Python OpenCV车道线识别侦测

Python OpenCV车道线识别侦测

运行结果如下：

代码如下：

import cv2 as cv
import numpy as np


def do_canny(frame):
    gray = cv.cvtColor(frame, cv.COLOR_RGB2GRAY)
    blur = cv.GaussianBlur(gray, (5, 5), 0)
    canny = cv.Canny(blur, 50, 150)
    return canny

def do_segment(frame):
    height = frame.shape[0]
    polygons = np.array([
                            [(0, height), (800, height), (380, 290)]
                        ])
    mask = np.zeros_like(frame)
    cv.fillPoly(mask, polygons, 255)
    segment = cv.bitwise_and(frame, mask)
    return segment

def calculate_lines(frame, lines):
    left = []
    right = []
    for line in lines:
        x1, y1, x2, y2 = line.reshape(4)
        slope = parameters[0]
        y_intercept = parameters[1]
        
        if slope < 0:
            left.append((slope, y_intercept))
        else:
            right.append((slope, y_intercept))
    
    left_avg = np.average(left, axis = 0)
    right_avg = np.average(right, axis = 0)
   
    left_line = calculate_coordinates(frame, left_avg)
    right_line = calculate_coordinates(frame, right_avg)
    return np.array([left_line, right_line])

def calculate_coordinates(frame, parameters):
    slope, intercept = parameters
    y1 = frame.shape[0]
    y2 = int(y1 - 150)
    return np.array([x1, y1, x2, y2])

cap = cv.VideoCapture("input.mp4")
while (cap.isOpened()):
    ret, frame = cap.read()
    canny = do_canny(frame)
    cv.imshow("canny", canny)
    
    segment = do_segment(canny)
    hough = cv.HoughLinesP(segment, 2, np.pi / 180, 100, np.array([]), minLineLength = 100, maxLineGap = 50)
    
    lines = calculate_lines(frame, hough)
    lines_visualize = visualize_lines(frame, lines)
    cv.imshow("hough", lines_visualize)
    output = cv.addWeighted(frame, 0.9, lines_visualize, 1, 1)
    cv.imshow("output", output)
    if cv.waitKey(10) & 0xFF == ord(q):
        break
cap.release()
cv.destroyAllWindows()

运行结果如下：

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