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import cv2
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import dlib
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import numpy as np
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import matplotlib.pyplot as plt
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from imutils import face_utils
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class FaceDetect:
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def __init__(self, pic_path):
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self.pic_path = pic_path
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if pic_path != "":
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self.pic = cv2.imread(self.pic_path, 1).astype(np.uint8)
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def ShowPic(self):
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cv2.imshow('当前图片', self.pic)
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cv2.waitKey(0) # 0一直显示，直到有键盘输入。也可以是其他数字.
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def detectFace(self):
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im = np.float32(self.pic) / 255.0
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# Calculate gradient
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gx = cv2.Sobel(im, cv2.CV_32F, 1, 0, ksize=1)
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gy = cv2.Sobel(im, cv2.CV_32F, 0, 1, ksize=1)
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mag, angle = cv2.cartToPolar(gx, gy, angleInDegrees=True)
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self.facePic = self.pic
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face_detect = dlib.get_frontal_face_detector()
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rects = face_detect(self.pic, 1)
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for (i, rect) in enumerate(rects):
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(x, y, w, h) = face_utils.rect_to_bb(rect)
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self.facePic = cv2.rectangle(self.pic, (x, y), (x + w, y + h), (255, 255, 255), 3)
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cv2.imwrite("img/faceImg/facePic.jpg", self.facePic)
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cv2.waitKey(0) # 0一直显示，直到有键盘输入。也可以是其他数字.
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def videoDetect(self):
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video_capture = cv2.VideoCapture(0)
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face_detect = dlib.get_frontal_face_detector()
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flag = 0
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while True:
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ret, frame = video_capture.read()
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gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
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rects = face_detect(gray, 1)
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for (i, rect) in enumerate(rects):
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(x, y, w, h) = face_utils.rect_to_bb(rect)
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cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
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cv2.imshow('Face detect, Press ESC Quit', frame)
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if cv2.waitKey(3) is 27:
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break
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if cv2.getWindowProperty('Face detect, Press ESC Quit', cv2.WND_PROP_AUTOSIZE) < 1:
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break
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video_capture.release()
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cv2.destroyWindow(self)
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