智能小车opencv巡线代码

以下是智能小车OpenCV巡线代码的示例：

import cv2
import numpy as np

# 设置ROI区域
def roi(img, vertices):
    mask = np.zeros_like(img)
    cv2.fillPoly(mask, vertices, 255)
    masked = cv2.bitwise_and(img, mask)
    return masked

# 处理图像
def process_img(original_image):
    # 转换为灰度图像
    processed_img = cv2.cvtColor(original_image, cv2.COLOR_BGR2GRAY)
    # 高斯模糊
    processed_img = cv2.GaussianBlur(processed_img, (5, 5), 0)
    # 边缘检测
    processed_img = cv2.Canny(processed_img, threshold1=50, threshold2=150)
    # 设置ROI区域
    vertices = np.array([[0, 480], [0, 280], [150, 200], [490, 200], [640, 280], [640, 480]], np.int32)
    processed_img = roi(processed_img, [vertices])
    # 返回处理后的图像
    return processed_img

# 找到直线
def find_lines(img, lines):
    left_line_x = []
    left_line_y = []
    right_line_x = []
    right_line_y = []
    for line in lines:
        for x1, y1, x2, y2 in line:
            slope = (y2 - y1) / (x2 - x1)
            if slope < 0:
                left_line_x.extend([x1, x2])
                left_line_y.extend([y1, y2])
            else:
                right_line_x.extend([x1, x2])
                right_line_y.extend([y1, y2])
    min_y = img.shape[0] * 0.6
    max_y = img.shape[0]
    poly_left = np.poly1d(np.polyfit(left_line_y, left_line_x, deg=1))
    left_x_start = int(poly_left(max_y))
    left_x_end = int(poly_left(min_y))
    poly_right = np.poly1d(np.polyfit(right_line_y, right_line_x, deg=1))
    right_x_start = int(poly_right(max_y))
    right_x_end = int(poly_right(min_y))
    return [[left_x_start, int(max_y), left_x_end, int(min_y)]], [[right_x_start, int(max_y), right_x_end, int(min_y)]]

# 绘制直线
def draw_lines(img, lines):
    line_img = np.zeros((img.shape[0], img.shape[1], 3), dtype=np.uint8)
    for line in lines:
        for x1, y1, x2, y2 in line:
            cv2.line(line_img, (x1, y1), (x2, y2), [0, 255, 0], thickness=5)
    return line_img

# 主函数
def main():
    cap = cv2.VideoCapture(0)
    while True:
        _, frame = cap.read()
        processed_img = process_img(frame)
        lines = cv2.HoughLinesP(processed_img, rho=6, theta=np.pi / 60, threshold=160, lines=np.array([]), minLineLength=40, maxLineGap=25)
        left_line, right_line = find_lines(processed_img, lines)
        line_img = draw_lines(frame, [left_line, right_line])
        result = cv2.addWeighted(frame, 0.9, line_img, 1, 1)
        cv2.imshow("result", result)
        if cv2.waitKey(1) & 0xFF == ord('q'):
            break
    cap.release()
    cv2.destroyAllWindows()

if __name__ == '__main__':
    main()