def corresponding_roi(rpc1, rpc2, x, y, w, h):
"""
Uses RPC functions to determine the region of im2 associated to the
specified ROI of im1.
Args:
rpc1, rpc2: two instances of the rpcm.RPCModel class, or paths to
the xml files
x, y, w, h: four integers defining a rectangular region of interest
(ROI) in the first view. (x, y) is the top-left corner, and (w, h)
are the dimensions of the rectangle.
Returns:
four integers defining a ROI in the second view. This ROI is supposed
to contain the projections of the 3D points that are visible in the
input ROI.
"""
# read rpc files
if not isinstance(rpc1, rpcm.RPCModel):
rpc1 = rpcm.RPCModel(rpc1)
if not isinstance(rpc2, rpcm.RPCModel):
rpc2 = rpcm.RPCModel(rpc2)
m, M = altitude_range(rpc1, x, y, w, h, 0, 0)
# build an array with vertices of the 3D ROI, obtained as {2D ROI} x [m, M]
a = np.array([x, x, x, x, x + w, x + w, x + w, x + w])
b = np.array([y, y, y + h, y + h, y, y, y + h, y + h])
c = np.array([m, M, m, M, m, M, m, M])
# corresponding points in im2
xx, yy = find_corresponding_point(rpc1, rpc2, a, b, c)[0:2]
# return coordinates of the bounding box in im2
out = common.bounding_box2D(np.vstack([xx, yy]).T)
return np.round(out)
def check_parameters(d):
"""
Check that the provided dictionary defines all mandatory s2p arguments.
Args:
d: python dictionary
"""
# verify that input files paths are defined
if 'images' not in d or len(d['images']) < 2:
print('ERROR: missing paths to input images')
sys.exit(1)
for img in d['images']:
if not dict_has_keys(img, ['img']):
print('ERROR: missing img paths for image', img)
sys.exit(1)
# read RPCs
for img in d['images']:
if 'rpc' in img:
if isinstance(img['rpc'], str): # path to an RPC file
img['rpcm'] = rpcm.rpc_from_rpc_file(img['rpc'])
elif isinstance(img['rpc'], dict): # RPC dict in 'rpcm' format
img['rpcm'] = rpcm.RPCModel(img['rpc'], dict_format='rpcm')
else:
raise NotImplementedError(
'rpc of type {} not supported'.format(type(img['rpc'])))
else:
img['rpcm'] = rpcm.rpc_from_geotiff(img['img'])
# verify that an input ROI is defined
if 'full_img' in d and d['full_img']:
sz = common.image_size_gdal(d['images'][0]['img'])
d['roi'] = {'x': 0, 'y': 0, 'w': sz[0], 'h': sz[1]}
elif 'roi' in d and dict_has_keys(d['roi'], ['x', 'y', 'w', 'h']):
pass
elif 'roi_geojson' in d:
ll_poly = geographiclib.read_lon_lat_poly_from_geojson(
d['roi_geojson'])
d['roi'] = rpc_utils.roi_process(
d['images'][0]['rpcm'],
ll_poly,
use_srtm=d.get('use_srtm'),
exogenous_dem=d.get('exogenous_dem'),
exogenous_dem_geoid_mode=d.get('exogenous_dem_geoid_mode'))
else:
print('ERROR: missing or incomplete roi definition')
sys.exit(1)
# d['roi'] : all the values must be integers
d['roi']['x'] = int(np.floor(d['roi']['x']))
d['roi']['y'] = int(np.floor(d['roi']['y']))
d['roi']['w'] = int(np.ceil(d['roi']['w']))
d['roi']['h'] = int(np.ceil(d['roi']['h']))
# warn about unknown parameters. The known parameters are those defined in
# the global config.cfg dictionary, plus the mandatory 'images' and 'roi'
for k in d.keys():
if k not in ['images', 'roi', 'roi_geojson']:
if k not in cfg:
print('WARNING: ignoring unknown parameter {}.'.format(k))
def fixture_data(tmp_path):
"""
Copy the test data to a temporary directory
"""
img1 = data_path(os.path.join("input_pair", "img_01.tif"))
with rasterio.open(img1) as f:
rpc1 = rpcm.RPCModel(f.tags(ns="RPC"))
shutil.copy(img1, tmp_path / "img_01.tif")
img2 = data_path(os.path.join("input_pair", "img_02.tif"))
with rasterio.open(img2) as f:
rpc2 = rpcm.RPCModel(f.tags(ns="RPC"))
shutil.copy(img2, tmp_path / "img_02.tif")
config = data_path(os.path.join("input_pair", "config.json"))
tmp_config = tmp_path / "config.json"
shutil.copy(config, tmp_config)
return tmp_config, tmp_path, rpc1, rpc2
def check_parameters(d):
"""
Check that the provided dictionary defines all mandatory s2p arguments.
