{ "cells": [ { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "view-in-github" }, "source": [ "\"Open" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "T1dEKfhqK9Gg" }, "source": [ "# Eigen Faces\n", "Here we use principal component analysis (PCA) to reduce the number of features in a dataset of faces.\n", "The PC's are then fed into a Support Vector Machine (SVM) classifier to classify the faces based on learned features.\n", "\n", "\n", "The dataset used in this example is a preprocessed excerpt of the\n", "\"Labeled Faces in the Wild\", aka [LFW]('http://vis-www.cs.umass.edu/lfw/lfw-funneled.tgz')\n", "\n", "[More on LFW]('http://vis-www.cs.umass.edu/lfw/')\n", "\n", "[Other resources]('http://scikit-learn.org/stable/auto_examples/applications/face_recognition.html')\n" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "90N8wtB3Lfqh" }, "source": [ "## Import the libraries\n", "Here we import the libraries that we need for later" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "colab": {}, "colab_type": "code", "id": "45QV6abqMzh2" }, "outputs": [], "source": [ "from time import time\n", "import logging\n", "import pylab as pl\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "\n", "# !pip install -U scikit-learn\n", "from sklearn.model_selection import train_test_split\n", "from sklearn.model_selection import GridSearchCV\n", "from sklearn.datasets import fetch_lfw_people\n", "from sklearn.metrics import classification_report\n", "from sklearn.metrics import confusion_matrix\n", "from sklearn.decomposition import PCA\n", "from sklearn.svm import SVC\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "colab": {}, "colab_type": "code", "id": "Tx45bywRNo91" }, "outputs": [], "source": [ "#Display progress\n", "logging.basicConfig(level=logging.INFO, format='%(asctime)s %(message)s')\n" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "_-e7Cq2lL31e" }, "source": [ "## Get the data\n", "Here we pull in the data and store it in numpy arrays\n", "\n" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 252 }, "colab_type": "code", "id": "Np3BhNhxOCuo", "outputId": "29126bf1-f1ea-4d0b-abb8-1606acd861b6" }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Downloading LFW metadata: https://ndownloader.figshare.com/files/5976012\n", "2019-07-19 05:21:21,839 Downloading LFW metadata: https://ndownloader.figshare.com/files/5976012\n", "Downloading LFW metadata: https://ndownloader.figshare.com/files/5976009\n", "2019-07-19 05:21:28,215 Downloading LFW metadata: https://ndownloader.figshare.com/files/5976009\n", "Downloading LFW metadata: https://ndownloader.figshare.com/files/5976006\n", "2019-07-19 05:21:29,542 Downloading LFW metadata: https://ndownloader.figshare.com/files/5976006\n", "Downloading LFW data (~200MB): https://ndownloader.figshare.com/files/5976015\n", "2019-07-19 05:21:31,138 Downloading LFW data (~200MB): https://ndownloader.figshare.com/files/5976015\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Total dataset size:\n", "n_samples: 1288\n", "n_features: 1850\n", "n_classes: 7\n", "Classes: ['Ariel Sharon' 'Colin Powell' 'Donald Rumsfeld' 'George W Bush'\n", " 'Gerhard Schroeder' 'Hugo Chavez' 'Tony Blair']\n" ] } ], "source": [ "#Download the data\n", "lfw_people =fetch_lfw_people(min_faces_per_person=70, resize=0.4)\n", "\n", "#Find out shape infomration about the images to help with plotting them\n", "n_samples, h, w=lfw_people.images.shape\n", "\n", "np.random.seed(42)\n", "\n", "# for machine learning we use the data directly (as relative pixel\n", "# position info is ignored by this model)\n", "X = lfw_people.data\n", "n_features = X.shape[1]\n", "\n", "# the label to predict is the ID of the person\n", "y = lfw_people.target\n", "target_names = lfw_people.target_names\n", "n_classes = target_names.shape[0]\n", "\n", "print (\"Total dataset size:\")\n", "print (\"n_samples: %d\" % n_samples)\n", "print (\"n_features: %d\" % n_features)\n", "print (\"n_classes: %d\" % n_classes)\n", "print (\"Classes: %s\" % target_names)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 183 }, "colab_type": "code", "id": "lDf_JK5WZ6-A", "outputId": "d12aaadc-f046-48e1-939f-090cbd1306dc" }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": { "tags": [] }, "output_type": "display_data" } ], "source": [ "#Lets look at the data to see what they look like\n", "\n", "pl.figure\n", "for i in range(0,3):\n", " pl.subplot(1,3,i+1)\n", " pl.imshow(X[i].reshape((h,w)), cmap=pl.cm.bone)\n", " pl.title(target_names[lfw_people.target[i]])\n", " pl.xticks(())\n", " pl.yticks(())\n", " " ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "mNp2PQTbTwub" }, "source": [ "##Split Data (Test|Train)\n", "Here we split the data into a testing and train set" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 34 }, "colab_type": "code", "id": "ukhs8iAtWGAB", "outputId": "a8f71514-31c9-4a3e-e71f-343441e4258d" }, "outputs": [ { "data": { "text/plain": [ "dtype('int64')" ] }, "execution_count": 5, "metadata": { "tags": [] }, "output_type": "execute_result" } ], "source": [ "X_train, X_test, y_train, y_test =train_test_split(X,y, test_size=0.25, random_state=42)\n", "y_test.dtype" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "XGAigHUFWsWs" }, "source": [ "##Do PCA and Dimensionality Reduction on Data\n", "Now we compute the PC's using PCA" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 217 }, "colab_type": "code", "id": "CM9j-1hmXA5x", "outputId": "e6b559ab-7e6a-4e60-e967-81a10429993a" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Extracting the top 250 eignefaces from 966 faces\n", "Done in 0.399s\n" ] }, { "data": { "image/png": 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", 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" ] }, "metadata": { "tags": [] }, "output_type": "display_data" } ], "source": [ "\n", "# Compute a PCA (eigenfaces) on the face dataset (treated as unlabeled\n", "# dataset): unsupervised feature extraction / dimensionality reduction\n", "n_components = 250\n", "\n", "print(\"Extracting the top %d eignefaces from %d faces\" % (n_components, X_train.shape[0]))\n", "\n", "#Initiate a time counter (kinda like tic toc)\n", "t0=time()\n", "\n", "#Here we take the training data and compute the PCs\n", "pca=PCA(n_components=n_components, whiten=True).fit(X_train)\n", "\n", "\n", "#Print the time it took to compute\n", "print(\"Done in %0.3fs\" % (time()-t0))\n", "\n", "\n", "\n", "#Reshape the PCs to the image format\n", "eigenfaces =pca.components_.reshape((n_components,h,w))\n", "\n", "pl.figure\n", "for i in range(0,3):\n", " pl.subplot(1,3,i+1)\n", " pl.imshow(eigenfaces[i], cmap=pl.cm.bone)\n", " pl.title(\"Eigenface PC- %d\" % (i+1))\n", " pl.xticks(())\n", " pl.yticks(())\n", "# cbar = pl.colorbar()\n", "# cbar.solids.set_edgecolor(\"face\")\n", "# pl.draw()\n", "\n", "# print(pca.explained_variance_ )\n", "# print(pca.explained_variance_ratio_)\n", "\n" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "yCE7800Z18-B" }, "source": [ "### Look at the top PC's\n", "Here we're going to plot the top PCs identified" ] }, { "cell_type": "code", "execution_count": 37, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 245 }, "colab_type": "code", "id": "6gEnvdVLsYJ0", "outputId": "6b930a4b-980f-46bc-c7e1-d3b7ea695109" }, "outputs": [ { "data": { "text/plain": [ "(250,)" ] }, "execution_count": 37, "metadata": { "tags": [] }, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": { "tags": [] }, "output_type": "display_data" } ], "source": [ "top_pcs=21\n", "plt.figure( figsize=(9, 3))\n", "plt.subplot(121)\n", "plt.bar(np.arange(top_pcs),pca.explained_variance_[0:top_pcs])\n", "plt.xlabel('PCs')\n", "plt.ylabel('Var')\n", "\n", "plt.subplot(122)\n", "plt.bar(np.arange(top_pcs),pca.explained_variance_ratio_[0:top_pcs])\n", "plt.xlabel('PCs')\n", "plt.ylabel('Ratio')\n", "\n", "np.shape(pca.explained_variance_)" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "0R9M6-wgedM2" }, "source": [ "### Projecting the PCs\n", "Now that we have the PCs (the vectors that account for the max variances) we can project the data down to the PCs. In this case they are the eigenfaces from above.\n" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 50 }, "colab_type": "code", "id": "q9UrC4FXdX8c", "outputId": "44653d6f-8ab4-4b8e-80c2-1da0bbb19c06" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Projecting the input data on the eignefaces orthonormal basis\n", "Done in 0.035s\n" ] } ], "source": [ "print(\"Projecting the input data on the eignefaces orthonormal basis\")\n", "\n", "t0=time()#tic\n", "\n", "X_train_pca = pca.transform(X_train) #take the training data and project it to eigenfaces\n", "X_test_pca = pca.transform(X_test)#take the test data and project it to eigenfaces\n", "print(\"Done in %0.3fs\" % (time()- t0)) #toc" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "DTPG7XVLcjIM" }, "source": [ "##Train a SVM Classification Model" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "ysTIBFaXcoaS" }, "source": [ "So now that we have the most important features extracted out by PCA we can use those to train a classifier. The SVM classifier can then be used to predict who's face is being presented\n" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 188 }, "colab_type": "code", "id": "ijcCI7lWc6nC", "outputId": "9f73cfd3-2452-4b38-8f58-47550b89099b" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Fitting the classifier to the training set\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/usr/local/lib/python3.6/dist-packages/sklearn/model_selection/_split.py:1978: FutureWarning: The default value of cv will change from 3 to 5 in version 0.22. Specify it explicitly to silence this warning.\n", " warnings.warn(CV_WARNING, FutureWarning)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "done in 39.016s\n", "Best estimator found by grid search:\n", "SVC(C=1000.0, cache_size=200, class_weight='balanced', coef0=0.0,\n", " decision_function_shape='ovr', degree=3, gamma=0.001, kernel='rbf',\n", " max_iter=-1, probability=False, random_state=None, shrinking=True,\n", " tol=0.001, verbose=False)\n" ] } ], "source": [ "#Training\n", "\n", "print (\"Fitting the classifier to the training set\")\n", "t0 = time()\n", "#These set parameters that we want to optimize. These are passed to GridSearch\n", "#which uses the optimal paramters in the fitting classifier =clf\n", "param_grid = {\n", " 'C': [1e3, 5e3, 1e4, 5e4, 1e5],\n", " 'gamma': [0.0001, 0.0005, 0.001, 0.005, 0.01, 0.1],\n", " }\n", "# for sklearn version 0.16 or prior, the class_weight parameter value is 'auto'\n", "clf = GridSearchCV(SVC(kernel='rbf', class_weight='balanced'), param_grid)\n", "clf = clf.fit(X_train_pca, y_train)\n", "print (\"done in %0.3fs\" % (time() - t0))\n", "print (\"Best estimator found by grid search:\")\n", "print (clf.best_estimator_)" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 403 }, "colab_type": "code", "id": "UDKbnyxUirle", "outputId": "d3a5de5e-1150-4f70-b431-87287327ea2a" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Predicting the people names on the testing set\n", "done in 0.125s\n", " precision recall f1-score support\n", "\n", " Ariel Sharon 0.64 0.69 0.67 13\n", " Colin Powell 0.75 0.90 0.82 60\n", " Donald Rumsfeld 0.82 0.67 0.73 27\n", " George W Bush 0.91 0.92 0.91 146\n", "Gerhard Schroeder 0.87 0.80 0.83 25\n", " Hugo Chavez 0.80 0.53 0.64 15\n", " Tony Blair 0.82 0.78 0.80 36\n", "\n", " accuracy 0.84 322\n", " macro avg 0.80 0.76 0.77 322\n", " weighted avg 0.84 0.84 0.84 322\n", "\n", "[[ 9 1 1 2 0 0 0]\n", " [ 1 54 2 2 0 1 0]\n", " [ 2 3 18 3 0 0 1]\n", " [ 1 6 1 134 1 1 2]\n", " [ 0 2 0 1 20 0 2]\n", " [ 0 4 0 2 0 8 1]\n", " [ 1 2 0 3 2 0 28]]\n" ] } ], "source": [ "#Testing the classifier \n", "\n", "print (\"Predicting the people names on the testing set\")\n", "t0 = time()\n", "y_pred = clf.predict(X_test_pca)\n", "print (\"done in %0.3fs\" % (time() - t0))\n", "\n", "print (classification_report(y_test, y_pred, target_names=target_names))\n", "print (confusion_matrix(y_test, y_pred, labels=range(n_classes)))\n", "\n" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "62m6EIPrls1w" }, "source": [ "##Visualizing Results\n", "Now that we've trained and tested the SVM to classify faces lets visualized the results" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "colab": {}, "colab_type": "code", "id": "85GkCbn0l81b" }, "outputs": [], "source": [ "#Create a helper function to look at the pictures\n", " \n", "def plot_gallery(images, titles, h, w, n_row=3, n_col=4):\n", " \"\"\"Helper function to plot a gallery of portraits\"\"\"\n", " pl.figure(figsize=(1.8 * n_col, 2.4 * n_row))\n", " pl.subplots_adjust(bottom=0, left=.01, right=.99, top=.90, hspace=.35)\n", " for i in range(n_row * n_col):\n", " pl.subplot(n_row, n_col, i + 1)\n", " pl.imshow(images[i].reshape((h, w)), cmap=pl.cm.gray)\n", " pl.title(titles[i], size=12)\n", " pl.xticks(())\n", " pl.yticks(())\n", "\n", "\n", "# plot the result of the prediction on a portion of the test set\n", "\n", "def title(y_pred, y_test, target_names, i):\n", " pred_name = target_names[y_pred[i]].rsplit(' ', 1)[-1]\n", " true_name = target_names[y_test[i]].rsplit(' ', 1)[-1]\n", " return 'predicted: %s\\ntrue: %s' % (pred_name, true_name)\n", "\n", "prediction_titles = [title(y_pred, y_test, target_names, i)\n", " for i in range(y_pred.shape[0])] " ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 1000 }, "colab_type": "code", "id": "Ghrh0ceNpjG1", "outputId": "87204449-9260-45b2-c3ea-611dea4fbf6f" }, "outputs": [ { "data": { "image/png": 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", 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", 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" ] }, "metadata": { "tags": [] }, "output_type": "display_data" } ], "source": [ "#Now print out preductions\n", "# prediction_titles=(X_test, prediction_titles,h,w)\n", "\n", "plot_gallery(X_test, prediction_titles, h, w )\n", "\n", "#Plot the eignefaces\n", "\n", "eigenface_titles =[\"Eigneface %d \" % i for i in range(eigenfaces.shape[0])]\n", "plot_gallery(eigenfaces, eigenface_titles, h, w)\n", "\n", "plt.show()" ] } ], "metadata": { "colab": { "collapsed_sections": [], "include_colab_link": true, "name": "EigenFaces-PCA.ipynb", "provenance": [], "version": "0.3.2" }, "kernelspec": { "display_name": "Python 3", "name": "python3" } }, "nbformat": 4, "nbformat_minor": 0 }