def heights_fusion(tile):
"""
Merge the height maps computed for each image pair and generate a ply cloud.
Args:
tile: a dictionary that provides all you need to process a tile
"""
tile_dir = tile['dir']
height_maps = [os.path.join(tile_dir, 'pair_%d' % (i + 1), 'height_map.tif')
for i in range(len(cfg['images']) - 1)]
# remove spurious matches
if cfg['cargarse_basura']:
for img in height_maps:
common.cargarse_basura(img, img)
# load global mean heights
global_mean_heights = []
for i in range(len(cfg['images']) - 1):
x = np.loadtxt(os.path.join(cfg['out_dir'],
'global_mean_height_pair_{}.txt'.format(i+1)))
global_mean_heights.append(x)
# merge the height maps (applying mean offset to register)
fusion.merge_n(os.path.join(tile_dir, 'height_map.tif'), height_maps,
global_mean_heights, averaging=cfg['fusion_operator'],
threshold=cfg['fusion_thresh'])
if cfg['clean_intermediate']:
for f in height_maps:
common.remove(f)
def heights_fusion(tile):
"""
Merge the height maps computed for each image pair and generate a ply cloud.
Args:
tile: a dictionary that provides all you need to process a tile
"""
tile_dir = tile['dir']
height_maps = [os.path.join(tile_dir, 'pair_%d' % (i + 1), 'height_map.tif')
for i in range(len(cfg['images']) - 1)]
# remove spurious matches
if cfg['cargarse_basura']:
for img in height_maps:
common.cargarse_basura(img, img)
# load global mean heights
global_mean_heights = []
for i in range(len(cfg['images']) - 1):
x = np.loadtxt(os.path.join(cfg['out_dir'],
'global_mean_height_pair_{}.txt'.format(i+1)))
global_mean_heights.append(x)
# merge the height maps (applying mean offset to register)
fusion.merge_n(os.path.join(tile_dir, 'height_map.tif'), height_maps,
global_mean_heights, averaging=cfg['fusion_operator'],
threshold=cfg['fusion_thresh'])
if cfg['clean_intermediate']:
for f in height_maps:
common.remove(f)
def heights_fusion(tile, mean_heights_global):
"""
Merge the height maps computed for each image pair and generate a ply cloud.
Args:
tile: a dictionary that provides all you need to process a tile
mean_heights_global: list containing the means of all the global height
maps
"""
tile_dir = tile['dir']
nb_pairs = len(mean_heights_global)
height_maps = [
os.path.join(tile_dir, 'pair_%d' % (i + 1), 'height_map.tif')
for i in range(nb_pairs)
]
# remove spurious matches
if cfg['cargarse_basura']:
for img in height_maps:
common.cargarse_basura(img, img)
# merge the height maps (applying mean offset to register)
fusion.merge_n(os.path.join(tile_dir, 'height_map.tif'),
height_maps,
mean_heights_global,
averaging=cfg['fusion_operator'],
threshold=cfg['fusion_thresh'])
if cfg['clean_intermediate']:
for f in height_maps:
common.remove(f)
