate Dataset\n", + "\n", + "This is the same code from Assignment 1" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "id": "hgpG3WDuypfa" + }, + "outputs": [], + "source": [ + "from sklearn import datasets\n", + "from sklearn.model_selection import train_test_split\n", + "\n", + "# Generate the data\n", + "X, y = datasets.make_regression(n_samples=100, n_features=5, noise=5, random_state=4)\n", + "\n", + "# Split the data\n", + "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=1234)\n", + "X_train, X_val, y_train, y_val = train_test_split(X_train, y_train, test_size=0.2, random_state=1)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "r6it-Rm7zD1Y" + }, + "source": [ + "## Visualize Dataset\n", + "This is the same code from Assignment 1" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "id": "UautPVj1yzaQ" + }, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "# Your code here\n", + "for i in range(1,5):\n", + " plt.scatter(X_train[:,i-1],y_train)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "XMXb9lTyzGHE" + }, + "source": [ + "## Model Definition\n", + "\n", + "Using TensorFlow, build a model with the following definition:\n", + "> Input of shape 5 \\\\\n", + "> Dense of shape 5 \\\\\n", + "> Dense of shape 5 \\\\\n", + "> Dense of shape 1 \\\\\n", + "\n", + "Use Mean Square Error Loss and Stochaistic Gradient Descent (SGD) Optimizer\n", + "\n", + "Use Gradient Decay with appropriate parameters" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "id": "r32N1xK2ziOs" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/100\n", + "2/2 [==============================] - 0s 103ms/step - loss: 11357.2617 - accuracy: 0.0000e+00 - val_loss: 11758.5664 - val_accuracy: 0.0000e+00\n", + "Epoch 2/100\n", + "2/2 [==============================] - 0s 30ms/step - loss: 11354.8926 - accuracy: 0.0000e+00 - val_loss: 11756.9033 - val_accuracy: 0.0000e+00\n", + "Epoch 3/100\n", + "2/2 [==============================] - 0s 23ms/step - loss: 11352.7051 - accuracy: 0.0000e+00 - val_loss: 11755.2324 - val_accuracy: 0.0000e+00\n", + "Epoch 4/100\n", + "2/2 [==============================] - 0s 28ms/step - loss: 11350.2988 - accuracy: 0.0000e+00 - val_loss: 11753.6562 - val_accuracy: 0.0000e+00\n", + "Epoch 5/100\n", + "2/2 [==============================] - 0s 26ms/step - loss: 11348.2832 - accuracy: 0.0000e+00 - val_loss: 11752.0742 - val_accuracy: 0.0000e+00\n", + "Epoch 6/100\n", + "2/2 [==============================] - 0s 24ms/step - loss: 11346.2910 - accuracy: 0.0000e+00 - val_loss: 11750.4756 - val_accuracy: 0.0000e+00\n", + "Epoch 7/100\n", + "2/2 [==============================] - 0s 23ms/step - loss: 11343.8389 - accuracy: 0.0000e+00 - val_loss: 11748.9180 - val_accuracy: 0.0000e+00\n", + "Epoch 8/100\n", + "2/2 [==============================] - 0s 22ms/step - loss: 11341.6338 - accuracy: 0.0000e+00 - val_loss: 11747.3525 - val_accuracy: 0.0000e+00\n", + "Epoch 9/100\n", + "2/2 [==============================] - 0s 22ms/step - loss: 11339.5850 - accuracy: 0.0000e+00 - val_loss: 11745.7725 - val_accuracy: 0.0000e+00\n", + "Epoch 10/100\n", + "2/2 [==============================] - 0s 21ms/step - loss: 11337.3906 - accuracy: 0.0000e+00 - val_loss: 11744.1650 - val_accuracy: 0.0000e+00\n", + "Epoch 11/100\n", + "2/2 [==============================] - 0s 29ms/step - loss: 11335.0869 - accuracy: 0.0000e+00 - val_loss: 11742.5576 - val_accuracy: 0.0000e+00\n", + "Epoch 12/100\n", + "2/2 [==============================] - 0s 31ms/step - loss: 11332.9766 - accuracy: 0.0000e+00 - val_loss: 11740.9248 - val_accuracy: 0.0000e+00\n", + "Epoch 13/100\n", + "2/2 [==============================] - 0s 29ms/step - loss: 11330.7031 - accuracy: 0.0000e+00 - val_loss: 11739.2754 - val_accuracy: 0.0000e+00\n", + "Epoch 14/100\n", + "2/2 [==============================] - 0s 23ms/step - loss: 11328.5195 - accuracy: 0.0000e+00 - val_loss: 11737.5820 - val_accuracy: 0.0000e+00\n", + "Epoch 15/100\n", + "2/2 [==============================] - 0s 22ms/step - loss: 11326.3457 - accuracy: 0.0000e+00 - val_loss: 11735.9092 - val_accuracy: 0.0000e+00\n", + "Epoch 16/100\n", + "2/2 [==============================] - 0s 23ms/step - loss: 11323.9600 - accuracy: 0.0000e+00 - val_loss: 11734.1318 - val_accuracy: 0.0000e+00\n", + "Epoch 17/100\n", + "2/2 [==============================] - 0s 28ms/step - loss: 11321.7686 - accuracy: 0.0000e+00 - val_loss: 11732.3320 - val_accuracy: 0.0000e+00\n", + "Epoch 18/100\n", + "2/2 [==============================] - 0s 24ms/step - loss: 11319.4082 - accuracy: 0.0000e+00 - val_loss: 11730.5264 - val_accuracy: 0.0000e+00\n", + "Epoch 19/100\n", + "2/2 [==============================] - 0s 25ms/step - loss: 11317.2188 - accuracy: 0.0000e+00 - val_loss: 11728.7461 - val_accuracy: 0.0000e+00\n", + "Epoch 20/100\n", + "2/2 [==============================] - 0s 22ms/step - loss: 11315.1484 - accuracy: 0.0000e+00 - val_loss: 11726.9336 - val_accuracy: 0.0000e+00\n", + "Epoch 21/100\n", + "2/2 [==============================] - 0s 22ms/step - loss: 11312.5479 - accuracy: 0.0000e+00 - val_loss: 11725.1553 - val_accuracy: 0.0000e+00\n", + "Epoch 22/100\n", + "2/2 [==============================] - 0s 21ms/step - loss: 11310.2725 - accuracy: 0.0000e+00 - val_loss: 11723.3477 - val_accuracy: 0.0000e+00\n", + "Epoch 23/100\n", + "2/2 [==============================] - 0s 20ms/step - loss: 11307.7695 - accuracy: 0.0000e+00 - val_loss: 11721.5684 - val_accuracy: 0.0000e+00\n", + "Epoch 24/100\n", + "2/2 [==============================] - 0s 28ms/step - loss: 11305.8027 - accuracy: 0.0000e+00 - val_loss: 11719.7070 - val_accuracy: 0.0000e+00\n", + "Epoch 25/100\n", + "2/2 [==============================] - 0s 26ms/step - loss: 11303.5518 - accuracy: 0.0000e+00 - val_loss: 11717.8867 - val_accuracy: 0.0000e+00\n", + "Epoch 26/100\n", + "2/2 [==============================] - 0s 25ms/step - loss: 11301.1455 - accuracy: 0.0000e+00 - val_loss: 11716.0430 - val_accuracy: 0.0000e+00\n", + "Epoch 27/100\n", + "2/2 [==============================] - 0s 26ms/step - loss: 11298.8389 - accuracy: 0.0000e+00 - val_loss: 11714.2158 - val_accuracy: 0.0000e+00\n", + "Epoch 28/100\n", + "2/2 [==============================] - 0s 41ms/step - loss: 11296.7832 - accuracy: 0.0000e+00 - val_loss: 11712.2793 - val_accuracy: 0.0000e+00\n", + "Epoch 29/100\n", + "2/2 [==============================] - 0s 44ms/step - loss: 11294.3545 - accuracy: 0.0000e+00 - val_loss: 11710.3809 - val_accuracy: 0.0000e+00\n", + "Epoch 30/100\n", + "2/2 [==============================] - 0s 43ms/step - loss: 11292.0381 - accuracy: 0.0000e+00 - val_loss: 11708.4541 - val_accuracy: 0.0000e+00\n", + "Epoch 31/100\n", + "2/2 [==============================] - 0s 50ms/step - loss: 11289.8086 - accuracy: 0.0000e+00 - val_loss: 11706.5469 - val_accuracy: 0.0000e+00\n", + "Epoch 32/100\n", + "2/2 [==============================] - 0s 47ms/step - loss: 11287.4658 - accuracy: 0.0000e+00 - val_loss: 11704.6562 - val_accuracy: 0.0000e+00\n", + "Epoch 33/100\n", + "2/2 [==============================] - 0s 37ms/step - loss: 11285.0576 - accuracy: 0.0000e+00 - val_loss: 11702.7168 - val_accuracy: 0.0000e+00\n", + "Epoch 34/100\n", + "2/2 [==============================] - 0s 38ms/step - loss: 11282.4092 - accuracy: 0.0000e+00 - val_loss: 11700.7930 - val_accuracy: 0.0000e+00\n", + "Epoch 35/100\n", + "2/2 [==============================] - 0s 46ms/step - loss: 11280.2363 - accuracy: 0.0000e+00 - val_loss: 11698.8359 - val_accuracy: 0.0000e+00\n", + "Epoch 36/100\n", + "2/2 [==============================] - 0s 30ms/step - loss: 11277.8418 - accuracy: 0.0000e+00 - val_loss: 11696.8174 - val_accuracy: 0.0000e+00\n", + "Epoch 37/100\n", + "2/2 [==============================] - 0s 23ms/step - loss: 11275.2012 - accuracy: 0.0000e+00 - val_loss: 11694.8311 - val_accuracy: 0.0000e+00\n", + "Epoch 38/100\n", + "2/2 [==============================] - 0s 19ms/step - loss: 11272.7305 - accuracy: 0.0000e+00 - val_loss: 11692.8340 - val_accuracy: 0.0000e+00\n", + "Epoch 39/100\n", + "2/2 [==============================] - 0s 20ms/step - loss: 11270.2227 - accuracy: 0.0000e+00 - val_loss: 11690.7461 - val_accuracy: 0.0000e+00\n", + "Epoch 40/100\n", + "2/2 [==============================] - 0s 22ms/step - loss: 11267.9434 - accuracy: 0.0000e+00 - val_loss: 11688.6221 - val_accuracy: 0.0000e+00\n", + "Epoch 41/100\n", + "2/2 [==============================] - 0s 19ms/step - loss: 11265.3096 - accuracy: 0.0000e+00 - val_loss: 11686.5146 - val_accuracy: 0.0000e+00\n", + "Epoch 42/100\n", + "2/2 [==============================] - 0s 19ms/step - loss: 11262.5527 - accuracy: 0.0000e+00 - val_loss: 11684.3633 - val_accuracy: 0.0000e+00\n", + "Epoch 43/100\n", + "2/2 [==============================] - 0s 20ms/step - loss: 11259.9287 - accuracy: 0.0000e+00 - val_loss: 11682.1865 - val_accuracy: 0.0000e+00\n", + "Epoch 44/100\n", + "2/2 [==============================] - 0s 19ms/step - loss: 11257.2637 - accuracy: 0.0000e+00 - val_loss: 11679.9854 - val_accuracy: 0.0000e+00\n", + "Epoch 45/100\n", + "2/2 [==============================] - 0s 18ms/step - loss: 11254.7871 - accuracy: 0.0000e+00 - val_loss: 11677.6973 - val_accuracy: 0.0000e+00\n", + "Epoch 46/100\n", + "2/2 [==============================] - 0s 18ms/step - loss: 11251.6729 - accuracy: 0.0000e+00 - val_loss: 11675.4473 - val_accuracy: 0.0000e+00\n", + "Epoch 47/100\n", + "2/2 [==============================] - 0s 19ms/step - loss: 11249.0820 - accuracy: 0.0000e+00 - val_loss: 11673.1680 - val_accuracy: 0.0000e+00\n", + "Epoch 48/100\n", + "2/2 [==============================] - 0s 19ms/step - loss: 11246.3262 - accuracy: 0.0000e+00 - val_loss: 11670.8262 - val_accuracy: 0.0000e+00\n", + "Epoch 49/100\n", + "2/2 [==============================] - 0s 19ms/step - loss: 11243.5098 - accuracy: 0.0000e+00 - val_loss: 11668.4580 - val_accuracy: 0.0000e+00\n", + "Epoch 50/100\n", + "2/2 [==============================] - 0s 18ms/step - loss: 11240.8535 - accuracy: 0.0000e+00 - val_loss: 11666.0430 - val_accuracy: 0.0000e+00\n", + "Epoch 51/100\n", + "2/2 [==============================] - 0s 18ms/step - loss: 11237.9043 - accuracy: 0.0000e+00 - val_loss: 11663.6113 - val_accuracy: 0.0000e+00\n", + "Epoch 52/100\n", + "2/2 [==============================] - 0s 18ms/step - loss: 11234.6357 - accuracy: 0.0000e+00 - val_loss: 11661.2256 - val_accuracy: 0.0000e+00\n", + "Epoch 53/100\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2/2 [==============================] - 0s 21ms/step - loss: 11231.8164 - accuracy: 0.0000e+00 - val_loss: 11658.7715 - val_accuracy: 0.0000e+00\n", + "Epoch 54/100\n", + "2/2 [==============================] - 0s 29ms/step - loss: 11229.0938 - accuracy: 0.0000e+00 - val_loss: 11656.2324 - val_accuracy: 0.0000e+00\n", + "Epoch 55/100\n", + "2/2 [==============================] - 0s 34ms/step - loss: 11225.9414 - accuracy: 0.0000e+00 - val_loss: 11653.7129 - val_accuracy: 0.0000e+00\n", + "Epoch 56/100\n", + "2/2 [==============================] - 