Args:
d: python dictionary
"""
# verify that input files paths are defined
if 'images' not in d or len(d['images']) < 2:
print('ERROR: missing paths to input images')
sys.exit(1)
for img in d['images']:
if not dict_has_keys(img, ['img']):
print('ERROR: missing img paths for image', img)
sys.exit(1)
# read RPCs
for img in d['images']:
if 'rpc' in img:
if isinstance(img['rpc'], str): # path to an RPC file
img['rpcm'] = rpcm.rpc_from_rpc_file(img['rpc'])
elif isinstance(img['rpc'], dict): # RPC dict in 'rpcm' format
img['rpcm'] = rpcm.RPCModel(img['rpc'], dict_format='rpcm')
else:
raise NotImplementedError(
'rpc of type {} not supported'.format(type(img['rpc'])))
else:
img['rpcm'] = rpcm.rpc_from_geotiff(img['img'])
# verify that roi or path to preview file are defined
if 'full_img' in d and d['full_img']:
sz = common.image_size_gdal(d['images'][0]['img'])
d['roi'] = {'x': 0, 'y': 0, 'w': sz[0], 'h': sz[1]}
elif 'roi' in d and dict_has_keys(d['roi'], ['x', 'y', 'w', 'h']):
pass
elif 'roi_utm' in d and dict_has_keys(
d['roi_utm'], ['utm_band', 'hemisphere', 'x', 'y', 'w', 'h']):
d['roi'] = rpc_utils.utm_roi_to_img_roi(d['images'][0]['rpcm'],
d['roi_utm'],
d.get('use_srtm'))
elif 'roi_kml' in d:
# this call defines cfg['utm_zone'] and cfg['utm_bbx'] as side effects
d['roi'] = rpc_utils.kml_roi_process(d['images'][0]['rpcm'],
d['roi_kml'], d.get('utm_zone'),
d.get('use_srtm'))
elif 'roi_geojson' in d:
# this call defines cfg['utm_zone'] and cfg['utm_bbx'] as side effects
d['roi'] = rpc_utils.geojson_roi_process(d['images'][0]['rpcm'],
d['roi_geojson'],
d.get('utm_zone'),
d.get('use_srtm'))
else:
print('ERROR: missing or incomplete roi definition')
sys.exit(1)
# d['roi'] : all the values must be integers
d['roi']['x'] = int(np.floor(d['roi']['x']))
d['roi']['y'] = int(np.floor(d['roi']['y']))
d['roi']['w'] = int(np.ceil(d['roi']['w']))
d['roi']['h'] = int(np.ceil(d['roi']['h']))
# warn about unknown parameters. The known parameters are those defined in
# the global config.cfg dictionary, plus the mandatory 'images' and 'roi' or
# 'roi_utm'
for k in d.keys():
if k not in [
'images', 'roi', 'roi_kml', 'roi_geojson', 'roi_utm',
'utm_zone'
]:
if k not in cfg:
print('WARNING: ignoring unknown parameter {}.'.format(k))