| import cv2 | |
| import numpy as np | |
| from helper.utils import points2array | |
| def blur_all_faces(input_imag,landmark_files): | |
| detector,predictor = landmark_files | |
| msg = None | |
| detections = detector(input_imag, 1) | |
| if len(detections) == 0: | |
| msg = "No faces detected" | |
| return input_imag, msg | |
| canvas = input_imag.copy() | |
| for rect in detections: | |
| landmarks = predictor(input_imag, rect) | |
| landmarks = points2array(landmarks.parts()) | |
| indices = list(range(16)) + [26,25,24,19,18,17,0] | |
| pts = np.array(landmarks)[indices].reshape(-1,1,2) | |
| canvas = cv2.fillPoly(canvas,[pts],(255,255,255)) | |
| canvas = cv2.cvtColor(canvas,cv2.COLOR_BGR2GRAY) | |
| face_mask = cv2.threshold(canvas, 250, 255, cv2.THRESH_BINARY)[1] | |
| face_mask_in = cv2.bitwise_not(face_mask) | |
| blurred_face = cv2.GaussianBlur(input_imag, (37, 37), 150) | |
| blurred_face = cv2.bitwise_and(blurred_face, blurred_face, mask=face_mask_inv) | |
| bg = cv2.bitwise_and(input_imag, input_imag, mask=face_mask_in) | |
| input_img = cv2.bitwise_or(bg,blurred_face) | |
| return input_img,msg | |