0s 39ms/step - loss: 11222.8398 - accuracy: 0.0000e+00 - val_loss: 11651.2070 - val_accuracy: 0.0000e+00\n", + "Epoch 57/100\n", + "2/2 [==============================] - 0s 24ms/step - loss: 11219.9473 - accuracy: 0.0000e+00 - val_loss: 11648.5781 - val_accuracy: 0.0000e+00\n", + "Epoch 58/100\n", + "2/2 [==============================] - 0s 19ms/step - loss: 11216.6191 - accuracy: 0.0000e+00 - val_loss: 11645.9727 - val_accuracy: 0.0000e+00\n", + "Epoch 59/100\n", + "2/2 [==============================] - 0s 19ms/step - loss: 11213.4326 - accuracy: 0.0000e+00 - val_loss: 11643.4033 - val_accuracy: 0.0000e+00\n", + "Epoch 60/100\n", + "2/2 [==============================] - 0s 21ms/step - loss: 11210.4160 - accuracy: 0.0000e+00 - val_loss: 11640.6904 - val_accuracy: 0.0000e+00\n", + "Epoch 61/100\n", + "2/2 [==============================] - 0s 23ms/step - loss: 11207.0049 - accuracy: 0.0000e+00 - val_loss: 11637.9346 - val_accuracy: 0.0000e+00\n", + "Epoch 62/100\n", + "2/2 [==============================] - 0s 20ms/step - loss: 11203.7617 - accuracy: 0.0000e+00 - val_loss: 11635.1201 - val_accuracy: 0.0000e+00\n", + "Epoch 63/100\n", + "2/2 [==============================] - 0s 19ms/step - loss: 11200.3779 - accuracy: 0.0000e+00 - val_loss: 11632.3057 - val_accuracy: 0.0000e+00\n", + "Epoch 64/100\n", + "2/2 [==============================] - 0s 18ms/step - loss: 11197.1123 - accuracy: 0.0000e+00 - val_loss: 11629.3701 - val_accuracy: 0.0000e+00\n", + "Epoch 65/100\n", + "2/2 [==============================] - 0s 25ms/step - loss: 11193.4033 - accuracy: 0.0000e+00 - val_loss: 11626.4854 - val_accuracy: 0.0000e+00\n", + "Epoch 66/100\n", + "2/2 [==============================] - 0s 19ms/step - loss: 11190.2051 - accuracy: 0.0000e+00 - val_loss: 11623.4736 - val_accuracy: 0.0000e+00\n", + "Epoch 67/100\n", + "2/2 [==============================] - 0s 20ms/step - loss: 11186.4121 - accuracy: 0.0000e+00 - val_loss: 11620.4180 - val_accuracy: 0.0000e+00\n", + "Epoch 68/100\n", + "2/2 [==============================] - 0s 20ms/step - loss: 11182.8867 - accuracy: 0.0000e+00 - val_loss: 11617.2793 - val_accuracy: 0.0000e+00\n", + "Epoch 69/100\n", + "2/2 [==============================] - 0s 19ms/step - loss: 11179.1182 - accuracy: 0.0000e+00 - val_loss: 11614.1016 - val_accuracy: 0.0000e+00\n", + "Epoch 70/100\n", + "2/2 [==============================] - 0s 19ms/step - loss: 11175.3984 - accuracy: 0.0000e+00 - val_loss: 11610.9365 - val_accuracy: 0.0000e+00\n", + "Epoch 71/100\n", + "2/2 [==============================] - 0s 21ms/step - loss: 11171.6406 - accuracy: 0.0000e+00 - val_loss: 11607.6738 - val_accuracy: 0.0000e+00\n", + "Epoch 72/100\n", + "2/2 [==============================] - 0s 20ms/step - loss: 11167.8398 - accuracy: 0.0000e+00 - val_loss: 11604.3906 - val_accuracy: 0.0000e+00\n", + "Epoch 73/100\n", + "2/2 [==============================] - 0s 19ms/step - loss: 11163.6562 - accuracy: 0.0000e+00 - val_loss: 11601.0947 - val_accuracy: 0.0000e+00\n", + "Epoch 74/100\n", + "2/2 [==============================] - 0s 21ms/step - loss: 11159.8789 - accuracy: 0.0000e+00 - val_loss: 11597.7949 - val_accuracy: 0.0000e+00\n", + "Epoch 75/100\n", + "2/2 [==============================] - 0s 21ms/step - loss: 11155.8135 - accuracy: 0.0000e+00 - val_loss: 11594.4629 - val_accuracy: 0.0000e+00\n", + "Epoch 76/100\n", + "2/2 [==============================] - 0s 20ms/step - loss: 11152.2344 - accuracy: 0.0000e+00 - val_loss: 11590.9805 - val_accuracy: 0.0000e+00\n", + "Epoch 77/100\n", + "2/2 [==============================] - 0s 20ms/step - loss: 11147.8457 - accuracy: 0.0000e+00 - val_loss: 11587.3213 - val_accuracy: 0.0000e+00\n", + "Epoch 78/100\n", + "2/2 [==============================] - 0s 20ms/step - loss: 11143.7402 - accuracy: 0.0000e+00 - val_loss: 11583.6064 - val_accuracy: 0.0000e+00\n", + "Epoch 79/100\n", + "2/2 [==============================] - 0s 21ms/step - loss: 11139.7041 - accuracy: 0.0000e+00 - val_loss: 11579.8594 - val_accuracy: 0.0000e+00\n", + "Epoch 80/100\n", + "2/2 [==============================] - 0s 21ms/step - loss: 11134.9502 - accuracy: 0.0000e+00 - val_loss: 11576.1719 - val_accuracy: 0.0000e+00\n", + "Epoch 81/100\n", + "2/2 [==============================] - 0s 19ms/step - loss: 11130.9062 - accuracy: 0.0000e+00 - val_loss: 11572.3262 - val_accuracy: 0.0000e+00\n", + "Epoch 82/100\n", + "2/2 [==============================] - 0s 20ms/step - loss: 11126.4531 - accuracy: 0.0000e+00 - val_loss: 11568.4941 - val_accuracy: 0.0000e+00\n", + "Epoch 83/100\n", + "2/2 [==============================] - 0s 19ms/step - loss: 11122.1113 - accuracy: 0.0000e+00 - val_loss: 11564.6006 - val_accuracy: 0.0000e+00\n", + "Epoch 84/100\n", + "2/2 [==============================] - 0s 22ms/step - loss: 11117.9277 - accuracy: 0.0000e+00 - val_loss: 11560.5898 - val_accuracy: 0.0000e+00\n", + "Epoch 85/100\n", + "2/2 [==============================] - 0s 20ms/step - loss: 11112.9297 - accuracy: 0.0000e+00 - val_loss: 11556.6396 - val_accuracy: 0.0000e+00\n", + "Epoch 86/100\n", + "2/2 [==============================] - 0s 19ms/step - loss: 11108.9258 - accuracy: 0.0000e+00 - val_loss: 11552.5459 - val_accuracy: 0.0000e+00\n", + "Epoch 87/100\n", + "2/2 [==============================] - 0s 21ms/step - loss: 11104.0625 - accuracy: 0.0000e+00 - val_loss: 11548.4580 - val_accuracy: 0.0000e+00\n", + "Epoch 88/100\n", + "2/2 [==============================] - 0s 18ms/step - loss: 11099.1934 - accuracy: 0.0000e+00 - val_loss: 11544.4121 - val_accuracy: 0.0000e+00\n", + "Epoch 89/100\n", + "2/2 [==============================] - 0s 18ms/step - loss: 11094.5791 - accuracy: 0.0000e+00 - val_loss: 11540.2832 - val_accuracy: 0.0000e+00\n", + "Epoch 90/100\n", + "2/2 [==============================] - 0s 18ms/step - loss: 11090.0947 - accuracy: 0.0000e+00 - val_loss: 11536.0137 - val_accuracy: 0.0000e+00\n", + "Epoch 91/100\n", + "2/2 [==============================] - 0s 19ms/step - loss: 11085.0840 - accuracy: 0.0000e+00 - val_loss: 11531.7539 - val_accuracy: 0.0000e+00\n", + "Epoch 92/100\n", + "2/2 [==============================] - 0s 18ms/step - loss: 11080.1943 - accuracy: 0.0000e+00 - val_loss: 11527.4795 - val_accuracy: 0.0000e+00\n", + "Epoch 93/100\n", + "2/2 [==============================] - 0s 18ms/step - loss: 11075.2861 - accuracy: 0.0000e+00 - val_loss: 11523.1367 - val_accuracy: 0.0000e+00\n", + "Epoch 94/100\n", + "2/2 [==============================] - 0s 19ms/step - loss: 11070.2969 - accuracy: 0.0000e+00 - val_loss: 11518.7578 - val_accuracy: 0.0000e+00\n", + "Epoch 95/100\n", + "2/2 [==============================] - 0s 20ms/step - loss: 11065.1328 - accuracy: 0.0000e+00 - val_loss: 11514.3389 - val_accuracy: 0.0000e+00\n", + "Epoch 96/100\n", + "2/2 [==============================] - 0s 18ms/step - loss: 11060.0713 - accuracy: 0.0000e+00 - val_loss: 11509.8438 - val_accuracy: 0.0000e+00\n", + "Epoch 97/100\n", + "2/2 [==============================] - 0s 20ms/step - loss: 11054.4766 - accuracy: 0.0000e+00 - val_loss: 11505.4502 - val_accuracy: 0.0000e+00\n", + "Epoch 98/100\n", + "2/2 [==============================] - 0s 19ms/step - loss: 11049.6338 - accuracy: 0.0000e+00 - val_loss: 11500.8672 - val_accuracy: 0.0000e+00\n", + "Epoch 99/100\n", + "2/2 [==============================] - 0s 19ms/step - loss: 11044.6113 - accuracy: 0.0000e+00 - val_loss: 11496.2168 - val_accuracy: 0.0000e+00\n", + "Epoch 100/100\n", + "2/2 [==============================] - 0s 20ms/step - loss: 11038.7832 - accuracy: 0.0000e+00 - val_loss: 11491.5762 - val_accuracy: 0.0000e+00\n" + ] + } + ], + "source": [ + "import tensorflow as tf\n", + "import keras\n", + "\n", + "# Your code here\n", + "model = keras.Sequential([\n", + " keras.layers.Flatten(input_shape=(5,)),\n", + " keras.layers.Dense(5, activation=tf.nn.relu),\n", + "\tkeras.layers.Dense(5, activation=tf.nn.relu),\n", + " keras.layers.Dense(1),\n", + "])\n", + "\n", + "model.compile(optimizer='adam',\n", + " loss='mse',\n", + " metrics=['accuracy'])\n", + "history = model.fit(X_train, y_train, epochs=100, validation_data=(X_val, y_val))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "jmeP6vt3z0oA" + }, + "source": [ + "## Plot Loss\n", + "\n", + "Using matplotlib visualise how the loss (both validation and training) is changing, use this information to retrain the model with appropriate parameters.
We ideally want the loss to be constant over the last few iterations." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "id": "RQTNqPHm0mOi" + }, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'history' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)", + "Input \u001b[1;32mIn [4]\u001b[0m, in \u001b[0;36m\u001b[1;34m\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[38;5;66;03m# Your code here\u001b[39;00m\n\u001b[1;32m----> 2\u001b[0m loss_train \u001b[38;5;241m=\u001b[39m \u001b[43mhistory\u001b[49m\u001b[38;5;241m.\u001b[39mhistory[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mloss\u001b[39m\u001b[38;5;124m'\u001b[39m]\n\u001b[0;32m 3\u001b[0m loss_val \u001b[38;5;241m=\u001b[39m history\u001b[38;5;241m.\u001b[39mhistory[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mval_loss\u001b[39m\u001b[38;5;124m'\u001b[39m]\n\u001b[0;32m 4\u001b[0m epochs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mrange\u001b[39m(\u001b[38;5;241m1\u001b[39m,\u001b[38;5;241m101\u001b[39m)\n", + "\u001b[1;31mNameError\u001b[0m: name 'history' is not defined" + ] + } + ], + "source": [ + "# Your code here\n", + "loss_train = history.history['loss']\n", + "loss_val = history.history['val_loss']\n", + "epochs = range(1,101)\n", + "plt.plot(epochs, loss_train, 'g', label='Training loss')\n", + "plt.plot(epochs, loss_val, 'b', label='validation loss')\n", + "plt.title('Training and Validation loss')\n", + "plt.xlabel('Epochs')\n", + "plt.ylabel('Loss')\n", + "plt.legend()\n", + "plt.show()\n", + "\n", + " " + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "IVrR_vXA7kOt" + }, + "source": [ + "## Evaluation Metrics\n", + "Use the R2 Score function implemented in the first assignment to evaluate the performance of the model." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "id": "-lOHpD8-7ggm" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1/1 [==============================] - 0s 55ms/step\n" + ] + }, + { + "data": { + "text/plain": [ + "-70504.31776374676" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Insert the function for R2 Score\n", + "import numpy as np\n", + "def r2_score(y_true, y_pred):\n", + " # return the r2 score\n", + " return 1-((np.sum(np.square(y_true-y_pred)))/(np.sum(np.square(y_true-(np.mean(y_true))))))\n", + "predictions= model.predict(X_test)\n", + "r2=r2_score(predictions, y_test)\n", + "r2" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "CHqzF1OU0pBg" + }, + "source": [ + "## Your own custom model\n", + "Build a custom model of your own choice.
\n", + "Describe it in detail in Markdown/Latex in the cell below.
