├── EmoDetect.py ├── FeatureGen.py ├── FeatureGen.pyc ├── LICENSE ├── README.md ├── pcadata.pkl ├── t1.jpg ├── t2.jpg ├── t3.jpg ├── t4.jpg ├── t5.jpg └── traindata.pkl /EmoDetect.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/python 2 | #Title: Script to find emotion using facial expression 3 | #Date:25/10/2015 4 | #Author:Adithya Selvaprithiviraj 5 | #PS: Not trained for nuetral expression 6 | 7 | 8 | import argparse,sys 9 | 10 | try: 11 | from FeatureGen import* 12 | except ImportError: 13 | print "Make sure FeatureGen.pyc file is in the current directory" 14 | exit() 15 | 16 | try: 17 | import dlib 18 | from skimage import io 19 | import numpy 20 | import cv2 21 | from sklearn.externals import joblib 22 | except ImportError: 23 | print "Make sure you have OpenCV, dLib, scikit learn and skimage libraries properly installed" 24 | exit() 25 | 26 | emotions={ 1:"Anger", 2:"Contempt", 3:"Disgust", 4:"Fear", 5:"Happy", 6:"Sadness", 7:"Surprise"} 27 | 28 | def Predict_Emotion(filename): 29 | 30 | print "Opening image...." 31 | try: 32 | img=io.imread(filename) 33 | cvimg=cv2.imread(filename) 34 | except: 35 | print "Exception: File Not found." 36 | return 37 | 38 | win.clear_overlay() 39 | win.set_image(img) 40 | 41 | dets=detector(img,1) 42 | 43 | if len(dets)==0: 44 | print "Unable to find any face." 45 | return 46 | 47 | for k,d in enumerate(dets): 48 | 49 | shape=predictor(img,d) 50 | landmarks=[] 51 | for i in range(68): 52 | landmarks.append(shape.part(i).x) 53 | landmarks.append(shape.part(i).y) 54 | 55 | 56 | landmarks=numpy.array(landmarks) 57 | 58 | print "Generating features......" 59 | features=generateFeatures(landmarks) 60 | features= numpy.asarray(features) 61 | 62 | print "Performing PCA Transform......." 63 | pca_features=pca.transform(features) 64 | 65 | print "Predicting using trained model........" 66 | emo_predicts=classify.predict(pca_features) 67 | print "Predicted emotion using trained data is { " + emotions[int(emo_predicts[0])] + " }" 68 | print "" 69 | 70 | font = cv2.FONT_HERSHEY_SIMPLEX 71 | cv2.putText(cvimg,emotions[int(emo_predicts[0])],(20,20), font, 1,(0,255,255),2) 72 | 73 | win.add_overlay(shape) 74 | 75 | cv2.namedWindow("Output") 76 | cv2.imshow("Output",cvimg) 77 | cv2.waitKey(0) 78 | 79 | 80 | if __name__ == "__main__": 81 | 82 | parser = argparse.ArgumentParser() 83 | parser.add_argument('-i', type=str, nargs='+', help="Enter the filenames with extention of an Image") 84 | arg=parser.parse_args() 85 | 86 | if not len(sys.argv) > 1: 87 | parser.print_help() 88 | exit() 89 | 90 | landmark_path="shape_predictor_68_face_landmarks.dat" 91 | 92 | print "Initializing Dlib face Detector.." 93 | detector= dlib.get_frontal_face_detector() 94 | 95 | print "Loading landmark identification data..." 96 | try: 97 | predictor= dlib.shape_predictor(landmark_path) 98 | except: 99 | print "Unable to find trained facial shape predictor. \nYou can download a trained facial shape predictor from: \nhttp://sourceforge.net/projects/dclib/files/dlib/v18.10/shape_predictor_68_face_landmarks.dat.bz2" 100 | exit() 101 | 102 | win=dlib.image_window() 103 | 104 | print "Loading trained data....." 105 | 106 | try: 107 | classify=joblib.load("traindata.pkl") 108 | pca=joblib.load("pcadata.pkl") 109 | except: 110 | print "Unable to load trained data. \nMake sure that traindata.pkl and pcadata.pkl are in the current directory" 111 | exit() 112 | 113 | for filename in arg.i: 114 | Predict_Emotion(filename) 115 | 116 | 117 | -------------------------------------------------------------------------------- /FeatureGen.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/python 2 | #Title:Support file to generate features 3 | #Inspired from https://github.com/avisingh599/face-rating 4 | #Date:25/10/2015 5 | 6 | import math,itertools,numpy 7 | 8 | def findRatio(points): 9 | 10 | ''' Function to find ratios ''' 11 | 12 | x=[0]*4 13 | y=[0]*4 14 | for i in range(4): 15 | x[i]=points[(2*i)] 16 | y[i]=points[(2*i)+1] 17 | 18 | dist1 = math.sqrt((x[0]-x[1])**2 + (y[0]-y[1])**2) 19 | dist2 = math.sqrt((x[2]-x[3])**2 + (y[2]-y[3])**2) 20 | ratio = dist1/dist2 21 | 22 | return ratio 23 | 24 | 25 | def generateFeatures(landmarkCoordinates): 26 | 27 | ''' Function to generate features ''' 28 | 29 | keyPoints = [18, 22, 23, 27, 37, 40, 43, 46, 28, 32, 34, 36, 5, 9, 13, 49, 55, 52, 58,61,63,65,67] 30 | combinations = itertools.combinations(keyPoints, 4) 31 | pointIndices1 = [] 32 | pointIndices2 = [] 33 | pointIndices3 = [] 34 | pointIndices4 = [] 35 | 36 | for combination in combinations: 37 | pointIndices1.append(combination[0]) 38 | pointIndices2.append(combination[1]) 39 | pointIndices3.append(combination[2]) 40 | pointIndices4.append(combination[3]) 41 | 42 | pointIndices1.append(combination[0]) 43 | pointIndices2.append(combination[2]) 44 | pointIndices3.append(combination[1]) 45 | pointIndices4.append(combination[3]) 46 | 47 | pointIndices1.append(combination[0]) 48 | pointIndices2.append(combination[3]) 49 | pointIndices3.append(combination[1]) 50 | pointIndices4.append(combination[2]) 51 | 52 | Features = numpy.zeros((1, len(pointIndices1))) 53 | ratios = []; 54 | 55 | for i in range(0, len(pointIndices1)): 56 | x1 = landmarkCoordinates[2*(pointIndices1[i]-1)] 57 | y1 = landmarkCoordinates[2*pointIndices1[i] - 1] 58 | x2 = landmarkCoordinates[2*(pointIndices2[i]-1)] 59 | y2 = landmarkCoordinates[2*pointIndices2[i] - 1] 60 | 61 | x3 = landmarkCoordinates[2*(pointIndices3[i]-1)] 62 | y3 = landmarkCoordinates[2*pointIndices3[i] - 1] 63 | x4 = landmarkCoordinates[2*(pointIndices4[i]-1)] 64 | y4 = landmarkCoordinates[2*pointIndices4[i] - 1] 65 | 66 | points = [x1, y1, x2, y2, x3, y3, x4, y4] 67 | ratios.append(findRatio(points)) 68 | 69 | Features = numpy.asarray(ratios) 70 | 71 | return Features 72 | -------------------------------------------------------------------------------- /FeatureGen.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/adithyaselv/face-expression-detect/4c1dc981eae2045adc5c3550acdb51f246727746/FeatureGen.pyc -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 2, June 1991 3 | 4 | Copyright (C) 1989, 1991 Free Software Foundation, Inc., 5 | 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA 6 | Everyone is permitted to copy and distribute verbatim copies 7 | of this license document, but changing it is not allowed. 8 | 9 | Preamble 10 | 11 | The licenses for most software are designed to take away your 12 | freedom to share and change it. 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If this is what you want to do, use the GNU Lesser General 339 | Public License instead of this License. 340 | 341 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # face-expression-detect 2 | 3 | ![ ](http://adithyaselv.com/assets/images/face-ex-det.png "expression detect") 4 | 5 | ### Video Link 6 | https://www.youtube.com/watch?v=2ky_W649G-Q 7 | 8 | ### Landmarks Detector Data 9 | [https://github.com/tzutalin/dlib-android/blob/master/data/shape_predictor_68_face_landmarks.dat](https://github.com/tzutalin/dlib-android/blob/master/data/shape_predictor_68_face_landmarks.dat) 10 | 11 | Download this and place it in the project folder. 12 | 13 | ### Dependencies 14 | 15 | * [Scikit learn]() 16 | * [opencv]() 17 | * [dlib with python support]() 18 | * [numpy]() 19 | * [skimage]() 20 | 21 | ### Usage 22 | 23 | ` $ python EmoDetect.py [-h] [-i I [I ...]] ` 24 | 25 | optional arguments: 26 | * -h, --help show this help message and exit 27 | * -i I [I ...] Enter the filenames with extention of an Image 28 | 29 | ### Dataset used for training 30 | 31 | [http://www.consortium.ri.cmu.edu/ckagree/](http://www.consortium.ri.cmu.edu/ckagree/) 32 | -------------------------------------------------------------------------------- /pcadata.pkl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/adithyaselv/face-expression-detect/4c1dc981eae2045adc5c3550acdb51f246727746/pcadata.pkl -------------------------------------------------------------------------------- /t1.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/adithyaselv/face-expression-detect/4c1dc981eae2045adc5c3550acdb51f246727746/t1.jpg -------------------------------------------------------------------------------- /t2.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/adithyaselv/face-expression-detect/4c1dc981eae2045adc5c3550acdb51f246727746/t2.jpg -------------------------------------------------------------------------------- /t3.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/adithyaselv/face-expression-detect/4c1dc981eae2045adc5c3550acdb51f246727746/t3.jpg -------------------------------------------------------------------------------- /t4.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/adithyaselv/face-expression-detect/4c1dc981eae2045adc5c3550acdb51f246727746/t4.jpg -------------------------------------------------------------------------------- /t5.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/adithyaselv/face-expression-detect/4c1dc981eae2045adc5c3550acdb51f246727746/t5.jpg -------------------------------------------------------------------------------- /traindata.pkl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/adithyaselv/face-expression-detect/4c1dc981eae2045adc5c3550acdb51f246727746/traindata.pkl --------------------------------------------------------------------------------