如何从立体图获取深度图 - KITTI 数据集

Question

After trying example stated in opencv documentation .

When I tried the same code on KITTI image pair I get this:

The code I am using right now looks like this, changing the parameters in StereoBM_create did not help much:

import numpy as np
import cv2
from matplotlib import pyplot as plt

imgL = cv2.imread('000002_left.png',0)
imgR = cv2.imread('000002_right.png',0)

stereo = cv2.StereoBM_create(numDisparities=16, blockSize=15)
#stereo = cv2.StereoBM_create(numDisparities=64, blockSize=17)

disparity = stereo.compute(imgL,imgR)
cv2.imwrite('depth_map.png', disparity)

disp_v2 = cv2.imread('depth_map.png')
disp_v2 = cv2.applyColorMap(disp_v2, cv2.COLORMAP_JET)

plt.imshow(disp_v2)

cv2.imwrite('depth_map_coloured.png', disp_v2)
plt.show()

Question is: How can I make the depth map better?

Answer 1

In my experience, StereoBM (OpenCV) doesn't work with KITTI images. Maybe because KITTI images are much more complex.

But I achieved to get good results using this:

https://github.com/ialhashim/DenseDepth

Answer 2

You should adjust the parameters of the stereo matcher in opencv.

This is a function inside a class I created. It can be seen that I adjust some parameters such as a number of disparities, min disparity etc.:

    def get_stereo_map(self, image_idx):
        left_RGB = self.get_left_RGB(image_idx) # left RGB image
        right_RGB = self.get_right_RGB(image_idx) # right RGB image
        # compute depth map from stereo
        stereo = cv2.StereoBM_create()
        stereo.setMinDisparity(0)
        num_disparities = 16*5
        stereo.setNumDisparities(num_disparities)
        stereo.setBlockSize(15)
        stereo.setSpeckleRange(16)
        # stereo.setSpeckleWindowSize(45)
        stereo_depth_map = stereo.compute(
            cv2.cvtColor(np.array(left_RGB), cv2.COLOR_RGB2GRAY),
            cv2.cvtColor(np.array(right_RGB), cv2.COLOR_RGB2GRAY))
        # by equation + divide by 16 to get true disperities
        stereo_depth_map = (self.storage.focal_pix_RGB * self.storage.baseline_m_RGB) \
                            / (stereo_depth_map/16)
        stereo_depth_map = DataParser.crop_redundant(stereo_depth_map)
        return stereo_depth_map

For full code refer to my repo: https://github.com/janezlapajne/kitty-stereo-dataset-parser Ground truth from lidar and stereo distance map are also included. Hope it helps anyone.