\n", + "Visualise the loss, as before." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "jF8oTUqq0y0g" + }, + "source": [ + "Your text here" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "id": "1XOk5hJu0oSQ" + }, + "outputs": [], + "source": [ + "# Your code here" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "id": "aS0ROZa402Lo" + }, + "outputs": [], + "source": [ + "import pandas as pd\n", + "data = pd.read_csv(r'C:\\Users\\VEDANT ADLAK\\CODING\\Power.csv')\n", + "x = data.iloc[:, :-1].values\n", + "Y = data.iloc[:, -1].values" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "x_train, x_test, Y_train, Y_test = train_test_split(x, Y, test_size=0.2, random_state=1234)\n", + "x_train, x_val, Y_train, Y_val = train_test_split(x_train, Y_train, test_size=0.2, random_state=1)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.preprocessing import StandardScaler\n", + "sc = StandardScaler()\n", + "x_train = sc.fit_transform(x_train)\n", + "x_test = sc.transform(x_test)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "ann = tf.keras.models.Sequential()\n", + "ann.add(tf.keras.layers.Dense(units=6, activation = 'relu'))\n", + "ann.add(tf.keras.layers.Dense(units=6, activation = 'relu'))\n", + "ann.add(tf.keras.layers.Dense(units=6, activation = 'relu'))\n", + "ann.add(tf.keras.layers.Dense(units=1))" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "ann.compile(optimizer='adam', loss='mean_squared_error')" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/100\n", + "192/192 [==============================] - 1s 1ms/step - loss: 205502.0625 - val_loss: 1055491.3750\n", + "Epoch 2/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 190986.4688 - val_loss: 217513104.0000\n", + "Epoch 3/100\n", + "192/192 [==============================] - 0s 2ms/step - loss: 118311.9766 - val_loss: 4483321856.0000\n", + "Epoch 4/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 34966.2695 - val_loss: 7665159680.0000\n", + "Epoch 5/100\n", + "192/192 [==============================] - 0s 2ms/step - loss: 14791.5361 - val_loss: 5248251904.0000\n", + "Epoch 6/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 10338.5312 - val_loss: 4176272384.0000\n", + "Epoch 7/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 7680.7041 - val_loss: 3463756800.0000\n", + "Epoch 8/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 5623.4736 - val_loss: 2978657280.0000\n", + "Epoch 9/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 4070.7275 - val_loss: 2693101312.0000\n", + "Epoch 10/100\n", + "192/192 [==============================] - 0s 989us/step - loss: 2931.8125 - val_loss: 2515322112.0000\n", + "Epoch 11/100\n", + "192/192 [==============================] - 0s 985us/step - loss: 2108.7588 - val_loss: 2322741760.0000\n", + "Epoch 12/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 1530.5260 - val_loss: 2165274624.0000\n", + "Epoch 13/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 1126.7343 - val_loss: 1982140288.0000\n", + "Epoch 14/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 837.6551 - val_loss: 1764351872.0000\n", + "Epoch 15/100\n", + "192/192 [==============================] - 0s 990us/step - loss: 628.0771 - val_loss: 1593813888.0000\n", + "Epoch 16/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 478.0287 - val_loss: 1440141696.0000\n", + "Epoch 17/100\n", + "192/192 [==============================] - 0s 2ms/step - loss: 368.2716 - val_loss: 1276639232.0000\n", + "Epoch 18/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 286.9301 - val_loss: 1158568064.0000\n", + "Epoch 19/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 224.9409 - val_loss: 1064603776.0000\n", + "Epoch 20/100\n", + "192/192 [==============================] - 0s 995us/step - loss: 178.4216 - val_loss: 969033536.0000\n", + "Epoch 21/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 142.7281 - val_loss: 904992128.0000\n", + "Epoch 22/100\n", + "192/192 [==============================] - 0s 989us/step - loss: 114.8841 - val_loss: 867124608.0000\n", + "Epoch 23/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 93.3930 - val_loss: 839956288.0000\n", + "Epoch 24/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 76.0847 - val_loss: 825296448.0000\n", + "Epoch 25/100\n", + "192/192 [==============================] - 0s 995us/step - loss: 62.7940 - val_loss: 808421952.0000\n", + "Epoch 26/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 52.6008 - val_loss: 790727296.0000\n", + "Epoch 27/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 44.6540 - val_loss: 779986240.0000\n", + "Epoch 28/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 38.8009 - val_loss: 764706560.0000\n", + "Epoch 29/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 34.3965 - val_loss: 750182848.0000\n", + "Epoch 30/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 31.1811 - val_loss: 723574272.0000\n", + "Epoch 31/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 28.5572 - val_loss: 713040000.0000\n", + "Epoch 32/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 26.9162 - val_loss: 699773568.0000\n", + "Epoch 33/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 25.5039 - val_loss: 689914880.0000\n", + "Epoch 34/100\n", + "192/192 [==============================] - 0s 994us/step - loss: 24.5436 - val_loss: 675314944.0000\n", + "Epoch 35/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 23.8607 - val_loss: 661008960.0000\n", + "Epoch 36/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 23.4081 - val_loss: 645466560.0000\n", + "Epoch 37/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 23.0349 - val_loss: 636793216.0000\n", + "Epoch 38/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 22.5760 - val_loss: 625942784.0000\n", + "Epoch 39/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 22.3486 - val_loss: 611333248.0000\n", + "Epoch 40/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 22.2903 - val_loss: 606125440.0000\n", + "Epoch 41/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 22.2299 - val_loss: 600408256.0000\n", + "Epoch 42/100\n", + "192/192 [==============================] - 0s 995us/step - loss: 22.0806 - val_loss: 590723264.0000\n", + "Epoch 43/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 21.7701 - val_loss: 583678144.0000\n", + "Epoch 44/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 21.9006 - val_loss: 577920960.0000\n", + "Epoch 45/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 21.8087 - val_loss: 567927296.0000\n", + "Epoch 46/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 21.8747 - val_loss: 564737856.0000\n", + "Epoch 47/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 21.8164 - val_loss: 558105024.0000\n", + "Epoch 48/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 21.7617 - val_loss: 545681472.0000\n", + "Epoch 49/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 22.2611 - val_loss: 547658624.0000\n", + "Epoch 50/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 21.7451 - val_loss: 529287840.0000\n", + "Epoch 51/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 21.6618 - val_loss: 538415424.0000\n", + "Epoch 52/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 21.6405 - val_loss: 526375744.0000\n", + "Epoch 53/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 21.6234 - val_loss: 523492224.0000\n", + "Epoch 54/100\n", + "192/192 [==============================] - 0s 991us/step - loss: 21.6752 - val_loss: 517951328.0000\n", + "Epoch 55/100\n", + "192/192 [==============================] - 0s 957us/step - loss: 21.5805 - val_loss: 517134720.0000\n", + "Epoch 56/100\n", + "192/192 [==============================] - 0s 990us/step - loss: 21.7772 - val_loss: 505650528.0000\n", + "Epoch 57/100\n", + "192/192 [==============================] - 0s 990us/step - loss: 21.4580 - val_loss: 501462752.0000\n", + "Epoch 58/100\n", + "192/192 [==============================] - 0s 958us/step - loss: 21.6620 - val_loss: 504142880.0000\n", + "Epoch 59/100\n", + "192/192 [==============================] - 0s 974us/step - loss: 21.6206 - val_loss: 497545408.0000\n", + "Epoch 60/100\n", + "192/192 [==============================] - 0s 984us/step - loss: 21.5144 - val_loss: 485903648.0000\n", + "Epoch 61/100\n", + "192/192 [==============================] - 0s 984us/step - loss: 21.4289 - val_loss: 488917472.0000\n", + "Epoch 62/100\n", + "192/192 [==============================] - 0s 958us/step - loss: 21.3365 - val_loss: 484559616.0000\n", + "Epoch 63/100\n", + "192/192 [==============================] - 0s 979us/step - loss: 21.1568 - val_loss: 469904416.0000\n", + "Epoch 64/100\n", + "192/192 [==============================] - 0s 952us/step - loss: 21.3791 - val_loss: 466319936.0000\n", + "Epoch 65/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 20.9299 - val_loss: 462157184.0000\n", + "Epoch 66/100\n", + "192/192 [==============================] - 0s 973us/step - loss: 20.9182 - val_loss: 460814720.0000\n", + "Epoch 67/100\n", + "192/192 [==============================] - 0s 969us/step - loss: 21.0156 - val_loss: 458287296.0000\n", + "Epoch 68/100\n", + "192/192 [==============================] - 0s 974us/step - loss: 21.0712 - val_loss: 451982144.0000\n", + "Epoch 69/100\n", + "192/192 [==============================] - 0s 945us/step - loss: 20.8178 - val_loss: 451185344.0000\n", + "Epoch 70/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 20.9400 - val_loss: 440099168.0000\n", + "Epoch 71/100\n", + "192/192 [==============================] - 0s 968us/step - loss: 20.9792 - val_loss: 444701056.0000\n", + "Epoch 72/100\n", + "192/192 [==============================] - 0s 969us/step - loss: 20.7082 - val_loss: 439451584.0000\n", + "Epoch 73/100\n", + "192/192 [==============================] - 0s 974us/step - loss: 20.8705 - val_loss: 438926240.0000\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 74/100\n", + "192/192 [==============================] - 0s 948us/step - loss: 20.9405 - val_loss: 434460960.0000\n", + "Epoch 75/100\n", + "192/192 [==============================] - 0s 953us/step - loss: 20.8470 - val_loss: 440190688.0000\n", + "Epoch 76/100\n", + "192/192 [==============================] - 0s 979us/step - loss: 20.8279 - val_loss: 430655072.0000\n", + "Epoch 77/100\n", + "192/192 [==============================] - 0s 937us/step - loss: 20.7440 - val_loss: 426091136.0000\n", + "Epoch 78/100\n", + "192/192 [==============================] - 0s 942us/step - loss: 20.9498 - val_loss: 434446048.0000\n", + "Epoch 79/100\n", + "192/192 [==============================] - 0s 953us/step - loss: 20.9132 - val_loss: 437293984.0000\n", + "Epoch 80/100\n", + "192/192 [==============================] - 0s 922us/step - loss: 21.0839 - val_loss: 439511328.0000\n", + "Epoch 81/100\n", + "192/192 [==============================] - 0s 952us/step - loss: 20.8824 - val_loss: 438428736.0000\n", + "Epoch 82/100\n", + "192/192 [==============================] - 0s 923us/step - loss: 20.8845 - val_loss: 437566528.0000\n", + "Epoch 83/100\n", + "192/192 [==============================] - 0s 942us/step - loss: 20.8207 - val_loss: 434014848.0000\n", + "Epoch 84/100\n", + "192/192 [==============================] - 0s 927us/step - loss: 20.8663 - val_loss: 441011040.0000\n", + "Epoch 85/100\n", + "192/192 [==============================] - 0s 921us/step - loss: 20.8142 - val_loss: 443873440.0000\n", + "Epoch 86/100\n", + "192/192 [==============================] - 0s 947us/step - loss: 20.7954 - val_loss: 430658112.0000\n", + "Epoch 87/100\n", + "192/192 [==============================] - 0s 912us/step - loss: 20.7968 - val_loss: 438615424.0000\n", + "Epoch 88/100\n", + "192/192 [==============================] - 0s 974us/step - loss: 20.8670 - val_loss: 432157152.0000\n", + "Epoch 89/100\n", + "192/192 [==============================] - 0s 963us/step - loss: 21.0467 - val_loss: 444976608.0000\n", + "Epoch 90/100\n", + "192/192 [==============================] - 0s 943us/step - loss: 20.7190 - val_loss: 448802464.0000\n", + "Epoch 91/100\n", + "192/192 [==============================] - 0s 916us/step - loss: 20.9051 - val_loss: 454478496.0000\n", + "Epoch 92/100\n", + "192/192 [==============================] - 0s 948us/step - loss: 20.8039 - val_loss: 449556576.0000\n", + "Epoch 93/100\n", + "192/192 [==============================] - 0s 937us/step - loss: 20.9025 - val_loss: 454530528.0000\n", + "Epoch 94/100\n", + "192/192 [==============================] - 0s 952us/step - loss: 20.5214 - val_loss: 448073920.0000\n", + "Epoch 95/100\n", + "192/192 [==============================] - 0s 969us/step - loss: 20.6263 - val_loss: 439715360.0000\n", + "Epoch 96/100\n", + "192/192 [==============================] - 0s 932us/step - loss: 20.7127 - val_loss: 452371936.0000\n", + "Epoch 97/100\n", + "192/192 [==============================] - 0s 1ms/step - loss: 20.7545 - val_loss: 448452736.0000\n", + "Epoch 98/100\n", + "192/192 [==============================] - 0s 953us/step - loss: 20.5185 - val_loss: 456734976.0000\n", + "Epoch 99/100\n", + "192/192 [==============================] - 0s 927us/step - loss: 20.6495 - val_loss: 456889440.0000\n", + "Epoch 100/100\n", + "192/192 [==============================] - 0s 921us/step - loss: 20.8627 - val_loss: 455231328.0000\n" + ] + } + ], + "source": [ + "gr=ann.fit(x_train, Y_train, epochs=100, validation_data=(x_val, Y_val))" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "loss_train = gr.history['loss']\n", + "loss_val =gr.history['val_loss']\n", + "epochs = range(1,101)\n", + "plt.plot(epochs, loss_train, 'g', label='Training loss')\n", + "plt.plot(epochs, loss_val, 'b', label='validation loss')\n", + "plt.title('Training and Validation loss')\n", + "plt.xlabel('Epochs')\n", + "plt.ylabel('Loss')\n", + "plt.legend()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "60/60 [==============================] - 0s 642us/step\n" + ] + }, + { + "data": { + "text/plain": [ + "-4000.5717946760174" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "prediction= ann.predict(x_test)\n", + "r2=r2_score(prediction, Y_test)\n", + "r2" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "colab": { + "collapsed_sections": [], + "name": "Copy of CVusingTF_Assgn2.ipynb", + "provenance": [ + { + "file_id": "1ptX8WQ4CFpsuB3FySAo-Ofzinil-gfw_", + "timestamp": 1654672766911 + } + ] + }, + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "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": "3.10.2" + } + }, + "nbformat": 4, + "nbformat_minor": 1 +} From 13f8950a40f1129a81f705267346c27b1f9e3e61 Mon Sep 17 00:00:00 2001 From: Vedantadlak <94456041+Vedantadlak@users.noreply.github.com> Date: Thu, 23 Jun 2022 15:23:20 +0530 Subject: [PATCH 4/6] Add files via upload --- Assignment 3/A3_211154.ipynb | 409 +++++++++++++++++++++++++++++++++++ 1 file changed, 409 insertions(+) create mode 100644 Assignment 3/A3_211154.ipynb diff --git a/Assignment 3/A3_211154.ipynb b/Assignment 3/A3_211154.ipynb new file mode 100644 index 0000000..27407f1 --- /dev/null +++ b/Assignment 3/A3_211154.ipynb @@ -0,0 +1,409 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "VGHh_5UYzKpV" + }, + "source": [ + "# Assignment 3\n", + "\n", + " In this Assignment, we will use CNN to classify digits. \n", + "The `MNIST` database is a large database of handwritten digits that is commonly used for training various image processing systems.\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "JnsMbCPNzPAr" + }, + "source": [ + "## Importing TensorFlow" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "id": "HRLTw3cMwvi7" + }, + "outputs": [], + "source": [ + "import tensorflow as tf\n", + "import matplotlib.pyplot as plt" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "6Ji7HGpgzSPi" + }, + "source": [ + "## Get the dataset" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "id": "oEW3KDEvzIHL" + }, + "outputs": [], + "source": [ + "# Import the dataset\n", + "\n", + "(x_train, y_train), (x_test, y_test) = tf.keras.datasets.mnist.load_data()" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "id": "F_sRU9dx_mYQ" + }, + "outputs": [], + "source": [ + "# Split the dataset\n", + "\n", + "from sklearn.model_selection import train_test_split\n", + "X_train,X_test,Y_train,Y_test=train_test_split(x_test,y_test,test_size=0.2)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "id": "rbt0WbW6sDVs" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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IOxAEYQeCIOxAEIQdCIKwA0EQdiCI/wd2tzSxEBZxwAAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Pre processing \n", + "x_train =tf.keras.utils.normalize(x_train,axis=1)\n", + "x_test = tf.keras.utils.normalize(x_test,axis=1)\n", + "plt.imshow(x_train[0], cmap=plt.cm.binary)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "EVpQheoVqoEG" + }, + "source": [ + "## Visualize the dataset\n", + "Print some images with labels." