请编写python基于相位编组的直线检测

以下是基于相位编组的直线检测的Python代码：

import cv2
import numpy as np

# 读取测试图像
img = cv2.imread('test_img.png', cv2.COLOR_BGR2GRAY)
img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)

# 计算图像的梯度
edge_x = cv2.Sobel(img, cv2.CV_64F, 1, 0)
edge_y = cv2.Sobel(img, cv2.CV_64F, 0, 1)
mag = np.sqrt(edge_x ** 2 + edge_y ** 2)
ang = np.arctan2(edge_y, edge_x)

# 参数设置
thres = 100
min_line_len = 300
max_line_gap = 50

# 相位编组
bins = int(np.pi / 2.0 * 100)  # 0-90度，每度为100个bin
hist = np.zeros(bins, np.float32)
for i in range(mag.shape[0]):
    for j in range(mag.shape[1]):
        h = int((ang[i, j] + np.pi / 2.0) / np.pi * 180.0 * 100)
        hist[h] += mag[i, j]

# 非极大值抑制
for i in range(1, bins-1):
    if hist[i] > hist[i-1] and hist[i] > hist[i+1]:
        hist[i] = hist[i] - np.mean(hist[max(0, i-5):min(i+6, bins-1)])
    else:
        hist[i] = 0

# 阈值处理
peak_val = np.max(hist) * 0.5
idx = np.where(hist > peak_val)[0]
if len(idx) == 0:
    print("No lines detected.")
    exit(0)

# 找到直线的角度
bin_width = np.pi / bins
angle = (idx + 0.5) * bin_width - np.pi / 2.0

# 绘制检测到的直线
for a in angle:
    a_deg = a / np.pi * 180.0
    print('检测到直线，角度 =', a_deg)
    a_rad = a + np.pi / 2.0
    x0 = np.cos(a_rad)
    y0 = np.sin(a_rad)
    x1 = int(x0 * 1000 + img.shape[1] / 2)
    y1 = int(y0 * 1000 + img.shape[0] / 2)
    x2 = int(x0 * -1000 + img.shape[1] / 2)
    y2 = int(y0 * -1000 + img.shape[0] / 2)
    cv2.line(img, (x1, y1), (x2, y2), (0, 255, 0), 2)
     
# 显示结果
cv2.imshow("Result", img)
cv2.waitKey(0)

其中，`test_img.png` 是要进行直线检测的图像。这个程序首先计算了图像的梯度，然后使用相位编组的方法进行直线检测。最后，检测到的直线将在原始图像上用绿线绘制出来。