无法到达左右路边

Question

我试图找到代表道路掩模（二进制图像）左右边缘的点。我尝试过使用轮廓检测，但它给出了整个图像的轮廓（包括上边缘和下边缘，已附加其图像）。

我想要的是2个数组，代表左右道路边缘的点。我得到的是一长串点（轮廓），包括道路的下部。我尝试通过从数组中删除靠近边界的那些点来过滤不必要的点，现在我剩下一个仅包含来自左右道路边缘的点的数组，但现在很难判断哪个点属于哪条路边缘（左或右）。
除此之外，我还使用了索贝尔边缘检测，但它不告诉点，只生成图像。我什至想过对索贝尔边缘检测器的输出应用轮廓检测，但这会导致一些不兼容问题。

代码：

import cv2
import numpy as np

image = cv2.imread('/home/user/Desktop/seg_output/1.jpg')

gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

_, binary_image = cv2.threshold(gray_image, 127, 255, cv2.THRESH_BINARY)


contours, _ = cv2.findContours(binary_image, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

# Sort contours based on their area
contours = sorted(contours, key=cv2.contourArea, reverse=True)

print("Contours: ", np.squeeze(contours[0]))
print("Contours shape: ", len(contours))

contour_image = cv2.drawContours(image.copy(), contours, 0, (0, 255, 0), 2)

print("Output Shape: ", contour_image.shape)

cv2.imshow('Contours', contour_image)
cv2.waitKey(0)
cv2.destroyAllWindows()

输入图像：

输出图像：

Answer 1

可以获取轮廓的坐标并筛选出你想要的，代码如下：

im = cv2.imread('road.jpg')
imGray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
_, thresh = cv2.threshold(imGray, 127, 255, cv2.THRESH_BINARY) # thresholding
contours, _ = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE) # none approximation is better than simple in this case!
largestContour = max(contours, key=cv2.contourArea) # get largest contour
height, width = im.shape[:2] # get shape
X,Y = np.array(contours).T # unpack contour to X and Y coordinates
indicesX = np.where((largestContour[:, :, 0] > 1) & (largestContour[:, :, 0] < width-1)) # get if X higher than 1 and lower than width -1
indicesY = np.where((largestContour[:, :, 1] > 1) & (largestContour[:, :, 1] < height-1))# get if Y higher than 1 and lower than height -1
combinedIndices = np.intersect1d(indicesX[0], indicesY[0]) # intersect indices
filteredContour = largestContour[combinedIndices] # get filtered contour
imContouredWithoutFilter = cv2.drawContours(im.copy(), largestContour, -1, (255, 0, 0), 3) # draw for plot
imContouredWithFilter = cv2.drawContours(im.copy(), filteredContour, -1, (0, 255, 0), 3) # draw for plot
# plotting
fig, ax = plt.subplots(nrows = 1, ncols = 2, sharex = True, sharey = True)
ax[0].imshow(imContouredWithoutFilter)
ax[0].axis("off")
ax[1].imshow(imContouredWithFilter)
ax[1].axis("off")
plt.show()

本例中最相关的行是使用

np.where

和

np.intersect1d

的地方。

以下是结果（左侧未过滤，右侧已过滤）：