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "id": "yF1Nj63Bz9m7" + }, + "outputs": [ + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "# Your code\n", + "plt.imshow(x_train[0], cmap=plt.cm.binary)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Rx8muKSIrKhe" + }, + "source": [ + "Plot statistics of the training and testing dataset \n", + "(`x axis`: digits, `y axis`: number of samples corresponding to the digits)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "id": "37kehTG_6Pi4" + }, + "outputs": [], + "source": [ + "import numpy as np\n", + "\n", + "# Your code\n", + "IMG_SIZE=28\n", + "x_trainr=np.array(x_train).reshape(-1,IMG_SIZE,IMG_SIZE,1)\n", + "x_testr=np.array(x_test).reshape(-1,IMG_SIZE,IMG_SIZE,1)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "kWlpCWdAr8d3" + }, + "source": [ + "## Model" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "id": "1L07EyQ0Yion" + }, + "outputs": [], + "source": [ + "# model building\n", + "\n", + "# You are supposed to look at some CNN architectures and add convolutional layers along with MaxPooling, specifying the kernel size, pooling size, activation \n", + "from tensorflow.keras.models import Sequential\n", + "from tensorflow.keras.layers import Dense,Dropout,Activation,Flatten,Conv2D,MaxPooling2D\n", + "#1st layer\n", + "model =Sequential()\n", + "model.add(Conv2D(64,(3,3),input_shape =x_trainr.shape[1:]))\n", + "model.add(Activation(\"relu\"))\n", + "model.add(MaxPooling2D(pool_size=(2,2)))\n", + "#2nd Layer\n", + "model.add(Conv2D(64,(3,3)))\n", + "model.add(Activation(\"relu\"))\n", + "model.add(MaxPooling2D(pool_size=(2,2)))\n", + "#3rd Layer\n", + "model.add(Conv2D(64,(3,3)))\n", + "model.add(Activation(\"relu\"))\n", + "model.add(MaxPooling2D(pool_size=(2,2)))\n", + "\n", + "model.add(Flatten())\n", + "model.add(Dense(64))\n", + "model.add(Activation(\"relu\"))\n", + "\n", + "model.add(Dense(32))\n", + "model.add(Activation(\"relu\"))\n", + " \n", + "model.add(Dense(10))\n", + "model.add(Activation(\"softmax\"))\n" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "id": "nKEZ8cbO9JVV" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/5\n", + "1313/1313 [==============================] - 66s 49ms/step - loss: 0.3331 - accuracy: 0.8946 - val_loss: 0.1358 - val_accuracy: 0.9579\n", + "Epoch 2/5\n", + "1313/1313 [==============================] - 65s 50ms/step - loss: 0.1065 - accuracy: 0.9684 - val_loss: 0.1023 - val_accuracy: 0.9693\n", + "Epoch 3/5\n", + "1313/1313 [==============================] - 63s 48ms/step - loss: 0.0770 - accuracy: 0.9768 - val_loss: 0.0714 - val_accuracy: 0.9781\n", + "Epoch 4/5\n", + "1313/1313 [==============================] - 64s 49ms/step - loss: 0.0602 - accuracy: 0.9811 - val_loss: 0.0734 - val_accuracy: 0.9782\n", + "Epoch 5/5\n", + "1313/1313 [==============================] - 62s 47ms/step - loss: 0.0492 - accuracy: 0.9849 - val_loss: 0.0651 - val_accuracy: 0.9812\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Compile the model (add optimizers and metrics)\n", + "\n", + "# Fit the model on the training data (specify validation_split, read about validation if new to you)\n", + "model.compile(loss=\"sparse_categorical_crossentropy\",optimizer =\"adam\", metrics=['accuracy'])\n", + "model.fit(x_trainr,y_train,epochs=5,validation_split=0.3)\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ml1Kna_DuJrL" + }, + "source": [ + "## Predict some images\n", + "Print the image along with its label (true value) and predicted value." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "id": "qioZul7_uiYq" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "313/313 [==============================] - 4s 13ms/step\n" + ] + } + ], + "source": [ + "# Your code\n", + "predictions=model.predict([x_testr])" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "7\n", + "2\n", + "1\n", + "0\n", + "4\n", + "1\n", + "4\n", + "9\n", + "5\n", + "9\n", + "0\n", + "6\n", + "9\n", + "0\n", + "1\n", + "5\n", + "9\n", + "7\n", + "3\n", + "4\n", + "9\n", + "6\n", + "6\n", + "5\n", + "4\n" + ] + } + ], + "source": [ + "for i in range(25):\n", + " print(np.argmax(predictions[i] ))" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "f= plt.figure()\n", + "for i in range(25):\n", + " f.add_subplot(1,25,i+1)\n", + " plt.imshow(x_test[i])\n", + "\n", + "\n", + "plt.show(block=True)\n" + ] + } + ], + "metadata": { + "accelerator": "GPU", + "colab": { + "name": "Copy of CV_with_TF-Assignment-3.ipynb", + "provenance": [ + { + "file_id": "1asGptVW1kSOD-sm44G3PJr-Ad9lPwQFR", + "timestamp": 1655806641912 + }, + { + "file_id": "1D6ydyPPCMxckA2UNfQAfoDNQMednmPXO", + "timestamp": 1655269145670 + }, + { + "file_id": "1SOXxLRZADUvtLiTygZYTHBTZP2l0W_jT", + "timestamp": 1655267663630 + }, + { + "file_id": "1nTfv0Eyv59_cvAq13soX2DgTp0t4G6M3", + "timestamp": 1655196024245 + } + ] + }, + "gpuClass": "standard", + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "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": "3.10.2" + } + }, + "nbformat": 4, + "nbformat_minor": 1 +} From 568905d71f070f501dae55d00a0889582fd86d35 Mon Sep 17 00:00:00 2001 From: Vedantadlak <94456041+Vedantadlak@users.noreply.github.com> Date: Sat, 16 Jul 2022 22:18:23 +0530 Subject: [PATCH 5/6] Add files via upload --- Final Task/A4_211154.ipynb | 1 + 1 file changed, 1 insertion(+) create mode 100644 Final Task/A4_211154.ipynb diff --git a/Final Task/A4_211154.ipynb b/Final Task/A4_211154.ipynb new file mode 100644 index 0000000..c792f3b --- /dev/null +++ b/Final Task/A4_211154.ipynb @@ -0,0 +1 @@ +{"cells":[{"cell_type":"markdown","metadata":{"id":"rtI19Rt-H7Uc"},"source":["## Final Task:\n","This is your final evaluation for the project. As decided, we will be predicting images of people into three classes: `without_mask`, `mask_weared_incorrect` and `with_mask`. "]},{"cell_type":"code","execution_count":1,"metadata":{"id":"c2CiXcHQTbX8","executionInfo":{"status":"ok","timestamp":1657988907110,"user_tz":-330,"elapsed":1869,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"}}},"outputs":[],"source":["import tensorflow as tf"]},{"cell_type":"markdown","metadata":{"id":"QKDPyiZTIm1c"},"source":["### Loading the dataset\n","Make a copy of the dataset given to you in your Google Drive (keep it outside, don't put it in any folder to avoid inconvenience). Ensure it is named as `Mask_Dataset` or change the path (the variable `data_dir`) accordingly."]},{"cell_type":"code","execution_count":null,"metadata":{"id":"hNEMe7XsIjrK"},"outputs":[],"source":["# Mount Google Drive\n","from google.colab import drive\n","drive.mount('/content/drive')\n","!unzip drive/MyDrive/Data/Mask_Dataset-20220712T181941Z-001"]},{"cell_type":"code","execution_count":3,"metadata":{"id":"8CXzo4MOJOl8","executionInfo":{"status":"ok","timestamp":1657988940898,"user_tz":-330,"elapsed":68,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"}}},"outputs":[],"source":["import pathlib\n","\n","path='/content/Mask_Dataset/'\n","data_dir = pathlib.Path(path)"]},{"cell_type":"markdown","metadata":{"id":"YHPHkGyDKscK"},"source":["### Know the Dataset\n","Most of the code is written for you as you aren't used to these libraries. You are to go through the documentation for your benefit."]},{"cell_type":"code","execution_count":4,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":67,"status":"ok","timestamp":1657988940898,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"},"user_tz":-330},"id":"PzbSy-vXKjD-","outputId":"d6450938-bdce-48c7-e87f-7ea3039133f8"},"outputs":[{"output_type":"stream","name":"stdout","text":["8982\n"]}],"source":["# Print image count\n","image_count = len(list(data_dir.glob('*/*.png')))\n","print(image_count)"]},{"cell_type":"code","execution_count":5,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":6,"status":"ok","timestamp":1657988940899,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"},"user_tz":-330},"id":"rFHWFYj5NCVm","outputId":"d4447cfc-234b-485b-db80-e64a2cb56605"},"outputs":[{"output_type":"stream","name":"stdout","text":["['without_mask', 'with_mask', 'mask_weared_incorrect']\n"]}],"source":["# Print Output Labels\n","import os\n","output_classes = os.listdir(data_dir)\n","print(output_classes)"]},{"cell_type":"code","execution_count":6,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":299},"executionInfo":{"elapsed":860,"status":"ok","timestamp":1657988941754,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"},"user_tz":-330},"id":"fESyMw90KaxN","outputId":"afcde5a4-c535-4d81-d468-3f1c62ce791c"},"outputs":[{"output_type":"stream","name":"stdout","text":["[2994, 2994, 2994]\n"]},{"output_type":"display_data","data":{"text/plain":["
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\n"},"metadata":{"needs_background":"light"}}],"source":["# Plot count of each ouput label\n","import matplotlib.pyplot as plt\n","\n","count=[]\n","for label in output_classes:\n"," this_path=path+label\n"," dir=pathlib.Path(this_path)\n"," im_count=os.listdir(dir)\n"," count.append(len(im_count))\n","\n","print(count)\n","\n","plt.bar(output_classes,count)\n","plt.title(\"Statistics\")\n","plt.show()"]},{"cell_type":"code","execution_count":7,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":268},"executionInfo":{"elapsed":1253,"status":"ok","timestamp":1657988943005,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"},"user_tz":-330},"id":"HDSJ2Zk5a14s","outputId":"8dfce03f-c3cb-4839-c014-53bcccc2185a"},"outputs":[{"output_type":"display_data","data":{"text/plain":["
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\n"},"metadata":{"needs_background":"light"}}],"source":["# Check some sample images (Use of cv2)\n","import cv2\n","from google.colab.patches import cv2_imshow\n","\n","# Your code\n","DataDirectory=\"/content/Mask_Dataset/\"\n","Classes =[\"mask_weared_incorrect\",\"with_mask\",\"without_mask\"]\n","for category in Classes:\n"," path=os.path.join(DataDirectory,category)\n"," for img in os.listdir(path):\n"," img_array = cv2.imread(os.path.join(path,img))\n"," plt.imshow(cv2.cvtColor(img_array, cv2.COLOR_BGR2RGB))\n"," plt.show()\n"," break\n"," break "]},{"cell_type":"code","execution_count":8,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":13,"status":"ok","timestamp":1657988943006,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"},"user_tz":-330},"id":"jWBEMC1FUfXS","outputId":"b562e1ae-c951-4fba-e807-10911b982037"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["(128, 128, 3)"]},"metadata":{},"execution_count":8}],"source":["# Check shape of the images in your dataset. This will be helpful while specifying input_shape in your Transfer Learning Model\n","img_array.shape"]},{"cell_type":"code","execution_count":9,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":286},"executionInfo":{"elapsed":11,"status":"ok","timestamp":1657988943006,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"},"user_tz":-330},"id":"ActfjQig7TaK","outputId":"163c1c72-66f8-4d15-efcd-9c70e23d8f15"},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":9},{"output_type":"display_data","data":{"text/plain":["
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\n"},"metadata":{"needs_background":"light"}}],"source":["# Check if all the images have same shape, else you need to resize them to some common size\n","# The code provided as it is above in the template will help \n","img_size= 224\n","new_array = cv2.resize(img_array,(img_size,img_size))\n","plt.imshow(cv2.cvtColor(new_array, cv2.COLOR_BGR2RGB))"]},{"cell_type":"code","execution_count":10,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":10,"status":"ok","timestamp":1657988943007,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"},"user_tz":-330},"id":"G-Atau4Rfc-x","outputId":"94061acd-2e96-4e8c-a96b-c9720b5d9f41"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["(224, 224, 3)"]},"metadata":{},"execution_count":10}],"source":["# If the shape is variable, reshape to a common size \n","# If it is same, prove it\n","s=new_array.shape\n","s"]},{"cell_type":"code","execution_count":11,"metadata":{"id":"F0XHxMo2RVQd","executionInfo":{"status":"ok","timestamp":1657988943007,"user_tz":-330,"elapsed":9,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"}}},"outputs":[],"source":["# Anything else you want to plot/experiment"]},{"cell_type":"markdown","metadata":{"id":"zSoUXS1cRbnu"},"source":["### Model Definition\n","Choose a model for Transfer Learning (You may also experment with multiple models and keep all of them in this notebook)"]},{"cell_type":"code","execution_count":12,"metadata":{"id":"QKZmIgXMTHfy","executionInfo":{"status":"ok","timestamp":1657988943436,"user_tz":-330,"elapsed":437,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"}}},"outputs":[],"source":["from tensorflow.keras.layers import Input, Lambda, Dense, Flatten,MaxPooling2D\n","from tensorflow.keras.models import Model\n","from tensorflow.keras import layers\n","from tensorflow.keras.preprocessing import image\n","from tensorflow.keras.models import Sequential\n","from keras.applications.vgg19 import VGG19\n","from keras.applications.vgg19 import preprocess_input\n","from keras import Sequential\n","from keras.layers import Flatten, Dense\n","from keras.preprocessing.image import ImageDataGenerator\n","from tensorflow.keras.preprocessing.image import img_to_array\n","from tensorflow.keras.preprocessing.image import load_img\n","from tensorflow.keras.utils import to_categorical\n","from sklearn.preprocessing import LabelEncoder\n","from sklearn.model_selection import train_test_split\n","from sklearn.metrics import classification_report\n","from tensorflow.keras.preprocessing.image import ImageDataGenerator\n","from tensorflow.keras.applications import MobileNetV2\n","from tensorflow.keras.layers import AveragePooling2D\n","from tensorflow.keras.layers import Dropout\n","from tensorflow.keras.layers import Flatten\n","from tensorflow.keras.layers import Dense\n","from tensorflow.keras.layers import Input\n","from tensorflow.keras.models import Model\n","from tensorflow.keras.optimizers import Adam\n","from tensorflow.keras.applications.mobilenet_v2 import preprocess_input\n","from tensorflow.keras.preprocessing.image import img_to_array\n","from tensorflow.keras.preprocessing.image import load_img\n","from tensorflow.keras.utils import to_categorical\n","from sklearn.preprocessing import LabelBinarizer\n","from sklearn.model_selection import train_test_split\n","from sklearn.metrics import classification_report\n","from imutils import paths\n","import matplotlib.pyplot as plt\n","import numpy as np\n","import os"]},{"cell_type":"code","execution_count":13,"metadata":{"id":"9xWLUibHRNGj","executionInfo":{"status":"ok","timestamp":1657988951028,"user_tz":-330,"elapsed":7593,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"}},"colab":{"base_uri":"https://localhost:8080/"},"outputId":"cbe34b85-1e2d-4a81-b7ae-80207e54a8cf"},"outputs":[{"output_type":"stream","name":"stdout","text":["Downloading data from https://storage.googleapis.com/tensorflow/keras-applications/resnet/resnet50_weights_tf_dim_ordering_tf_kernels_notop.h5\n","94773248/94765736 [==============================] - 1s 0us/step\n","94781440/94765736 [==============================] - 1s 0us/step\n"]}],"source":["from keras.applications.resnet import ResNet50\n","from tensorflow.keras.optimizers import Adam\n","# Choose and define base model\n","model=ResNet50(include_top=False,weights='imagenet',input_shape=s)\n","\n"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"J3TwB_GLd7BU"},"outputs":[],"source":["# Print base model summary and have a look at the layers\n","model.summary()"]},{"cell_type":"code","execution_count":15,"metadata":{"id":"F_Heq3C1eKd-","executionInfo":{"status":"ok","timestamp":1657988952819,"user_tz":-330,"elapsed":23,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"}}},"outputs":[],"source":["# As we're using Transfer Learning, you do not need to train all the layers. Freeze all of the layers or train some layers (experiment)\n","for layer in model.layers:\n"," layer.trainable = False"]},{"cell_type":"code","execution_count":16,"metadata":{"id":"MKx1EtUJea6D","executionInfo":{"status":"ok","timestamp":1657988952819,"user_tz":-330,"elapsed":22,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"}}},"outputs":[],"source":["# Append Fully connected/custom Conv2D/Dropout/MaxPooling layers to the base model\n","from keras.layers import Convolution2D, MaxPooling2D, ZeroPadding2D, GlobalAveragePooling2D, AveragePooling2D\n","av1=GlobalAveragePooling2D()(model.output)\n","fc1=Dense(256,activation='relu')(av1)\n","d1=Dropout(0.5)(fc1)\n","fc2=Dense(3,activation='softmax')(d1)\n","\n","\n","\n","\n"]},{"cell_type":"code","execution_count":17,"metadata":{"id":"q6I3oTTNgP8L","executionInfo":{"status":"ok","timestamp":1657988952820,"user_tz":-330,"elapsed":23,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"}}},"outputs":[],"source":["# Add the final output layer\n","\n","new_model=Model(inputs=model.input,outputs=fc2)\n"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"6aVQocJwgN5r"},"outputs":[],"source":["# Print your model's summary\n","\n","new_model.summary()"]},{"cell_type":"code","execution_count":19,"metadata":{"id":"qdC71fUBgXAg","executionInfo":{"status":"ok","timestamp":1657988955645,"user_tz":-330,"elapsed":16,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"}},"colab":{"base_uri":"https://localhost:8080/"},"outputId":"101c78af-0599-4d11-e5e8-05b1077bc0af"},"outputs":[{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.7/dist-packages/keras/optimizer_v2/adam.py:105: UserWarning: The `lr` argument is deprecated, use `learning_rate` instead.