def compute_tiles_coordinates(rx, ry, rw, rh, tw, th, z=1):
"""
"""
out = []
neighborhood_dict = dict()
for y in np.arange(ry, ry + rh, th):
h = min(th, ry + rh - y)
for x in np.arange(rx, rx + rw, tw):
w = min(tw, rx + rw - x)
# ensure that tile coordinates are multiples of the zoom factor
x, y, w, h = common.round_roi_to_nearest_multiple(z, x, y, w, h)
out.append((x, y, w, h))
# get coordinates of tiles from neighborhood
out2 = []
for y2 in [y - th, y, y + th]:
h2 = min(th, ry + rh - y2)
for x2 in [x - tw, x, x + tw]:
w2 = min(tw, rx + rw - x2)
if rx + rw > x2 >= rx:
if ry + rh > y2 >= ry:
x2, y2, w2, h2 = common.round_roi_to_nearest_multiple(
z, x2, y2, w2, h2)
out2.append((x2, y2, w2, h2))
neighborhood_dict[str((x, y, w, h))] = out2
return out, neighborhood_dict
def compute_tiles_coordinates(rx, ry, rw, rh, tw, th, z=1):
"""
"""
out = []
neighborhood_dict = dict()
for y in np.arange(ry, ry + rh, th):
h = min(th, ry + rh - y)
for x in np.arange(rx, rx + rw, tw):
w = min(tw, rx + rw - x)
# ensure that tile coordinates are multiples of the zoom factor
x, y, w, h = common.round_roi_to_nearest_multiple(z, x, y, w, h)
out.append((x, y, w, h))
# get coordinates of tiles from neighborhood
out2 = []
for y2 in [y - th, y, y + th]:
h2 = min(th, ry + rh - y2)
for x2 in [x - tw, x, x + tw]:
w2 = min(tw, rx + rw - x2)
if rx + rw > x2 >= rx:
if ry + rh > y2 >= ry:
x2, y2, w2, h2 = common.round_roi_to_nearest_multiple(z, x2, y2, w2, h2)
out2.append((x2, y2, w2, h2))
neighborhood_dict[str((x, y, w, h))] = out2
return out, neighborhood_dict
def build_cfg(user_cfg):
"""
Populate a dictionary containing the s2p parameters from a user config file.
This dictionary is contained in the global variable 'cfg' of the config
module.
Args:
user_cfg: user config dictionary
"""
# check that all the mandatory arguments are defined
check_parameters(user_cfg)
# fill the config module: updates the content of the config.cfg dictionary
# with the content of the user_cfg dictionary
cfg.update(user_cfg)
# sets keys 'clr', 'cld' and 'roi' of the reference image to None if they
# are not already defined. The default values of these optional arguments
# can not be defined directly in the config.py module. They would be
# overwritten by the previous update, because they are in a nested dict.
cfg['images'][0].setdefault('clr')
cfg['images'][0].setdefault('cld')
cfg['images'][0].setdefault('roi')
cfg['images'][0].setdefault('wat')
# Make sure that input data have absolute paths
for i in range(0, len(cfg['images'])):
for d in ['clr', 'cld', 'roi', 'wat', 'img', 'rpc']:
if d in cfg['images'][i] and cfg['images'][i][d] is not None:
cfg['images'][i][d] = os.path.abspath(cfg['images'][i][d])
# check the zoom factor
z = cfg['subsampling_factor']
assert (z > 0 and z == np.floor(z))
# ensure that the coordinates of the ROI are multiples of the zoom factor,
# to avoid bad registration of tiles due to rounding problems.
x = cfg['roi']['x']
y = cfg['roi']['y']
w = cfg['roi']['w']
h = cfg['roi']['h']
x, y, w, h = common.round_roi_to_nearest_multiple(z, x, y, w, h)
cfg['roi'] = {'x': x, 'y': y, 'w': w, 'h': h}
# if srtm is disabled set disparity range method to sift
if 'disable_srtm' in cfg and cfg['disable_srtm']:
cfg['disp_range_method'] = 'sift'
# get utm zone
if 'utm_zone' not in cfg or cfg['utm_zone'] is None:
cfg['utm_zone'] = rpc_utils.utm_zone(cfg['images'][0]['rpc'], x, y, w,
h)
def build_cfg(user_cfg):
"""
Populate a dictionary containing the s2p parameters from a user config file.
This dictionary is contained in the global variable 'cfg' of the config
module.
Args:
user_cfg: user config dictionary
"""
# check that all the mandatory arguments are defined
check_parameters(user_cfg)
# fill the config module: updates the content of the config.cfg dictionary
# with the content of the user_cfg dictionary
cfg.update(user_cfg)
# sets keys 'clr', 'cld' and 'roi' of the reference image to None if they
# are not already defined. The default values of these optional arguments
# can not be defined directly in the config.py module. They would be
# overwritten by the previous update, because they are in a nested dict.
cfg['images'][0].setdefault('clr')
cfg['images'][0].setdefault('cld')
cfg['images'][0].setdefault('roi')
cfg['images'][0].setdefault('wat')
# Make sure that input data have absolute paths
for i in range(0,len(cfg['images'])):
for d in ['clr','cld','roi','wat','img','rpc']:
if d in cfg['images'][i] and cfg['images'][i][d] is not None:
cfg['images'][i][d] = os.path.abspath(cfg['images'][i][d])
# check the zoom factor
z = cfg['subsampling_factor']
assert(z > 0 and z == np.floor(z))
# ensure that the coordinates of the ROI are multiples of the zoom factor,
# to avoid bad registration of tiles due to rounding problems.
x = cfg['roi']['x']
y = cfg['roi']['y']
w = cfg['roi']['w']
h = cfg['roi']['h']
x, y, w, h = common.round_roi_to_nearest_multiple(z, x,y, w, h)
cfg['roi'] = {'x': x, 'y': y, 'w': w, 'h': h}
# if srtm is disabled set disparity range method to sift
if 'disable_srtm' in cfg and cfg['disable_srtm']:
cfg['disp_range_method'] = 'sift'
# get utm zone
if 'utm_zone' not in cfg or cfg['utm_zone'] is None:
cfg['utm_zone'] = rpc_utils.utm_zone(cfg['images'][0]['rpc'], x, y, w, h)
def compute_tiles_coordinates(rx, ry, rw, rh, tw, th, z=1):
"""
"""
out = []
for y in np.arange(ry, ry + rh, th):
h = min(th, ry + rh - y)
for x in np.arange(rx, rx + rw, tw):
w = min(tw, rx + rw - x)
# ensure that tile coordinates are multiples of the zoom factor
x, y, w, h = common.round_roi_to_nearest_multiple(z, x, y, w, h)
out.append((x, y, w, h))
return out