lane_detect.py 文件源码

def run_step(self, img, thrs1, thrs2, debug):
        self.lines = []
        self.lines2 = []
        height, width, c = img.shape
        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

        if(self.previous_mask_left == None):
            self.previous_mask_left = np.zeros((height, width, 1), np.uint8)
        if(self.previous_mask_right == None):
            self.previous_mask_right = np.zeros((height, width, 1), np.uint8)
        self.edge = cv2.Canny(gray, thrs1, thrs2, apertureSize=5)
        self.masked_edges_left, self.current_mask_left, self.previous_mask_left, self.left_line \
            = self.update_edge_mask(self.previous_mask_left, self.left_line, -1, thrs1, thrs2, debug)
        self.masked_edges_right, self.current_mask_right, self.previous_mask_right, self.right_line \
            = self.update_edge_mask(self.previous_mask_right, self.right_line, 1, thrs1, thrs2, debug)

        self.segment_history = self.boxes
        self.boxes = [find_lane_markers(self.masked_edges_left), find_lane_markers(self.masked_edges_right)]
        self.eps = [ep[-2:] + combine_eps(cur, past)[:2] for cur, past, ep in zip(self.boxes, self.segment_history, self.eps)]
        self.depth_pairs = [(a, b) for eps in self.eps for ep in eps if len(ep) > 0 for a, b in zip(ep[0], ep[1])[:2]]