def stereo_matching(tile, i):
"""
Compute the disparity of a pair of images on a given tile.
Args:
tile: dictionary containing the information needed to process a tile.
i: index of the processed pair
"""
out_dir = os.path.join(tile['dir'], 'pair_{}'.format(i))
x, y = tile['coordinates'][:2]
outputs = ['rectified_mask.png', 'rectified_disp.tif']
if os.path.exists(os.path.join(out_dir, 'stderr.log')):
print('disparity estimation: stderr.log exists')
print('pair_{} not processed on tile {} {}'.format(i, x, y))
return
if cfg['skip_existing'] and all(
os.path.isfile(os.path.join(out_dir, f)) for f in outputs):
print('disparity estimation done on tile {} {} pair {}'.format(
x, y, i))
return
print('estimating disparity on tile {} {} pair {}...'.format(x, y, i))
rect1 = os.path.join(out_dir, 'rectified_ref.tif')
rect2 = os.path.join(out_dir, 'rectified_sec.tif')
disp = os.path.join(out_dir, 'rectified_disp.tif')
mask = os.path.join(out_dir, 'rectified_mask.png')
disp_min, disp_max = np.loadtxt(os.path.join(out_dir, 'disp_min_max.txt'))
block_matching.compute_disparity_map(rect1, rect2, disp, mask,
cfg['matching_algorithm'], disp_min,
disp_max)
# add margin around masked pixels
masking.erosion(mask, mask, cfg['msk_erosion'])
if cfg['clean_intermediate']:
if len(cfg['images']) > 2:
common.remove(rect1)
common.remove(rect2)
common.remove(os.path.join(out_dir, 'disp_min_max.txt'))
def stereo_matching(tile,i):
"""
Compute the disparity of a pair of images on a given tile.
Args:
tile: dictionary containing the information needed to process a tile.
i: index of the processed pair
"""
out_dir = os.path.join(tile['dir'], 'pair_{}'.format(i))
x, y = tile['coordinates'][:2]
outputs = ['rectified_mask.png', 'rectified_disp.tif']
if os.path.exists(os.path.join(out_dir, 'stderr.log')):
print('disparity estimation: stderr.log exists')
print('pair_{} not processed on tile {} {}'.format(i, x, y))
return
if cfg['skip_existing'] and all(os.path.isfile(os.path.join(out_dir, f)) for
f in outputs):
print('disparity estimation done on tile {} {} pair {}'.format(x, y, i))
return
print('estimating disparity on tile {} {} pair {}...'.format(x, y, i))
rect1 = os.path.join(out_dir, 'rectified_ref.tif')
rect2 = os.path.join(out_dir, 'rectified_sec.tif')
disp = os.path.join(out_dir, 'rectified_disp.tif')
mask = os.path.join(out_dir, 'rectified_mask.png')
disp_min, disp_max = np.loadtxt(os.path.join(out_dir, 'disp_min_max.txt'))
block_matching.compute_disparity_map(rect1, rect2, disp, mask,
cfg['matching_algorithm'], disp_min,
disp_max)
# add margin around masked pixels
masking.erosion(mask, mask, cfg['msk_erosion'])
if cfg['clean_intermediate']:
if len(cfg['images']) > 2:
common.remove(rect1)
common.remove(rect2)
common.remove(os.path.join(out_dir,'disp_min_max.txt'))