datasets for stereo depth

1. CRE dateset

# 0,1,2,3
https://data.megengine.org.cn/research/crestereo/dataset/tree/0.tar
https://data.megengine.org.cn/research/crestereo/dataset/shapenet/0.tar
https://data.megengine.org.cn/research/crestereo/dataset/reflective/0.tar
https://data.megengine.org.cn/research/crestereo/dataset/hole/0.tar


def get_disp(disp_path):
    disp = cv2.imread(disp_path, cv2.IMREAD_UNCHANGED)
    return disp.astype(np.float32) / 32

	

2. Falling Things

http://research.nvidia.com/publication/2018-06_Falling-Things
https://drive.google.com/file/d/1y4h9T6D9rf6dAmsRwEtfzJdcghCnI_01/view
[BT](magnet:?xt=urn:btih:5643313104D5000D183250EC341D6291FBC89554)

depth数据 
Depth along the optical axis (in 0.1 mm increments)

估算以及读txt验证 B = 600
f = 480 / tan(32°) = 768.16058349609375

disp = B*f/depth

3. Sceneflow

https://lmb.informatik.uni-freiburg.de/data/SceneFlowDatasets_CVPR16/Release_april16/data/FlyingThings3D/raw_data/flyingthings3d__frames_cleanpass.tar
https://lmb.informatik.uni-freiburg.de/data/SceneFlowDatasets_CVPR16/Release_april16/data/FlyingThings3D/derived_data/flyingthings3d__disparity.tar.bz2

4. Sintel

http://sintel.is.tue.mpg.de/downloads

disp = cv2.imread("disp..", cv2.IMREAD_UNCHANGED).astype(np.float64)
disp_float = disp[:, :, 2] * 4 + disp[:, :, 1] / (2 ** 6) + disp[:, :, 0] / (2 ** 14)

baseline = 10 # cm
fov = 72 
fx = 687 

5.others
[InStereo2K] https://github.com/YuhuaXu/StereoDataset
disp = u16 / 100.

read/write pfm file: https://lmb.informatik.uni-freiburg.de/resources/datasets/IO.py

Read pfm files

import re
import sys
import numpy as np

def read_pfm(filename):
    with open(filename, 'rb') as file:
        # header
        header = file.readline().rstrip()
        if (sys.version[0]) == '3':
            header = header.decode('utf-8')
        if header == 'PF':
            color = True
        elif header == 'Pf':
            color = False
        else:
            raise Exception('Not a PFM file.')

        # width height
        if (sys.version[0]) == '3':
            dim_match = re.match(r'^(\d+)\s(\d+)\s$', file.readline().decode('utf-8'))
        else:
            dim_match = re.match(r'^(\d+)\s(\d+)\s$', file.readline())
        if dim_match:
            width, height = map(int, dim_match.groups())
        else:
            raise Exception('Malformed PFM header.')

        # scale
        if (sys.version[0]) == '3':
            scale = float(file.readline().rstrip().decode('utf-8'))
        else:
            scale = float(file.readline().rstrip())

        # endian
        if scale < 0:  # little-endian
            endian = '<'
            scale = -scale
        else:
            endian = '>'  # big-endian

        # data
        data = np.fromfile(file, endian + 'f')
    shape = (height, width, 3) if color else (height, width)

    data = np.reshape(data, shape)
    data = np.flipud(data)
    return data, scale