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| import cv2 | |
| import numpy as np | |
| from keras.models import load_model | |
| model=load_model('C:/Users/radha manohar kumar/Downloads/Facial Emotion Recognition/Facial Emotion/model.keras') | |
| faceDetect=cv2.CascadeClassifier('c:/Users/radha manohar kumar/Downloads/Facial Emotion Recognition/Facial Emotion/haarcascade_frontalface_default.xml') | |
| labels_dict={0:'Angry',1:'Disgust', 2:'Fear', 3:'Happy',4:'Neutral',5:'Sad',6:"Smirk",7:'Surprise'} | |
| # len(number_of_image), image_height, image_width, channel | |
| frame=cv2.imread("face_emotion1.jpg") | |
| gray=cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) | |
| faces= faceDetect.detectMultiScale(gray, 1.3, 3) | |
| for x,y,w,h in faces: | |
| sub_face_img=gray[y:y+h, x:x+w] | |
| resized=cv2.resize(sub_face_img,(48,48)) | |
| normalize=resized/255.0 | |
| reshaped=np.reshape(normalize, (1, 48, 48, 1)) | |
| result=model.predict(reshaped) | |
| label=np.argmax(result, axis=1)[0] | |
| print(label) | |
| cv2.rectangle(frame, (x,y), (x+w, y+h), (0,0,255), 1) | |
| cv2.rectangle(frame,(x,y),(x+w,y+h),(50,50,255),2) | |
| cv2.rectangle(frame,(x,y-40),(x+w,y),(50,50,255),-1) | |
| cv2.putText(frame, labels_dict[label], (x, y-10),cv2.FONT_HERSHEY_SIMPLEX,0.8,(255,255,255),2) | |
| cv2.imshow("Frame",frame) | |
| cv2.waitKey(0) | |
| cv2.destroyAllWindows() |