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| import cv2 | |
| import numpy as np | |
| import dlib | |
| from imutils import face_utils | |
| import imutils | |
| import joblib | |
| class FaceDetection(object): | |
| def __init__(self): | |
| self.detector = dlib.get_frontal_face_detector() | |
| self.predictor = joblib.load('./shape_predictor_68_face_landmarks_predictor.pkl') | |
| self.fa = face_utils.FaceAligner(self.predictor, desiredFaceWidth=256) | |
| def face_detect(self, frame): | |
| #frame = imutils.resize(frame, width=400) | |
| face_frame = np.zeros((10, 10, 3), np.uint8) | |
| mask = np.zeros((10, 10, 3), np.uint8) | |
| ROI1 = np.zeros((10, 10, 3), np.uint8) | |
| ROI2 = np.zeros((10, 10, 3), np.uint8) | |
| face_region = np.zeros((10, 10, 3), np.uint8) | |
| #ROI3 = np.zeros((10, 10, 3), np.uint8) | |
| status = False | |
| if frame is None: | |
| return | |
| gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) | |
| # detect faces in the grayscale image | |
| rects = self.detector(gray, 0) | |
| # loop over the face detections | |
| #for (i, rect) in enumerate(rects): | |
| # determine the facial landmarks for the face region, then | |
| # convert the facial landmark (x, y)-coordinates to a NumPy | |
| # array | |
| #assumpion: only 1 face is detected | |
| if len(rects)>0: | |
| status = True | |
| # shape = self.predictor(gray, rects[0]) | |
| # shape = face_utils.shape_to_np(shape) | |
| # convert dlib's rectangle to a OpenCV-style bounding box | |
| # [i.e., (x, y, w, h)], then draw the face bounding box | |
| (x, y, w, h) = face_utils.rect_to_bb(rects[0]) | |
| cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 1) | |
| if y<0: | |
| print("a") | |
| return frame, face_frame, ROI1, ROI2, status, mask | |
| #if i==0: | |
| face_frame = frame[y:y+h,x:x+w] | |
| face_region = face_frame.copy() | |
| # show the face number | |
| #cv2.putText(frame, "Face #{}".format(i + 1), (x - 10, y - 10), | |
| # cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2) | |
| # loop over the (x, y)-coordinates for the facial landmarks | |
| # and draw them on the image | |
| # for (x, y) in shape: | |
| # cv2.circle(frame, (x, y), 1, (0, 0, 255), -1) #draw facial landmarks | |
| if(face_frame.shape[:2][1] != 0): | |
| face_frame = imutils.resize(face_frame,width=256) | |
| #print(frame,'|||',gray,'|||',rects[0],type(np.array(rects[0]))) | |
| face_frame = self.fa.align(frame,gray,rects[0]) # align face | |
| grayf = cv2.cvtColor(face_frame, cv2.COLOR_BGR2GRAY) | |
| rectsf = self.detector(grayf, 0) | |
| if len(rectsf) >0: | |
| shape = self.predictor(grayf, rectsf[0]) | |
| shape = face_utils.shape_to_np(shape) | |
| for (a, b) in shape: | |
| cv2.circle(face_frame, (a, b), 1, (0, 0, 255), -1) #draw facial landmarks | |
| cv2.rectangle(face_frame,(shape[54][0], shape[29][1]), #draw rectangle on right and left cheeks | |
| (shape[12][0],shape[33][1]), (0,255,0), 0) | |
| cv2.rectangle(face_frame, (shape[4][0], shape[29][1]), | |
| (shape[48][0],shape[33][1]), (0,255,0), 0) | |
| ROI1 = face_frame[shape[29][1]:shape[33][1], #right cheek | |
| shape[54][0]:shape[12][0]] | |
| ROI2 = face_frame[shape[29][1]:shape[33][1], #left cheek | |
| shape[4][0]:shape[48][0]] | |
| # ROI3 = face_frame[shape[29][1]:shape[33][1], #nose | |
| # shape[31][0]:shape[35][0]] | |
| #get the shape of face for color amplification | |
| rshape = np.zeros_like(shape) | |
| rshape = self.face_remap(shape) | |
| mask = np.zeros((face_frame.shape[0], face_frame.shape[1])) | |
| cv2.fillConvexPoly(mask, rshape[0:27], 1) | |
| # mask = np.zeros((face_frame.shape[0], face_frame.shape[1],3),np.uint8) | |
| # cv2.fillConvexPoly(mask, shape, 1) | |
| #cv2.imshow("face align", face_frame) | |
| # cv2.rectangle(frame,(shape[54][0], shape[29][1]), #draw rectangle on right and left cheeks | |
| # (shape[12][0],shape[54][1]), (0,255,0), 0) | |
| # cv2.rectangle(frame, (shape[4][0], shape[29][1]), | |
| # (shape[48][0],shape[48][1]), (0,255,0), 0) | |
| # ROI1 = frame[shape[29][1]:shape[54][1], #right cheek | |
| # shape[54][0]:shape[12][0]] | |
| # ROI2 = frame[shape[29][1]:shape[54][1], #left cheek | |
| # shape[4][0]:shape[48][0]] | |
| else: | |
| cv2.putText(frame, "No face detected", | |
| (200,200), cv2.FONT_HERSHEY_PLAIN, 1.5, (0, 0, 255),2) | |
| status = False | |
| return frame, face_frame, ROI1, ROI2, status, mask, face_region | |
| # some points in the facial landmarks need to be re-ordered | |
| def face_remap(self,shape): | |
| remapped_image = shape.copy() | |
| # left eye brow | |
| remapped_image[17] = shape[26] | |
| remapped_image[18] = shape[25] | |
| remapped_image[19] = shape[24] | |
| remapped_image[20] = shape[23] | |
| remapped_image[21] = shape[22] | |
| # right eye brow | |
| remapped_image[22] = shape[21] | |
| remapped_image[23] = shape[20] | |
| remapped_image[24] = shape[19] | |
| remapped_image[25] = shape[18] | |
| remapped_image[26] = shape[17] | |
| # neatening | |
| remapped_image[27] = shape[0] | |
| remapped_image = cv2.convexHull(shape) | |
| return remapped_image | |