车道线检测matlab代码lane detect

import cv2 import numpy as np import matplotlib.pyplot as plt #读取图片 img = cv2.imread("test_images/straight_lines1.jpg") cv2.imshow("img", img) #转换为灰度图像 img_gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY) cv2.imshow("img_gray", img_gray) #高斯滤波 img_gaussian = cv2.GaussianBlur(img_gray, (11, 11), 0.0) cv2.imshow("img_gaussian", img_gaussian) #Canny算法，边缘检测 img_edge = cv2.Canny(img_gaussian, 90, 180) cv2.imshow("img_edge", img_edge) #感兴趣区域提取 plt.imshow(img) #plt.show() mask = np.zeros_like(img_edge) vertices = np.array([[220, 670], [610, 410], [650, 410], [1100, 670]]) cv2.fillPoly(mask, [vertices], 255) img_edge_roi = cv2.bitwise_and(img_edge, mask) cv2.imshow('img_edge_roi', img_edge_roi) #直线检测 lines = cv2.HoughLinesP(img_edge_roi, 1, np.pi/180, 20, minLineLength = 10, maxLineGap = 10) #print(lines.shape) #画线 img_line = np.zeros_like(img) for line in lines: for x1, y1, x2, y2 in line: cv2.line(img_line, (x1, y1), (x2, y2), [0, 0, 255], 2) cv2.imshow('img_line', img_line) #去除斜率差异较大的线段 def clean_lines(lines, threshold): #计算斜率 slope = [(y2 - y1) / (x2 - x1) for line in lines for x1, x2, y1, y2 in line] while(len(slope) > 0): #计算斜率平均值 mean = np.mean(slope) #计算差值 diff = [abs(s - mean) for s in slope] #找出差值最大的下标 index = np.argmax(diff) # 如果下标对应的差值大于threshold就删去该线段 if diff[index] > threshold: slope.pop(index) lines.pop(index) else: break #拟合直线，计算车道线端点 def cal_lane_vertices(point_list, y_start, y_end): x = [p[0] for p in point_list] y = [p[1] for p in point_list] # 一次函数拟合,fit为(k, b) fit = np.polyfit(y, x, 1) #得到x = ky + b fit_fn = np.poly1d(fit) x_start = int(fit_fn(y_start)) x_end = int(fit_fn(y_end)) return [(x_start, y_start), (x_end, y_end)] #画车道线 def draw_lanes(img, lines, color = [0, 0, 255]): #左线段列表 right_lines = [] #右线段列表 left_lines = [] # 1.根据斜率分左右线段 for line in lines: for x1, y1, x2, y2 in line: if y2 - y1 != 0 and x2 - x1 != 0: #计算斜率 slope = (y2 - y1) / (x2 - x1) if slope > 0: right_lines.append(line) else: left_lines.append(line) if (len(left_lines) <= 0 or len(right_lines) <= 0): return img #2.去除斜率差异过大的线段 clean_lines(right_lines, 0.1) clean_lines(left_lines, 0.1) #3.直线拟合 left_points = [(x1, y1) for line in left_lines for x1, y1, x2, y2 in line] left_points = left_points + [(x2, y2) for line in left_lines for x1, y1, x2, y2 in line] right_points = [(x1, y1) for line in right_lines for x1, y1, x2, y2 in line] right_points = right_points + [(x2, y2) for line in right_lines for x1, y1, x2, y2 in line] #计算车道线端点 left_vertices = cal_lane_vertices(left_points, img.shape[0] - 50, 450) right_vertices = cal_lane_vertices(right_points, img.shape[0] - 50, 450) #以矩形的形式拟合 vertices = np.array([left_vertices[0], left_vertices[1], right_vertices[1], right_vertices[0]]) cv2.fillPoly(img, [vertices], color) return img img_lane = draw_lanes(img, lines, color = [0, 0, 255]) cv2.imshow('img_lane', img_lane) cv2.waitKey(-1)