\n"," super(Adam, self).__init__(name, **kwargs)\n"]}],"source":["# Compile you model (set the parameters like loss/optimizers/metrics)\n","adam=Adam(lr=0.00003)\n","new_model.compile(optimizer='adam',loss = tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True), metrics=['accuracy'])"]},{"cell_type":"markdown","metadata":{"id":"RdUSMLggifex"},"source":["### Data Augmentation and Pre-processing\n","Augment the data. You may also try dyanamic augmentation using [`tf.keras.preprocessing.image.ImageDataGenerator `](https://www.tensorflow.org/api_docs/python/tf/keras/preprocessing/image/ImageDataGenerator). \n","You may use [`tf.keras.applications.vgg16.preprocess_input`](https://www.tensorflow.org/api_docs/python/tf/keras/applications/vgg16/preprocess_input)(or some other base model's utility) for pre-processing (can also be passed as a parameter to `ImageDataGenerator`)"]},{"cell_type":"code","execution_count":20,"metadata":{"executionInfo":{"elapsed":2912,"status":"ok","timestamp":1657988958553,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"},"user_tz":-330},"id":"NbHUZcOAObGQ","colab":{"base_uri":"https://localhost:8080/"},"outputId":"27f62dc8-591e-4b46-ccaa-4f8cf3749201"},"outputs":[{"output_type":"stream","name":"stdout","text":["Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"]}],"source":["from google.colab import drive\n","drive.mount('/content/drive')"]},{"cell_type":"code","execution_count":21,"metadata":{"id":"DBscSsvkgn39","executionInfo":{"status":"ok","timestamp":1657988958554,"user_tz":-330,"elapsed":6,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"}}},"outputs":[],"source":["from keras.applications.vgg16 import preprocess_input # Change according to your base model\n","from tensorflow.keras.preprocessing.image import ImageDataGenerator\n","\n","# Your code \n","INIT_LR = 1e-4\n","EPOCHS = 20\n","BS = 32\n","train_datagen = ImageDataGenerator(\n"," rescale=1 / 255.0,\n"," rotation_range=20,\n"," zoom_range=0.05,\n"," width_shift_range=0.05,\n"," height_shift_range=0.05,\n"," shear_range=0.05,\n"," horizontal_flip=True,\n"," fill_mode=\"nearest\",\n"," validation_split=0.20)\n","\n","test_datagen = ImageDataGenerator(rescale=1 / 255.0)"]},{"cell_type":"code","execution_count":22,"metadata":{"id":"rhyHEFXDkZr4","executionInfo":{"status":"ok","timestamp":1657988958554,"user_tz":-330,"elapsed":6,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"}}},"outputs":[],"source":["# Anything else you wish to try"]},{"cell_type":"markdown","metadata":{"id":"IcKPxCpOkcuG"},"source":["### Training and Validation Dataset \n","Split the dataset into training and validation (We'll be looking for your validation accuracy, assume we are using complete dataset for now). \n","\n","Hint: `flow_from_directory` used with `ImageDataGenerator` will simplify things for you."]},{"cell_type":"code","execution_count":23,"metadata":{"id":"wLFAbPuKZ5b4","executionInfo":{"status":"ok","timestamp":1657988968701,"user_tz":-330,"elapsed":10153,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"}}},"outputs":[],"source":["import glob\n","import numpy as np\n","msi = glob.glob('/content/Mask_Dataset/mask_weared_incorrect/*.*')\n","wm = glob.glob('/content/Mask_Dataset/with_mask/*.*')\n","wom = glob.glob('/content/Mask_Dataset/without_mask/*.*')\n","\n","\n","data = []\n","labels = []\n","\n","for i in msi: \n"," image=tf.keras.preprocessing.image.load_img(i, color_mode='rgb', \n"," target_size= s)\n"," image=np.array(image)\n"," data.append(image)\n"," labels.append(0)\n","for i in wm: \n"," image=tf.keras.preprocessing.image.load_img(i, color_mode='rgb', \n"," target_size= s)\n"," image=np.array(image)\n"," data.append(image)\n"," labels.append(1)\n","for i in wom: \n"," image=tf.keras.preprocessing.image.load_img(i, color_mode='rgb', \n"," target_size= s)\n"," image=np.array(image)\n"," data.append(image)\n"," labels.append(2)\n","\n","data = np.array(data)\n","labels = np.array(labels)\n","\n","from sklearn.model_selection import train_test_split\n","X_train, X_test, ytrain, ytest = train_test_split(data, labels, test_size=0.2,\n"," random_state=42)\n"]},{"cell_type":"markdown","metadata":{"id":"ZZPsjpT1mp3z"},"source":["### Training \n","Train your model for some epochs and plot the graph. Try and save your best model. Experiment with the parameters of `model.fit`"]},{"cell_type":"code","execution_count":24,"metadata":{"id":"5iC9wsF5a72v","executionInfo":{"status":"ok","timestamp":1657989114329,"user_tz":-330,"elapsed":145632,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"}},"colab":{"base_uri":"https://localhost:8080/"},"outputId":"d7a68de4-5894-469a-ede3-ea882f3a1223"},"outputs":[{"output_type":"stream","name":"stdout","text":["Epoch 1/5\n"]},{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.7/dist-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: \"`sparse_categorical_crossentropy` received `from_logits=True`, but the `output` argument was produced by a sigmoid or softmax activation and thus does not represent logits. Was this intended?\"\n"," return dispatch_target(*args, **kwargs)\n"]},{"output_type":"stream","name":"stdout","text":["180/180 [==============================] - 38s 138ms/step - loss: 0.2030 - accuracy: 0.9351 - val_loss: 0.0648 - val_accuracy: 0.9756\n","Epoch 2/5\n","180/180 [==============================] - 21s 115ms/step - loss: 0.0895 - accuracy: 0.9671 - val_loss: 0.0708 - val_accuracy: 0.9743\n","Epoch 3/5\n","180/180 [==============================] - 21s 116ms/step - loss: 0.0645 - accuracy: 0.9779 - val_loss: 0.0404 - val_accuracy: 0.9826\n","Epoch 4/5\n","180/180 [==============================] - 21s 118ms/step - loss: 0.0340 - accuracy: 0.9873 - val_loss: 0.0398 - val_accuracy: 0.9847\n","Epoch 5/5\n","180/180 [==============================] - 22s 121ms/step - loss: 0.0239 - accuracy: 0.9925 - val_loss: 0.0536 - val_accuracy: 0.9833\n"]}],"source":["hist=new_model.fit(X_train,ytrain,epochs=5,validation_split=0.20)\n"]},{"cell_type":"code","execution_count":27,"metadata":{"id":"Gs2X14MBmu7W","executionInfo":{"status":"ok","timestamp":1657989313702,"user_tz":-330,"elapsed":414,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"}},"colab":{"base_uri":"https://localhost:8080/"},"outputId":"426bbaa4-ea41-45eb-9593-9f17d2a2eb66"},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":27}],"source":["from keras.callbacks import ModelCheckpoint\n","# ModelCheckpoint is helpful to save the model giving best results (brownie points)\n","tf.keras.callbacks.ModelCheckpoint(\n"," DataDirectory,\n"," monitor=\"val_loss\",\n"," verbose=0,\n"," save_best_only=False,\n"," save_weights_only=False,\n"," mode=\"auto\",\n"," save_freq=\"epoch\",\n"," options=None,\n"," initial_value_threshold=None,\n"," \n",")"]},{"cell_type":"markdown","metadata":{"id":"FTvRa1FXri4R"},"source":["### Evaluate the performance"]},{"cell_type":"code","execution_count":28,"metadata":{"id":"cTH6flzcrck0","executionInfo":{"status":"ok","timestamp":1657989320391,"user_tz":-330,"elapsed":511,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"}},"colab":{"base_uri":"https://localhost:8080/","height":295},"outputId":"20ed008a-6f80-42c5-9d33-a9bf9abb3645"},"outputs":[{"output_type":"display_data","data":{"text/plain":["
"],"image/png":"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\n"},"metadata":{"needs_background":"light"}}],"source":["# Plot training & validation loss/accuracy values\n","loss_train = hist.history['loss']\n","loss_val =hist.history['val_loss']\n","epochs = range(1,6)\n","plt.plot(epochs, loss_train, 'g', label='Training loss')\n","plt.plot(epochs, loss_val, 'b', label='validation loss')\n","plt.title('Training and Validation loss')\n","plt.xlabel('Epochs')\n","plt.ylabel('Loss')\n","plt.legend()\n","plt.show()"]},{"cell_type":"code","execution_count":32,"metadata":{"id":"fJ-ZtU84r66Z","executionInfo":{"status":"error","timestamp":1657989898786,"user_tz":-330,"elapsed":149573,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"}},"colab":{"base_uri":"https://localhost:8080/","height":519},"outputId":"f4d30564-d643-4e2f-84af-a600e953f8bb"},"outputs":[{"output_type":"stream","name":"stdout","text":["Epoch 1/5\n","180/180 [==============================] - 22s 120ms/step - loss: 0.0353 - accuracy: 0.9878 - val_loss: 0.1011 - val_accuracy: 0.9791\n","Epoch 2/5\n","180/180 [==============================] - 22s 123ms/step - loss: 0.0259 - accuracy: 0.9901 - val_loss: 0.0897 - val_accuracy: 0.9812\n","Epoch 3/5\n","180/180 [==============================] - 23s 127ms/step - loss: 0.0116 - accuracy: 0.9965 - val_loss: 0.0420 - val_accuracy: 0.9882\n","Epoch 4/5\n","180/180 [==============================] - 22s 123ms/step - loss: 0.0088 - accuracy: 0.9965 - val_loss: 0.0387 - val_accuracy: 0.9889\n","Epoch 5/5\n","180/180 [==============================] - 22s 122ms/step - loss: 0.0036 - accuracy: 0.9984 - val_loss: 0.0533 - val_accuracy: 0.9868\n"]},{"output_type":"error","ename":"ValueError","evalue":"ignored","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)","\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0mnew_model\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX_train\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mytrain\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mepochs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mvalidation_split\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0.20\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 9\u001b[0;31m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mclassification_report\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mytest\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0masarray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnew_model\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpredict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX_test\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;32m/usr/local/lib/python3.7/dist-packages/sklearn/metrics/_classification.py\u001b[0m in \u001b[0;36mclassification_report\u001b[0;34m(y_true, y_pred, labels, target_names, sample_weight, digits, output_dict, zero_division)\u001b[0m\n\u001b[1;32m 2108\u001b[0m \"\"\"\n\u001b[1;32m 2109\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2110\u001b[0;31m \u001b[0my_type\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_true\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_pred\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_check_targets\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my_true\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_pred\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2111\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2112\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mlabels\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.7/dist-packages/sklearn/metrics/_classification.py\u001b[0m in \u001b[0;36m_check_targets\u001b[0;34m(y_true, y_pred)\u001b[0m\n\u001b[1;32m 93\u001b[0m raise ValueError(\n\u001b[1;32m 94\u001b[0m \"Classification metrics can't handle a mix of {0} and {1} targets\".format(\n\u001b[0;32m---> 95\u001b[0;31m \u001b[0mtype_true\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtype_pred\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 96\u001b[0m )\n\u001b[1;32m 97\u001b[0m )\n","\u001b[0;31mValueError\u001b[0m: Classification metrics can't handle a mix of multiclass and continuous-multioutput targets"]}],"source":["from types import new_class\n","from sklearn.metrics import classification_report, confusion_matrix\n","import numpy as np\n","\n","\n","\n","new_model.fit(X_train,ytrain,epochs=5,validation_split=0.20)\n","\n","print(classification_report(ytest, np.asarray(new_model.predict(X_test))))\n"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"VytDxkswrvXw","executionInfo":{"status":"aborted","timestamp":1657989114333,"user_tz":-330,"elapsed":8,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"}}},"outputs":[],"source":["# Use the classification report to print precision, recall, f1-score for the three classes(optional, brownie points)\n"]}],"metadata":{"accelerator":"GPU","colab":{"collapsed_sections":[],"name":"Copy of Copy of ICG-CVwTF-Final_Task.ipynb","provenance":[{"file_id":"1LRPK0LU3-NmzNXNzqH7Ziy4TG0LbcN0B","timestamp":1657787729346},{"file_id":"1-StHlJj6XIfC0fptgdCWJ_OT_11cDP2G","timestamp":1657650542199},{"file_id":"161I3lETOZM4v3Mqmr7L7NY7gb6XbSyNJ","timestamp":1656064995558}]},"gpuClass":"standard","kernelspec":{"display_name":"Python 3","name":"python3"},"language_info":{"name":"python"}},"nbformat":4,"nbformat_minor":0} \ No newline at end of file From 0ef693af756e5e4ad0166caf88b10fc7f0d9799b Mon Sep 17 00:00:00 2001 From: VEDANT ADLAK Date: Mon, 26 Aug 2024 17:29:03 +0530 Subject: [PATCH 6/6] final changes --- Final Task/A4_211154.ipynb | 1 - Final Task/Final_Task.ipynb | 1045 +++++++++++++++++++++++++++++++++++ 2 files changed, 1045 insertions(+), 1 deletion(-) delete mode 100644 Final Task/A4_211154.ipynb create mode 100644 Final Task/Final_Task.ipynb diff --git a/Final Task/A4_211154.ipynb b/Final Task/A4_211154.ipynb deleted file mode 100644 index c792f3b..0000000 --- a/Final Task/A4_211154.ipynb +++ /dev/null @@ -1 +0,0 @@ -{"cells":[{"cell_type":"markdown","metadata":{"id":"rtI19Rt-H7Uc"},"source":["## Final Task:\n","This is your final evaluation for the project. As decided, we will be predicting images of people into three classes: `without_mask`, `mask_weared_incorrect` and `with_mask`. "]},{"cell_type":"code","execution_count":1,"metadata":{"id":"c2CiXcHQTbX8","executionInfo":{"status":"ok","timestamp":1657988907110,"user_tz":-330,"elapsed":1869,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"}}},"outputs":[],"source":["import tensorflow as tf"]},{"cell_type":"markdown","metadata":{"id":"QKDPyiZTIm1c"},"source":["### Loading the dataset\n","Make a copy of the dataset given to you in your Google Drive (keep it outside, don't put it in any folder to avoid inconvenience). Ensure it is named as `Mask_Dataset` or change the path (the variable `data_dir`) accordingly."]},{"cell_type":"code","execution_count":null,"metadata":{"id":"hNEMe7XsIjrK"},"outputs":[],"source":["# Mount Google Drive\n","from google.colab import drive\n","drive.mount('/content/drive')\n","!unzip drive/MyDrive/Data/Mask_Dataset-20220712T181941Z-001"]},{"cell_type":"code","execution_count":3,"metadata":{"id":"8CXzo4MOJOl8","executionInfo":{"status":"ok","timestamp":1657988940898,"user_tz":-330,"elapsed":68,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"}}},"outputs":[],"source":["import pathlib\n","\n","path='/content/Mask_Dataset/'\n","data_dir = pathlib.Path(path)"]},{"cell_type":"markdown","metadata":{"id":"YHPHkGyDKscK"},"source":["### Know the Dataset\n","Most of the code is written for you as you aren't used to these libraries. You are to go through the documentation for your benefit."]},{"cell_type":"code","execution_count":4,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":67,"status":"ok","timestamp":1657988940898,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"},"user_tz":-330},"id":"PzbSy-vXKjD-","outputId":"d6450938-bdce-48c7-e87f-7ea3039133f8"},"outputs":[{"output_type":"stream","name":"stdout","text":["8982\n"]}],"source":["# Print image count\n","image_count = len(list(data_dir.glob('*/*.png')))\n","print(image_count)"]},{"cell_type":"code","execution_count":5,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":6,"status":"ok","timestamp":1657988940899,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"},"user_tz":-330},"id":"rFHWFYj5NCVm","outputId":"d4447cfc-234b-485b-db80-e64a2cb56605"},"outputs":[{"output_type":"stream","name":"stdout","text":["['without_mask', 'with_mask', 'mask_weared_incorrect']\n"]}],"source":["# Print Output Labels\n","import os\n","output_classes = os.listdir(data_dir)\n","print(output_classes)"]},{"cell_type":"code","execution_count":6,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":299},"executionInfo":{"elapsed":860,"status":"ok","timestamp":1657988941754,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"},"user_tz":-330},"id":"fESyMw90KaxN","outputId":"afcde5a4-c535-4d81-d468-3f1c62ce791c"},"outputs":[{"output_type":"stream","name":"stdout","text":["[2994, 2994, 2994]\n"]},{"output_type":"display_data","data":{"text/plain":["
