Question

您好我是学生，我尝试为签名制作三维地图重建，并按照“OpenCV with Python by Example”一书中的示例，我不知道为什么，或者如何解决这个错误。我收到了这个错误，请帮助我。

这是代码：

import argparse
import cv2
import numpy as np
def build_arg_parser():
    parser = argparse.ArgumentParser(description='Reconstruct the 3D map from \the two input stereo images. Output will be saved in\'output.ply\'')
    parser.add_argument("--image-left", dest="image_left", required=True,
    help="Input image captured from the left")
    parser.add_argument("--image-right", dest="image_right", required=True,
    help="Input image captured from the right")
    parser.add_argument("--output-file", dest="output_file", required=True,
    help="Output filename (without the extension) where the point cloud will be saved")
    return parser
def create_output(vertices, colors, filename):
    colors = colors.reshape(-1, 3)
    vertices = np.hstack([vertices.reshape(-1,3), colors])
    ply_header = '''ply
    format ascii 1.0
    element vertex %(vert_num)d
    property float x
    property float y
    property float z
    property uchar red
    property uchar green
    property uchar blue
    end_header
    '''
    with open(filename, 'w') as f:
        f.write(ply_header % dict(vert_num=len(vertices)))
        np.savetxt(f, vertices, '%f %f %f %d %d %d')
if __name__ == '__main__':
    args = build_arg_parser().parse_args()
    image_left = cv2.imread(args.image_left)
    image_right = cv2.imread(args.image_right)
    output_file = args.output_file + '.ply'
if image_left.shape[0] != image_right.shape[0] or \
    image_left.shape[1] != image_right.shape[1]:
    raise TypeError("Input images must be of the same size")
# downscale images for faster processing
image_left = cv2.pyrDown(image_left)
image_right = cv2.pyrDown(image_right)
# disparity range is tuned for 'aloe' image pair
win_size = 1
min_disp = 16
max_disp = min_disp * 9
num_disp = max_disp - min_disp# Needs to be divisible by 16
stereo = cv2.StereoSGBM(minDisparity = min_disp,
    numDisparities = num_disp,
    SADWindowSize = win_size,
    uniquenessRatio = 10,
    speckleWindowSize = 100,
    speckleRange = 32,
    disp12MaxDiff = 1,
    P1 = 8*3*win_size**2,
    P2 = 32*3*win_size**2,
    fullDP = True
)
print "\nComputing the disparity map..."
disparity_map = stereo.compute(image_left,image_right).astype(np.float32) /16.0
print "\nGenerating the 3D map..."
h, w = image_left.shape[:2]
focal_length = 0.8*w
# Perspective transformation matrix
Q = np.float32([[1, 0, 0, -w/2.0],
               [0,-1, 0, h/2.0],
               [0, 0, 0, -focal_length],
               [0, 0, 1, 0]])
points_3D = cv2.reprojectImageTo3D(disparity_map, Q)
colors = cv2.cvtColor(image_left, cv2.COLOR_BGR2RGB)
mask_map = disparity_map > disparity_map.min()
output_points = points_3D[mask_map]
output_colors = colors[mask_map]
print "\nCreating the output file...\n"
create_output(output_points, output_colors, output_file)

这是我在控制台中收到的错误：

Computing the disparity map...
   Traceback (most recent call last):
      File "rec.py", line 58, in <module>
disparity_map = stereo.compute(image_left,image_right).astype(np.float32) / 16.0
TypeError: Incorrect type of self (must be 'StereoMatcher' or its derivative)

Answer 1

你应该使用：

stereo = cv2.StereoSGBM_create(
    minDisparity = min_disp,
    numDisparities = num_disp,
    SADWindowSize = win_size,
    uniquenessRatio = 10,
    speckleWindowSize = 100,
    speckleRange = 32,
    disp12MaxDiff = 1,
    P1 = 8*3*win_size**2,
    P2 = 32*3*win_size**2,
    fullDP = True
)

构建3D Map Python

1 个答案: