我们从Python开源项目中,提取了以下2个代码示例,用于说明如何使用cv2.bitwise_xor()。
def movement(mat_1,mat_2): mat_1_gray = cv2.cvtColor(mat_1.copy(),cv2.COLOR_BGR2GRAY) mat_1_gray = cv2.blur(mat_1_gray,(blur1,blur1)) _,mat_1_gray = cv2.threshold(mat_1_gray,100,255,0) mat_2_gray = cv2.cvtColor(mat_2.copy(),cv2.COLOR_BGR2GRAY) mat_2_gray = cv2.blur(mat_2_gray,(blur1,blur1)) _,mat_2_gray = cv2.threshold(mat_2_gray,100,255,0) mat_2_gray = cv2.bitwise_xor(mat_1_gray,mat_2_gray) mat_2_gray = cv2.blur(mat_2_gray,(blur2,blur2)) _,mat_2_gray = cv2.threshold(mat_2_gray,70,255,0) mat_2_gray = cv2.erode(mat_2_gray,np.ones((erodeval,erodeval))) mat_2_gray = cv2.dilate(mat_2_gray,np.ones((4,4))) _, contours,__ = cv2.findContours(mat_2_gray,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE) if len(contours) > 0:return True #If there were any movements return False #if not #Pedestrian Recognition Thread
def bit_xor(self, frame): self._ndarray = cv2.bitwise_xor(self.ndarray, frame.ndarray) self._contours = None