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\n"},"metadata":{"needs_background":"light"}}],"source":["# Plot count of each ouput label\n","import matplotlib.pyplot as plt\n","\n","count=[]\n","for label in output_classes:\n"," this_path=path+label\n"," dir=pathlib.Path(this_path)\n"," im_count=os.listdir(dir)\n"," count.append(len(im_count))\n","\n","print(count)\n","\n","plt.bar(output_classes,count)\n","plt.title(\"Statistics\")\n","plt.show()"]},{"cell_type":"code","execution_count":7,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":268},"executionInfo":{"elapsed":1253,"status":"ok","timestamp":1657988943005,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"},"user_tz":-330},"id":"HDSJ2Zk5a14s","outputId":"8dfce03f-c3cb-4839-c014-53bcccc2185a"},"outputs":[{"output_type":"display_data","data":{"text/plain":["
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\n"},"metadata":{"needs_background":"light"}}],"source":["# Check some sample images (Use of cv2)\n","import cv2\n","from google.colab.patches import cv2_imshow\n","\n","# Your code\n","DataDirectory=\"/content/Mask_Dataset/\"\n","Classes =[\"mask_weared_incorrect\",\"with_mask\",\"without_mask\"]\n","for category in Classes:\n"," path=os.path.join(DataDirectory,category)\n"," for img in os.listdir(path):\n"," img_array = cv2.imread(os.path.join(path,img))\n"," plt.imshow(cv2.cvtColor(img_array, cv2.COLOR_BGR2RGB))\n"," plt.show()\n"," break\n"," break "]},{"cell_type":"code","execution_count":8,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":13,"status":"ok","timestamp":1657988943006,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"},"user_tz":-330},"id":"jWBEMC1FUfXS","outputId":"b562e1ae-c951-4fba-e807-10911b982037"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["(128, 128, 3)"]},"metadata":{},"execution_count":8}],"source":["# Check shape of the images in your dataset. This will be helpful while specifying input_shape in your Transfer Learning Model\n","img_array.shape"]},{"cell_type":"code","execution_count":9,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":286},"executionInfo":{"elapsed":11,"status":"ok","timestamp":1657988943006,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"},"user_tz":-330},"id":"ActfjQig7TaK","outputId":"163c1c72-66f8-4d15-efcd-9c70e23d8f15"},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":9},{"output_type":"display_data","data":{"text/plain":["
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\n"},"metadata":{"needs_background":"light"}}],"source":["# Check if all the images have same shape, else you need to resize them to some common size\n","# The code provided as it is above in the template will help \n","img_size= 224\n","new_array = cv2.resize(img_array,(img_size,img_size))\n","plt.imshow(cv2.cvtColor(new_array, cv2.COLOR_BGR2RGB))"]},{"cell_type":"code","execution_count":10,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":10,"status":"ok","timestamp":1657988943007,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"},"user_tz":-330},"id":"G-Atau4Rfc-x","outputId":"94061acd-2e96-4e8c-a96b-c9720b5d9f41"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["(224, 224, 3)"]},"metadata":{},"execution_count":10}],"source":["# If the shape is variable, reshape to a common size \n","# If it is same, prove it\n","s=new_array.shape\n","s"]},{"cell_type":"code","execution_count":11,"metadata":{"id":"F0XHxMo2RVQd","executionInfo":{"status":"ok","timestamp":1657988943007,"user_tz":-330,"elapsed":9,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"}}},"outputs":[],"source":["# Anything else you want to plot/experiment"]},{"cell_type":"markdown","metadata":{"id":"zSoUXS1cRbnu"},"source":["### Model Definition\n","Choose a model for Transfer Learning (You may also experment with multiple models and keep all of them in this notebook)"]},{"cell_type":"code","execution_count":12,"metadata":{"id":"QKZmIgXMTHfy","executionInfo":{"status":"ok","timestamp":1657988943436,"user_tz":-330,"elapsed":437,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"}}},"outputs":[],"source":["from tensorflow.keras.layers import Input, Lambda, Dense, Flatten,MaxPooling2D\n","from tensorflow.keras.models import Model\n","from tensorflow.keras import layers\n","from tensorflow.keras.preprocessing import image\n","from tensorflow.keras.models import Sequential\n","from keras.applications.vgg19 import VGG19\n","from keras.applications.vgg19 import preprocess_input\n","from keras import Sequential\n","from keras.layers import Flatten, Dense\n","from keras.preprocessing.image import ImageDataGenerator\n","from tensorflow.keras.preprocessing.image import img_to_array\n","from tensorflow.keras.preprocessing.image import load_img\n","from tensorflow.keras.utils import to_categorical\n","from sklearn.preprocessing import LabelEncoder\n","from sklearn.model_selection import train_test_split\n","from sklearn.metrics import classification_report\n","from tensorflow.keras.preprocessing.image import ImageDataGenerator\n","from tensorflow.keras.applications import MobileNetV2\n","from tensorflow.keras.layers import AveragePooling2D\n","from tensorflow.keras.layers import Dropout\n","from tensorflow.keras.layers import Flatten\n","from tensorflow.keras.layers import Dense\n","from tensorflow.keras.layers import Input\n","from tensorflow.keras.models import Model\n","from tensorflow.keras.optimizers import Adam\n","from tensorflow.keras.applications.mobilenet_v2 import preprocess_input\n","from tensorflow.keras.preprocessing.image import img_to_array\n","from tensorflow.keras.preprocessing.image import load_img\n","from tensorflow.keras.utils import to_categorical\n","from sklearn.preprocessing import LabelBinarizer\n","from sklearn.model_selection import train_test_split\n","from sklearn.metrics import classification_report\n","from imutils import paths\n","import matplotlib.pyplot as plt\n","import numpy as np\n","import os"]},{"cell_type":"code","execution_count":13,"metadata":{"id":"9xWLUibHRNGj","executionInfo":{"status":"ok","timestamp":1657988951028,"user_tz":-330,"elapsed":7593,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"}},"colab":{"base_uri":"https://localhost:8080/"},"outputId":"cbe34b85-1e2d-4a81-b7ae-80207e54a8cf"},"outputs":[{"output_type":"stream","name":"stdout","text":["Downloading data from https://storage.googleapis.com/tensorflow/keras-applications/resnet/resnet50_weights_tf_dim_ordering_tf_kernels_notop.h5\n","94773248/94765736 [==============================] - 1s 0us/step\n","94781440/94765736 [==============================] - 1s 0us/step\n"]}],"source":["from keras.applications.resnet import ResNet50\n","from tensorflow.keras.optimizers import Adam\n","# Choose and define base model\n","model=ResNet50(include_top=False,weights='imagenet',input_shape=s)\n","\n"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"J3TwB_GLd7BU"},"outputs":[],"source":["# Print base model summary and have a look at the layers\n","model.summary()"]},{"cell_type":"code","execution_count":15,"metadata":{"id":"F_Heq3C1eKd-","executionInfo":{"status":"ok","timestamp":1657988952819,"user_tz":-330,"elapsed":23,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"}}},"outputs":[],"source":["# As we're using Transfer Learning, you do not need to train all the layers. Freeze all of the layers or train some layers (experiment)\n","for layer in model.layers:\n"," layer.trainable = False"]},{"cell_type":"code","execution_count":16,"metadata":{"id":"MKx1EtUJea6D","executionInfo":{"status":"ok","timestamp":1657988952819,"user_tz":-330,"elapsed":22,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"}}},"outputs":[],"source":["# Append Fully connected/custom Conv2D/Dropout/MaxPooling layers to the base model\n","from keras.layers import Convolution2D, MaxPooling2D, ZeroPadding2D, GlobalAveragePooling2D, AveragePooling2D\n","av1=GlobalAveragePooling2D()(model.output)\n","fc1=Dense(256,activation='relu')(av1)\n","d1=Dropout(0.5)(fc1)\n","fc2=Dense(3,activation='softmax')(d1)\n","\n","\n","\n","\n"]},{"cell_type":"code","execution_count":17,"metadata":{"id":"q6I3oTTNgP8L","executionInfo":{"status":"ok","timestamp":1657988952820,"user_tz":-330,"elapsed":23,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"}}},"outputs":[],"source":["# Add the final output layer\n","\n","new_model=Model(inputs=model.input,outputs=fc2)\n"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"6aVQocJwgN5r"},"outputs":[],"source":["# Print your model's summary\n","\n","new_model.summary()"]},{"cell_type":"code","execution_count":19,"metadata":{"id":"qdC71fUBgXAg","executionInfo":{"status":"ok","timestamp":1657988955645,"user_tz":-330,"elapsed":16,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"}},"colab":{"base_uri":"https://localhost:8080/"},"outputId":"101c78af-0599-4d11-e5e8-05b1077bc0af"},"outputs":[{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.7/dist-packages/keras/optimizer_v2/adam.py:105: UserWarning: The `lr` argument is deprecated, use `learning_rate` instead.\n"," super(Adam, self).__init__(name, **kwargs)\n"]}],"source":["# Compile you model (set the parameters like loss/optimizers/metrics)\n","adam=Adam(lr=0.00003)\n","new_model.compile(optimizer='adam',loss = tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True), metrics=['accuracy'])"]},{"cell_type":"markdown","metadata":{"id":"RdUSMLggifex"},"source":["### Data Augmentation and Pre-processing\n","Augment the data. You may also try dyanamic augmentation using [`tf.keras.preprocessing.image.ImageDataGenerator `](https://www.tensorflow.org/api_docs/python/tf/keras/preprocessing/image/ImageDataGenerator). \n","You may use [`tf.keras.applications.vgg16.preprocess_input`](https://www.tensorflow.org/api_docs/python/tf/keras/applications/vgg16/preprocess_input)(or some other base model's utility) for pre-processing (can also be passed as a parameter to `ImageDataGenerator`)"]},{"cell_type":"code","execution_count":20,"metadata":{"executionInfo":{"elapsed":2912,"status":"ok","timestamp":1657988958553,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"},"user_tz":-330},"id":"NbHUZcOAObGQ","colab":{"base_uri":"https://localhost:8080/"},"outputId":"27f62dc8-591e-4b46-ccaa-4f8cf3749201"},"outputs":[{"output_type":"stream","name":"stdout","text":["Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"]}],"source":["from google.colab import drive\n","drive.mount('/content/drive')"]},{"cell_type":"code","execution_count":21,"metadata":{"id":"DBscSsvkgn39","executionInfo":{"status":"ok","timestamp":1657988958554,"user_tz":-330,"elapsed":6,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"}}},"outputs":[],"source":["from keras.applications.vgg16 import preprocess_input # Change according to your base model\n","from tensorflow.keras.preprocessing.image import ImageDataGenerator\n","\n","# Your code \n","INIT_LR = 1e-4\n","EPOCHS = 20\n","BS = 32\n","train_datagen = ImageDataGenerator(\n"," rescale=1 / 255.0,\n"," rotation_range=20,\n"," zoom_range=0.05,\n"," width_shift_range=0.05,\n"," height_shift_range=0.05,\n"," shear_range=0.05,\n"," horizontal_flip=True,\n"," fill_mode=\"nearest\",\n"," validation_split=0.20)\n","\n","test_datagen = ImageDataGenerator(rescale=1 / 255.0)"]},{"cell_type":"code","execution_count":22,"metadata":{"id":"rhyHEFXDkZr4","executionInfo":{"status":"ok","timestamp":1657988958554,"user_tz":-330,"elapsed":6,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"}}},"outputs":[],"source":["# Anything else you wish to try"]},{"cell_type":"markdown","metadata":{"id":"IcKPxCpOkcuG"},"source":["### Training and Validation Dataset \n","Split the dataset into training and validation (We'll be looking for your validation accuracy, assume we are using complete dataset for now). \n","\n","Hint: `flow_from_directory` used with `ImageDataGenerator` will simplify things for you."]},{"cell_type":"code","execution_count":23,"metadata":{"id":"wLFAbPuKZ5b4","executionInfo":{"status":"ok","timestamp":1657988968701,"user_tz":-330,"elapsed":10153,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"}}},"outputs":[],"source":["import glob\n","import numpy as np\n","msi = glob.glob('/content/Mask_Dataset/mask_weared_incorrect/*.*')\n","wm = glob.glob('/content/Mask_Dataset/with_mask/*.*')\n","wom = glob.glob('/content/Mask_Dataset/without_mask/*.*')\n","\n","\n","data = []\n","labels = []\n","\n","for i in msi: \n"," image=tf.keras.preprocessing.image.load_img(i, color_mode='rgb', \n"," target_size= s)\n"," image=np.array(image)\n"," data.append(image)\n"," labels.append(0)\n","for i in wm: \n"," image=tf.keras.preprocessing.image.load_img(i, color_mode='rgb', \n"," target_size= s)\n"," image=np.array(image)\n"," data.append(image)\n"," labels.append(1)\n","for i in wom: \n"," image=tf.keras.preprocessing.image.load_img(i, color_mode='rgb', \n"," target_size= s)\n"," image=np.array(image)\n"," data.append(image)\n"," labels.append(2)\n","\n","data = np.array(data)\n","labels = np.array(labels)\n","\n","from sklearn.model_selection import train_test_split\n","X_train, X_test, ytrain, ytest = train_test_split(data, labels, test_size=0.2,\n"," random_state=42)\n"]},{"cell_type":"markdown","metadata":{"id":"ZZPsjpT1mp3z"},"source":["### Training \n","Train your model for some epochs and plot the graph. Try and save your best model. Experiment with the parameters of `model.fit`"]},{"cell_type":"code","execution_count":24,"metadata":{"id":"5iC9wsF5a72v","executionInfo":{"status":"ok","timestamp":1657989114329,"user_tz":-330,"elapsed":145632,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"}},"colab":{"base_uri":"https://localhost:8080/"},"outputId":"d7a68de4-5894-469a-ede3-ea882f3a1223"},"outputs":[{"output_type":"stream","name":"stdout","text":["Epoch 1/5\n"]},{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.7/dist-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: \"`sparse_categorical_crossentropy` received `from_logits=True`, but the `output` argument was produced by a sigmoid or softmax activation and thus does not represent logits. Was this intended?\"\n"," return dispatch_target(*args, **kwargs)\n"]},{"output_type":"stream","name":"stdout","text":["180/180 [==============================] - 38s 138ms/step - loss: 0.2030 - accuracy: 0.9351 - val_loss: 0.0648 - val_accuracy: 0.9756\n","Epoch 2/5\n","180/180 [==============================] - 21s 115ms/step - loss: 0.0895 - accuracy: 0.9671 - val_loss: 0.0708 - val_accuracy: 0.9743\n","Epoch 3/5\n","180/180 [==============================] - 21s 116ms/step - loss: 0.0645 - accuracy: 0.9779 - val_loss: 0.0404 - val_accuracy: 0.9826\n","Epoch 4/5\n","180/180 [==============================] - 21s 118ms/step - loss: 0.0340 - accuracy: 0.9873 - val_loss: 0.0398 - val_accuracy: 0.9847\n","Epoch 5/5\n","180/180 [==============================] - 22s 121ms/step - loss: 0.0239 - accuracy: 0.9925 - val_loss: 0.0536 - val_accuracy: 0.9833\n"]}],"source":["hist=new_model.fit(X_train,ytrain,epochs=5,validation_split=0.20)\n"]},{"cell_type":"code","execution_count":27,"metadata":{"id":"Gs2X14MBmu7W","executionInfo":{"status":"ok","timestamp":1657989313702,"user_tz":-330,"elapsed":414,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"}},"colab":{"base_uri":"https://localhost:8080/"},"outputId":"426bbaa4-ea41-45eb-9593-9f17d2a2eb66"},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":27}],"source":["from keras.callbacks import ModelCheckpoint\n","# ModelCheckpoint is helpful to save the model giving best results (brownie points)\n","tf.keras.callbacks.ModelCheckpoint(\n"," DataDirectory,\n"," monitor=\"val_loss\",\n"," verbose=0,\n"," save_best_only=False,\n"," save_weights_only=False,\n"," mode=\"auto\",\n"," save_freq=\"epoch\",\n"," options=None,\n"," initial_value_threshold=None,\n"," \n",")"]},{"cell_type":"markdown","metadata":{"id":"FTvRa1FXri4R"},"source":["### Evaluate the performance"]},{"cell_type":"code","execution_count":28,"metadata":{"id":"cTH6flzcrck0","executionInfo":{"status":"ok","timestamp":1657989320391,"user_tz":-330,"elapsed":511,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"}},"colab":{"base_uri":"https://localhost:8080/","height":295},"outputId":"20ed008a-6f80-42c5-9d33-a9bf9abb3645"},"outputs":[{"output_type":"display_data","data":{"text/plain":["
"],"image/png":"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\n"},"metadata":{"needs_background":"light"}}],"source":["# Plot training & validation loss/accuracy values\n","loss_train = hist.history['loss']\n","loss_val =hist.history['val_loss']\n","epochs = range(1,6)\n","plt.plot(epochs, loss_train, 'g', label='Training loss')\n","plt.plot(epochs, loss_val, 'b', label='validation loss')\n","plt.title('Training and Validation loss')\n","plt.xlabel('Epochs')\n","plt.ylabel('Loss')\n","plt.legend()\n","plt.show()"]},{"cell_type":"code","execution_count":32,"metadata":{"id":"fJ-ZtU84r66Z","executionInfo":{"status":"error","timestamp":1657989898786,"user_tz":-330,"elapsed":149573,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"}},"colab":{"base_uri":"https://localhost:8080/","height":519},"outputId":"f4d30564-d643-4e2f-84af-a600e953f8bb"},"outputs":[{"output_type":"stream","name":"stdout","text":["Epoch 1/5\n","180/180 [==============================] - 22s 120ms/step - loss: 0.0353 - accuracy: 0.9878 - val_loss: 0.1011 - val_accuracy: 0.9791\n","Epoch 2/5\n","180/180 [==============================] - 22s 123ms/step - loss: 0.0259 - accuracy: 0.9901 - val_loss: 0.0897 - val_accuracy: 0.9812\n","Epoch 3/5\n","180/180 [==============================] - 23s 127ms/step - loss: 0.0116 - accuracy: 0.9965 - val_loss: 0.0420 - val_accuracy: 0.9882\n","Epoch 4/5\n","180/180 [==============================] - 22s 123ms/step - loss: 0.0088 - accuracy: 0.9965 - val_loss: 0.0387 - val_accuracy: 0.9889\n","Epoch 5/5\n","180/180 [==============================] - 22s 122ms/step - loss: 0.0036 - accuracy: 0.9984 - val_loss: 0.0533 - val_accuracy: 0.9868\n"]},{"output_type":"error","ename":"ValueError","evalue":"ignored","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)","\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0mnew_model\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX_train\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mytrain\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mepochs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mvalidation_split\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0.20\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 9\u001b[0;31m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mclassification_report\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mytest\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0masarray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnew_model\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpredict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX_test\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;32m/usr/local/lib/python3.7/dist-packages/sklearn/metrics/_classification.py\u001b[0m in \u001b[0;36mclassification_report\u001b[0;34m(y_true, y_pred, labels, target_names, sample_weight, digits, output_dict, zero_division)\u001b[0m\n\u001b[1;32m 2108\u001b[0m \"\"\"\n\u001b[1;32m 2109\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2110\u001b[0;31m \u001b[0my_type\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_true\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_pred\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_check_targets\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my_true\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_pred\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2111\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2112\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mlabels\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.7/dist-packages/sklearn/metrics/_classification.py\u001b[0m in \u001b[0;36m_check_targets\u001b[0;34m(y_true, y_pred)\u001b[0m\n\u001b[1;32m 93\u001b[0m raise ValueError(\n\u001b[1;32m 94\u001b[0m \"Classification metrics can't handle a mix of {0} and {1} targets\".format(\n\u001b[0;32m---> 95\u001b[0;31m \u001b[0mtype_true\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtype_pred\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 96\u001b[0m )\n\u001b[1;32m 97\u001b[0m )\n","\u001b[0;31mValueError\u001b[0m: Classification metrics can't handle a mix of multiclass and continuous-multioutput targets"]}],"source":["from types import new_class\n","from sklearn.metrics import classification_report, confusion_matrix\n","import numpy as np\n","\n","\n","\n","new_model.fit(X_train,ytrain,epochs=5,validation_split=0.20)\n","\n","print(classification_report(ytest, np.asarray(new_model.predict(X_test))))\n"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"VytDxkswrvXw","executionInfo":{"status":"aborted","timestamp":1657989114333,"user_tz":-330,"elapsed":8,"user":{"displayName":"P4_Vedant Adlak","userId":"16249337540951820902"}}},"outputs":[],"source":["# Use the classification report to print precision, recall, f1-score for the three classes(optional, brownie points)\n"]}],"metadata":{"accelerator":"GPU","colab":{"collapsed_sections":[],"name":"Copy of Copy of ICG-CVwTF-Final_Task.ipynb","provenance":[{"file_id":"1LRPK0LU3-NmzNXNzqH7Ziy4TG0LbcN0B","timestamp":1657787729346},{"file_id":"1-StHlJj6XIfC0fptgdCWJ_OT_11cDP2G","timestamp":1657650542199},{"file_id":"161I3lETOZM4v3Mqmr7L7NY7gb6XbSyNJ","timestamp":1656064995558}]},"gpuClass":"standard","kernelspec":{"display_name":"Python 3","name":"python3"},"language_info":{"name":"python"}},"nbformat":4,"nbformat_minor":0} \ No newline at end of file diff --git a/Final Task/Final_Task.ipynb b/Final Task/Final_Task.ipynb new file mode 100644 index 0000000..306aeaf --- /dev/null +++ b/Final Task/Final_Task.ipynb @@ -0,0 +1,1045 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "rtI19Rt-H7Uc" + }, + "source": [ + "## Final Task:\n", + "This is your final evaluation for the project. As decided, we will be predicting images of people into three classes: `without_mask`, `mask_weared_incorrect` and `with_mask`. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "c2CiXcHQTbX8" + }, + "outputs": [], + "source": [ + "import tensorflow as tf" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "QKDPyiZTIm1c" + }, + "source": [ + "### Loading the dataset\n", + "Make a copy of the dataset given to you in your Google Drive (keep it outside, don't put it in any folder to avoid inconvenience). Ensure it is named as `Mask_Dataset` or change the path (the variable `data_dir`) accordingly." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "hNEMe7XsIjrK", + "outputId": "be9f86b1-e3ec-43c4-de30-6fb2bf1268cf" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Mounted at /content/drive\n" + ] + } + ], + "source": [ + "# Mount Google Drive\n", + "from google.colab import drive\n", + "drive.mount('/content/drive')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "8CXzo4MOJOl8" + }, + "outputs": [], + "source": [ + "import pathlib\n", + "\n", + "path='/content/drive/MyDrive/Mask_Dataset/'\n", + "data_dir = pathlib.Path(path)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "YHPHkGyDKscK" + }, + "source": [ + "### Know the Dataset\n", + "Most of the code is written for you as you aren't used to these libraries. You are to go through the documentation for your benefit." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "PzbSy-vXKjD-", + "outputId": "5bb9462e-521b-457b-d981-234a867a07a5" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "8992\n" + ] + } + ], + "source": [ + "# Print image count\n", + "image_count = len(list(data_dir.glob('*/*.png')))\n", + "print(image_count)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "rFHWFYj5NCVm", + "outputId": "4e7bcce0-8704-4992-e1a1-732555fbd33b" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['mask_weared_incorrect', 'with_mask', 'without_mask']\n" + ] + } + ], + "source": [ + "# Print Output Labels\n", + "import os\n", + "output_classes = os.listdir(data_dir)\n", + "print(output_classes)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 299 + }, + "id": "fESyMw90KaxN", + "outputId": "77dab5df-1f0a-4408-f841-8cbf4ae03382" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[2994, 3004, 2994]\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Plot count of each ouput label\n", + "import matplotlib.pyplot as plt\n", + "\n", + "count=[]\n", + "for label in output_classes:\n", + " this_path=path+label\n", + " dir=pathlib.Path(this_path)\n", + " im_count=os.listdir(dir)\n", + " count.append(len(im_count))\n", + "\n", + "print(count)\n", + "\n", + "plt.bar(output_classes,count)\n", + "plt.title(\"Statistics\")\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 311 + }, + "id": "HDSJ2Zk5a14s", + "outputId": "962c4472-a7f0-4741-9b4a-1de935f2d87d" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Pictures of mask_weared_incorrect: \n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Pictures of without_mask: \n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Check some sample images (Use of cv2)\n", + "import cv2\n", + "import numpy as np\n", + "from google.colab.patches import cv2_imshow\n", + "\n", + "for label in output_classes:\n", + " this_path=path+label\n", + " dir=pathlib.Path(this_path)\n", + " l = []\n", + " images = os.listdir(dir)\n", + " for i,im in enumerate(images):\n", + " if i%295==0:\n", + " l.append(cv2.imread(this_path+'/'+im))\n", + " print(\"Pictures of \"+label+\": \")\n", + " hori = np.concatenate(l, axis=1)\n", + " cv2_imshow(hori)\n", + "\n", + "\n", + "# Your code" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "jWBEMC1FUfXS", + "outputId": "5df46d7a-353a-467b-c83e-494430f5fd0b" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "In mask_weared_incorrect dataset:\n", + "(128, 128, 3)\n", + "(128, 128, 3)\n", + "In with_mask dataset:\n", + "(128, 128, 3)\n", + "(128, 128, 3)\n", + "In without_mask dataset:\n", + "(128, 128, 3)\n", + "(128, 128, 3)\n" + ] + } + ], + "source": [ + "# Check shape of the images in your dataset. This will be helpful while specifying input_shape in your Transfer Learning Model\n", + "import cv2\n", + "import numpy as np\n", + "\n", + "for cls in output_classes:\n", + " print(\"In\",cls,\"dataset:\")\n", + " for i in range(1,3):\n", + " im = cv2.imread(path+cls+\"/\"+str(i)+\".png\")\n", + " print(im.shape)\n", + "SHAPE = im.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "52BhBWRab5yc", + "outputId": "20da7935-ce40-495f-b805-e594c58f8621" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "All images have same shape, (128, 128, 3)\n" + ] + } + ], + "source": [ + "# # Check if all the images have same shape, else you need to resize them to some common size\n", + "# # The code provided as it is above in the template will help \n", + "SHAPE = (128,128,3)\n", + "\n", + "imgs = data_dir.glob('*/*.png')\n", + "flag = 0\n", + "for i in imgs:\n", + " im = cv2.imread(i.as_posix())\n", + " if im.shape != SHAPE:\n", + " flag = 1\n", + " print(\"Image of new shape \", im.shape,\" found.\")\n", + " break\n", + "if flag == 0:\n", + " print(\"All images have same shape, \", SHAPE)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "zSoUXS1cRbnu" + }, + "source": [ + "### Model Definition\n", + "Choose a model for Transfer Learning (You may also experment with multiple models and keep all of them in this notebook)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "QKZmIgXMTHfy" + }, + "outputs": [], + "source": [ + "from tensorflow.keras.layers import Input, Lambda, Dense, Flatten, Dropout\n", + "from tensorflow.keras.models import Model\n", + "from tensorflow.keras.preprocessing import image\n", + "from tensorflow.keras.models import Sequential" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "9xWLUibHRNGj", + "outputId": "50424f75-164c-4279-e057-7790279f0baf" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Downloading data from https://storage.googleapis.com/tensorflow/keras-applications/vgg16/vgg16_weights_tf_dim_ordering_tf_kernels.h5\n", + "553467096/553467096 [==============================] - 20s 0us/step\n" + ] + } + ], + "source": [ + "# Choose and define base model\n", + "from tensorflow.keras.applications.vgg16 import VGG16\n", + "SHAPE = (128,128,3)\n", + "base_model = VGG16(weights = 'imagenet',include_top=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "J3TwB_GLd7BU", + "outputId": "cac93d47-d910-4819-eba0-057c91d31cab" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"vgg16\"\n", + "_________________________________________________________________\n", + " Layer (type) Output Shape Param # \n", + "=================================================================\n", + " input_2 (InputLayer) [(None, 224, 224, 3)] 0 \n", + " \n", + " block1_conv1 (Conv2D) (None, 224, 224, 64) 1792 \n", + " \n", + " block1_conv2 (Conv2D) (None, 224, 224, 64) 36928 \n", + " \n", + " block1_pool (MaxPooling2D) (None, 112, 112, 64) 0 \n", + " \n", + " block2_conv1 (Conv2D) (None, 112, 112, 128) 73856 \n", + " \n", + " block2_conv2 (Conv2D) (None, 112, 112, 128) 147584 \n", + " \n", + " block2_pool (MaxPooling2D) (None, 56, 56, 128) 0 \n", + " \n", + " block3_conv1 (Conv2D) (None, 56, 56, 256) 295168 \n", + " \n", + " block3_conv2 (Conv2D) (None, 56, 56, 256) 590080 \n", + " \n", + " block3_conv3 (Conv2D) (None, 56, 56, 256) 590080 \n", + " \n", + " block3_pool (MaxPooling2D) (None, 28, 28, 256) 0 \n", + " \n", + " block4_conv1 (Conv2D) (None, 28, 28, 512) 1180160 \n", + " \n", + " block4_conv2 (Conv2D) (None, 28, 28, 512) 2359808 \n", + " \n", + " block4_conv3 (Conv2D) (None, 28, 28, 512) 2359808 \n", + " \n", + " block4_pool (MaxPooling2D) (None, 14, 14, 512) 0 \n", + " \n", + " block5_conv1 (Conv2D) (None, 14, 14, 512) 2359808 \n", + " \n", + " block5_conv2 (Conv2D) (None, 14, 14, 512) 2359808 \n", + " \n", + " block5_conv3 (Conv2D) (None, 14, 14, 512) 2359808 \n", + " \n", + " block5_pool (MaxPooling2D) (None, 7, 7, 512) 0 \n", + " \n", + " flatten (Flatten) (None, 25088) 0 \n", + " \n", + " fc1 (Dense) (None, 4096) 102764544 \n", + " \n", + " fc2 (Dense) (None, 4096) 16781312 \n", + " \n", + " predictions (Dense) (None, 1000) 4097000 \n", + " \n", + "=================================================================\n", + "Total params: 138,357,544\n", + "Trainable params: 138,357,544\n", + "Non-trainable params: 0\n", + "_________________________________________________________________\n" + ] + } + ], + "source": [ + "# Print base model summary and have a look at the layers\n", + "base_model.summary()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "F_Heq3C1eKd-" + }, + "outputs": [], + "source": [ + "# As we're using Transfer Learning, you do not need to train all the layers. Freeze all of the layers or train some layers (experiment)\n", + "base_model.trainable = False" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "MKx1EtUJea6D" + }, + "outputs": [], + "source": [ + "# Append Fully connected/custom Conv2D/Dropout/MaxPooling layers to the base model\n", + "inputs = Input(shape = SHAPE)\n", + "x = base_model(inputs, training = False)\n", + "x = Flatten()(x)\n", + "x = Dense(2048,activation = 'relu')(x)\n", + "x = Dropout(0.25,seed=1)(x)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "q6I3oTTNgP8L" + }, + "outputs": [], + "source": [ + "# Add the final output layer\n", + "output_ = Dense(3,activation = 'softmax')(x)\n", + "model = Model(inputs,output_)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "6aVQocJwgN5r", + "outputId": "dfd31a18-0811-44f3-d0a6-d2806b20e9cc" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"model\"\n", + "_________________________________________________________________\n", + " Layer (type) Output Shape Param # \n", + "=================================================================\n", + " input_2 (InputLayer) [(None, 128, 128, 3)] 0 \n", + " \n", + " vgg16 (Functional) (None, 4, 4, 512) 14714688 \n", + " \n", + " flatten (Flatten) (None, 8192) 0 \n", + " \n", + " dense (Dense) (None, 2048) 16779264 \n", + " \n", + " dropout (Dropout) (None, 2048) 0 \n", + " \n", + " dense_1 (Dense) (None, 3) 6147 \n", + " \n", + "=================================================================\n", + "Total params: 31,500,099\n", + "Trainable params: 16,785,411\n", + "Non-trainable params: 14,714,688\n", + "_________________________________________________________________\n" + ] + } + ], + "source": [ + "# Print your model's summary\n", + "model.summary()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "qdC71fUBgXAg" + }, + "outputs": [], + "source": [ + "# Compile you model (set the parameters like loss/optimizers/metrics)\n", + "model.compile(optimizer=tf.keras.optimizers.Adam(0.001),\n", + " loss=tf.keras.losses.CategoricalCrossentropy(), \n", + " metrics='accuracy')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "RdUSMLggifex" + }, + "source": [ + "### Data Augmentation and Pre-processing\n", + "Augment the data. You may also try dyanamic augmentation using [`tf.keras.preprocessing.image.ImageDataGenerator `](https://www.tensorflow.org/api_docs/python/tf/keras/preprocessing/image/ImageDataGenerator). \n", + "You may use [`tf.keras.applications.vgg16.preprocess_input`](https://www.tensorflow.org/api_docs/python/tf/keras/applications/vgg16/preprocess_input)(or some other base model's utility) for pre-processing (can also be passed as a parameter to `ImageDataGenerator`)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "DBscSsvkgn39" + }, + "outputs": [], + "source": [ + "from keras.applications.vgg16 import preprocess_input # Change according to your base model\n", + "from tensorflow.keras.preprocessing.image import ImageDataGenerator\n", + "\n", + "# Your code \n", + "datagen = ImageDataGenerator(\n", + " rescale = 1./255,\n", + " rotation_range=20,\n", + " width_shift_range=0.2,\n", + " height_shift_range=0.2,\n", + " horizontal_flip=True,\n", + " shear_range = 0.2,\n", + " zoom_range = 0.2,\n", + " validation_split = 0.1\n", + ")\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "IcKPxCpOkcuG" + }, + "source": [ + "### Training and Validation Dataset \n", + "Split the dataset into training and validation (We'll be looking for your validation accuracy, assume we are using complete dataset for now). \n", + "\n", + "Hint: `flow_from_directory` used with `ImageDataGenerator` will simplify things for you." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "sB7hb3ybkJRq", + "outputId": "570e450d-c81e-4234-b98c-e2cb60b7d416" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Found 8094 images belonging to 3 classes.\n", + "Found 898 images belonging to 3 classes.\n" + ] + } + ], + "source": [ + "# Your code\n", + "train_generator = datagen.flow_from_directory(\n", + " path,\n", + " target_size=SHAPE[:-1],\n", + " subset='training'\n", + ")\n", + "\n", + "val_generator = datagen.flow_from_directory(\n", + " path,\n", + " target_size=SHAPE[:-1],\n", + " subset='validation'\n", + ")\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ZZPsjpT1mp3z" + }, + "source": [ + "### Training \n", + "Train your model for some epochs and plot the graph. Try and save your best model. Experiment with the parameters of `model.fit`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "Gs2X14MBmu7W", + "outputId": "bd9b3bf6-8c5b-446a-a661-be11952113a1" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/20\n", + "253/253 [==============================] - ETA: 0s - loss: 0.5189 - accuracy: 0.8614INFO:tensorflow:Assets written to: /content/drive/MyDrive/Mask_models/vgg16/assets\n", + "253/253 [==============================] - 103s 354ms/step - loss: 0.5189 - accuracy: 0.8614 - val_loss: 0.2201 - val_accuracy: 0.9143\n", + "Epoch 2/20\n", + "253/253 [==============================] - 71s 282ms/step - loss: 0.2115 - accuracy: 0.9192 - val_loss: 0.2449 - val_accuracy: 0.8964\n", + "Epoch 3/20\n", + "253/253 [==============================] - ETA: 0s - loss: 0.1767 - accuracy: 0.9369INFO:tensorflow:Assets written to: /content/drive/MyDrive/Mask_models/vgg16/assets\n", + "253/253 [==============================] - 78s 305ms/step - loss: 0.1767 - accuracy: 0.9369 - val_loss: 0.1778 - val_accuracy: 0.9376\n", + "Epoch 4/20\n", + "253/253 [==============================] - ETA: 0s - loss: 0.1713 - accuracy: 0.9371INFO:tensorflow:Assets written to: /content/drive/MyDrive/Mask_models/vgg16/assets\n", + "253/253 [==============================] - 80s 317ms/step - loss: 0.1713 - accuracy: 0.9371 - val_loss: 0.1518 - val_accuracy: 0.9388\n", + "Epoch 5/20\n", + "253/253 [==============================] - ETA: 0s - loss: 0.1538 - accuracy: 0.9453INFO:tensorflow:Assets written to: /content/drive/MyDrive/Mask_models/vgg16/assets\n", + "253/253 [==============================] - 83s 328ms/step - loss: 0.1538 - accuracy: 0.9453 - val_loss: 0.1332 - val_accuracy: 0.9510\n", + "Epoch 6/20\n", + "253/253 [==============================] - 77s 304ms/step - loss: 0.1534 - accuracy: 0.9433 - val_loss: 0.1494 - val_accuracy: 0.9499\n", + "Epoch 7/20\n", + "253/253 [==============================] - 75s 296ms/step - loss: 0.1276 - accuracy: 0.9524 - val_loss: 0.1370 - val_accuracy: 0.9510\n", + "Epoch 8/20\n", + "253/253 [==============================] - 76s 301ms/step - loss: 0.1390 - accuracy: 0.9486 - val_loss: 0.1402 - val_accuracy: 0.9499\n", + "Epoch 9/20\n", + "253/253 [==============================] - 73s 290ms/step - loss: 0.1329 - accuracy: 0.9522 - val_loss: 0.2010 - val_accuracy: 0.9287\n", + "Epoch 10/20\n", + "253/253 [==============================] - ETA: 0s - loss: 0.1214 - accuracy: 0.9558INFO:tensorflow:Assets written to: /content/drive/MyDrive/Mask_models/vgg16/assets\n", + "253/253 [==============================] - 77s 303ms/step - loss: 0.1214 - accuracy: 0.9558 - val_loss: 0.1175 - val_accuracy: 0.9610\n", + "Epoch 11/20\n", + "253/253 [==============================] - 71s 282ms/step - loss: 0.1130 - accuracy: 0.9569 - val_loss: 0.1114 - val_accuracy: 0.9577\n", + "Epoch 12/20\n", + "253/253 [==============================] - 72s 286ms/step - loss: 0.1179 - accuracy: 0.9576 - val_loss: 0.1202 - val_accuracy: 0.9555\n", + "Epoch 13/20\n", + "253/253 [==============================] - ETA: 0s - loss: 0.1025 - accuracy: 0.9628INFO:tensorflow:Assets written to: /content/drive/MyDrive/Mask_models/vgg16/assets\n", + "253/253 [==============================] - 76s 302ms/step - loss: 0.1025 - accuracy: 0.9628 - val_loss: 0.1077 - val_accuracy: 0.9644\n", + "Epoch 14/20\n", + "253/253 [==============================] - 74s 292ms/step - loss: 0.1098 - accuracy: 0.9603 - val_loss: 0.1126 - val_accuracy: 0.9644\n", + "Epoch 15/20\n", + "253/253 [==============================] - ETA: 0s - loss: 0.0999 - accuracy: 0.9657INFO:tensorflow:Assets written to: /content/drive/MyDrive/Mask_models/vgg16/assets\n", + "253/253 [==============================] - 78s 308ms/step - loss: 0.0999 - accuracy: 0.9657 - val_loss: 0.0908 - val_accuracy: 0.9655\n", + "Epoch 16/20\n", + "253/253 [==============================] - 75s 298ms/step - loss: 0.1120 - accuracy: 0.9595 - val_loss: 0.1015 - val_accuracy: 0.9610\n", + "Epoch 17/20\n", + "253/253 [==============================] - 77s 302ms/step - loss: 0.1019 - accuracy: 0.9640 - val_loss: 0.1197 - val_accuracy: 0.9599\n", + "Epoch 18/20\n", + "253/253 [==============================] - ETA: 0s - loss: 0.1000 - accuracy: 0.9645INFO:tensorflow:Assets written to: /content/drive/MyDrive/Mask_models/vgg16/assets\n", + "253/253 [==============================] - 77s 306ms/step - loss: 0.1000 - accuracy: 0.9645 - val_loss: 0.0971 - val_accuracy: 0.9688\n", + "Epoch 19/20\n", + "253/253 [==============================] - 72s 284ms/step - loss: 0.1020 - accuracy: 0.9638 - val_loss: 0.0918 - val_accuracy: 0.9677\n", + "Epoch 20/20\n", + "253/253 [==============================] - 70s 277ms/step - loss: 0.1080 - accuracy: 0.9597 - val_loss: 0.0934 - val_accuracy: 0.9655\n" + ] + } + ], + "source": [ + "from gc import callbacks\n", + "from keras.callbacks import ModelCheckpoint\n", + "# ModelCheckpoint is helpful to save the model giving best results (brownie points)\n", + "\n", + "ckptpath = '/content/drive/MyDrive/Mask_models/vgg16'\n", + "model_checkpoint_callback = ModelCheckpoint(\n", + " filepath=ckptpath,\n", + " monitor='val_accuracy',\n", + " mode='auto',\n", + " save_best_only=True)\n", + "\n", + "history = model.fit(train_generator,\n", + " epochs=20,\n", + " validation_data=val_generator,\n", + " verbose=1,\n", + " callbacks=[model_checkpoint_callback]\n", + " )" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "FTvRa1FXri4R" + }, + "source": [ + "### Evaluate the performance" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "49_Xhnf6S9YF", + "outputId": "1a23bbbe-9365-41e0-db7f-ab36e886514a" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/5\n", + "253/253 [==============================] - ETA: 0s - loss: 0.0844 - accuracy: 0.9701INFO:tensorflow:Assets written to: /content/drive/MyDrive/Mask_models/vgg16/assets\n", + "253/253 [==============================] - 97s 367ms/step - loss: 0.0844 - accuracy: 0.9701 - val_loss: 0.0631 - val_accuracy: 0.9822\n", + "Epoch 2/5\n", + "253/253 [==============================] - 85s 337ms/step - loss: 0.0470 - accuracy: 0.9838 - val_loss: 0.0765 - val_accuracy: 0.9744\n", + "Epoch 3/5\n", + "253/253 [==============================] - 86s 340ms/step - loss: 0.0337 - accuracy: 0.9896 - val_loss: 0.0727 - val_accuracy: 0.9755\n", + "Epoch 4/5\n", + "253/253 [==============================] - 85s 335ms/step - loss: 0.0377 - accuracy: 0.9868 - val_loss: 0.0696 - val_accuracy: 0.9788\n", + "Epoch 5/5\n", + "253/253 [==============================] - ETA: 0s - loss: 0.0307 - accuracy: 0.9899INFO:tensorflow:Assets written to: /content/drive/MyDrive/Mask_models/vgg16/assets\n", + "253/253 [==============================] - 90s 355ms/step - loss: 0.0307 - accuracy: 0.9899 - val_loss: 0.0414 - val_accuracy: 0.9855\n" + ] + } + ], + "source": [ + "# Fine tuning the model\n", + "\n", + "base_model.trainable = True\n", + "\n", + "model.compile(optimizer=tf.keras.optimizers.Adam(1e-5),\n", + " loss=tf.keras.losses.CategoricalCrossentropy(), \n", + " metrics='accuracy')\n", + "\n", + "history2 = model.fit(train_generator,\n", + " epochs=5,\n", + " validation_data=val_generator,\n", + " verbose=1,\n", + " callbacks=[model_checkpoint_callback]\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 286 + }, + "id": "MOnz4qCBcJVU", + "outputId": "5321280f-a0b9-4bf6-c326-7b977de4a598" + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Plot training & validation loss/accuracy values\n", + "import matplotlib.pyplot as plt\n", + "\n", + "fig,ax = plt.subplots(ncols=2, figsize=(18,5))\n", + "\n", + "ax[0].plot(range(1,26),\n", + " history.history['loss']+history2.history['loss'], \n", + " label='training loss',\n", + " color=\"brown\", \n", + " marker=\"o\")\n", + "ax[0].plot(range(1,26),\n", + " history.history['val_loss']+history2.history['val_loss'], \n", + " label='validation loss',\n", + " color=\"green\", \n", + " marker=\"o\")\n", + "\n", + "ax[0].set_xlabel(\"epochs\", fontsize = 14)\n", + "\n", + "ax[0].set_ylabel(\"loss\",\n", + " color=\"red\",\n", + " fontsize=14)\n", + "ax[0].legend(loc='best')\n", + "ax[0].grid(True)\n", + "\n", + "# ax[1]=ax.twinx()\n", + "ax[1].plot(range(1,26),\n", + " history.history['accuracy']+history2.history['accuracy'],\n", + " label='training accuracy',\n", + " # color=\"blue\",\n", + " marker=\"o\")\n", + "ax[1].plot(range(1,26),\n", + " history.history['val_accuracy']+history2.history['val_accuracy'],\n", + " label='validation accuracy',\n", + " # color=\"blue\",\n", + " marker=\"o\")\n", + "\n", + "ax[1].set_xlabel(\"epochs\", fontsize = 14)\n", + "\n", + "ax[1].set_ylabel(\"Accuracy\",color=\"blue\",fontsize=14)\n", + "\n", + "ax[1].legend(loc='best')\n", + "ax[1].grid(True)\n", + "\n", + "fig.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "9dHGk_1ZbQup" + }, + "outputs": [], + "source": [ + "best_model = tf.keras.models.load_model('/content/drive/MyDrive/Mask_models/vgg16')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "fMiC40RZbgUM", + "outputId": "0bcea3bb-b01f-47b4-b709-40f72fa1c9df" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "29/29 [==============================] - 10s 262ms/step - loss: 0.0458 - accuracy: 0.9866\n" + ] + } + ], + "source": [ + "eval = best_model.evaluate(val_generator)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "cmeq_DwqGIBk", + "outputId": "e073ec11-f5f9-4ff5-86c7-4f042dae86ff" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Evaluation Accuracy : 98.7% \n", + "Evaluation Loss : 0.045850\n" + ] + } + ], + "source": [ + "print('Evaluation Accuracy : {:.1f}%'.format(100*eval[1]),'\\nEvaluation Loss : {:.6f}'.format(eval[0]))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "fJ-ZtU84r66Z" + }, + "outputs": [], + "source": [ + "from sklearn.metrics import classification_report, confusion_matrix\n", + "import numpy as np\n", + "\n", + "y_test = val_generator.classes\n", + "x_test = val_generator.filepaths\n", + "y_pred = []\n", + "\n", + "def prepare(impath):\n", + " img = cv2.imread(impath)\n", + " img = cv2.resize(img,(128,128))\n", + " return img.reshape(-1,128,128,3)\n", + "\n", + "for i in x_test:\n", + " img = prepare(i)\n", + " pred = best_model.predict(img)\n", + " # print(pred)\n", + " y_pred.append(np.argmax(pred))\n", + "\n", + "y_pr = np.array(y_pred)\n", + "# print classification report" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "t5WYvjKkptPU", + "outputId": "c12a1b72-dd8b-4da6-c59e-c01a350b5bb7" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " precision recall f1-score support\n", + "\n", + " 0 1.00 0.01 0.03 299\n", + " 1 0.46 1.00 0.63 300\n", + " 2 1.00 0.81 0.89 299\n", + "\n", + " accuracy 0.61 898\n", + " macro avg 0.82 0.61 0.52 898\n", + "weighted avg 0.82 0.61 0.52 898\n", + "\n", + "\n", + "Confusion matrix: \n", + "\n", + "[[ 4 295 0]\n", + " [ 0 300 0]\n", + " [ 0 58 241]]\n" + ] + } + ], + "source": [ + "# 0 -> mask_weared_incorrect\n", + "# 1 -> with_mask\n", + "# 2 -> without_mask\n", + "\n", + "print(classification_report(y_test, y_pr))\n", + "print('\\nConfusion matrix: \\n')\n", + "print(confusion_matrix(y_test, y_pr))" + ] + } + ], + "metadata": { + "accelerator": "GPU", + "colab": { + "collapsed_sections": [], + "name": "Final Task.ipynb", + "provenance": [] + }, + "gpuClass": "standard", + "interpreter": { + "hash": "26de051ba29f2982a8de78e945f0abaf191376122a1563185a90213a26c5da77" + }, + "kernelspec": { + "display_name": "Python 3.10.0 64-bit", + "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": "3.10.0" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +}