def test_libsgm_zncc(self):
"""
Test pandora + plugin_libsgm if ZNCC measure is used
"""
# Prepare the configuration
user_cfg = pandora.read_config_file("tests/conf/sgm_zncc.json")
# Import pandora plugins
pandora.import_plugin()
# Instantiate machine
pandora_machine = PandoraMachine()
# Run the pandora pipeline
left, right = pandora.run(pandora_machine, self.left, self.right, -60,
0, user_cfg["pipeline"])
# Compares the calculated left disparity map with the ground truth
# If the disparity maps are not equal, raise an error
if common.strict_error(left["disparity_map"].data[61:-61, 61:-61],
self.disp_left_zncc[61:-61, 61:-61]) > 0:
raise AssertionError
# Compares the calculated right disparity map with the ground truth
# If the disparity maps are not equal, raise an error
if common.strict_error(right["disparity_map"].data,
self.disp_right_zncc) > 0:
raise AssertionError
def test_libsgm_zncc(self):
"""
Test pandora + plugin_libsgm if ZNCC measure is used
"""
# Prepare the configuration
user_cfg = pandora.read_config_file("tests/conf/sgm_zncc_python.json")
# Import pandora plugins
pandora.import_plugin()
# Instantiate machine
pandora_machine = PandoraMachine()
# Run the pandora pipeline
left, right = pandora.run(pandora_machine, self.left, self.right, -60,
0, user_cfg["pipeline"])
# Compares the calculated left disparity map with the ground truth
# If the disparity maps are not equal, raise an error
np.testing.assert_allclose(left["disparity_map"].data,
self.disp_left_zncc,
rtol=1e-04)
# Compares the calculated right disparity map with the ground truth
# If the disparity maps are not equal, raise an error
np.testing.assert_allclose(right["disparity_map"].data,
self.disp_right_zncc,
rtol=1e-04)
def test_libsgm(self):
"""
Test pandora + plugin_libsgm
"""
user_cfg = pandora.read_config_file(
"tests/conf/sgm_python_parall.json")
# Instantiate machine
pandora_machine = PandoraMachine()
# Import pandora plugins
pandora.import_plugin()
# Run the pandora pipeline
left, right = pandora.run(pandora_machine, self.left, self.right, -60,
0, user_cfg)
# Compares the calculated left disparity map with the ground truth
# If the percentage of pixel errors is > 0.20, raise an error
if common.error(left["disparity_map"].data, self.disp_left, 1) > 0.20:
raise AssertionError
# Compares the calculated left disparity map with the ground truth
# If the percentage of pixel errors ( error if ground truth - calculate > 2) is > 0.15, raise an error
if common.error(left["disparity_map"].data, self.disp_left, 2) > 0.15:
raise AssertionError
# Check the left validity mask cross checking ( bit 8 and 9 )
# Compares the calculated validity mask with the ground truth ( occlusion mask )
occlusion = np.ones(
(left["validity_mask"].shape[0], left["validity_mask"].shape[1]))
occlusion[left["validity_mask"].data >= 512] = 0
# If the percentage of errors is > 0.15, raise an error
if common.error_mask(occlusion, self.occlusion) > 0.15:
raise AssertionError
# Compares the calculated right disparity map with the ground truth
# If the percentage of pixel errors is > 0.20, raise an error
if common.error(-1 * right["disparity_map"].data, self.disp_right,
1) > 0.20:
raise AssertionError
# Compares the calculated right disparity map with the ground truth
# If the percentage of pixel errors ( error if ground truth - calculate > 2) is > 0.15, raise an error
if common.error(-1 * right["disparity_map"].data, self.disp_right,
2) > 0.15:
raise AssertionError
def test_libsgm_positive_disparities(self):
"""
Test pandora + plugin_libsgm, with positive disparities
"""
user_cfg = pandora.read_config_file(
"tests/conf/sgm_python_parall.json")
# Import pandora plugins
pandora.import_plugin()
# Instantiate machine
pandora_machine = PandoraMachine()
right, left = pandora.run(pandora_machine, self.right, self.left, 1,
60, user_cfg)
# Compares the calculated left disparity map with the ground truth
# If the percentage of pixel errors is > 0.20, raise an error
if common.error(left["disparity_map"].data, self.disp_left, 1) > 0.20:
raise AssertionError
# Compares the calculated left disparity map with the ground truth
# If the percentage of pixel errors ( error if ground truth - calculate > 2) is > 0.15, raise an error
if common.error(left["disparity_map"].data, self.disp_left, 2) > 0.15:
raise AssertionError
# Compares the calculated right disparity map with the ground truth
# If the percentage of pixel errors is > 0.20, raise an error
if common.error(-1 * right["disparity_map"].data, self.disp_right,
1) > 0.20:
raise AssertionError
# Compares the calculated right disparity map with the ground truth
# If the percentage of pixel errors ( error if ground truth - calculate > 2) is > 0.15, raise an error
if common.error(-1 * right["disparity_map"].data, self.disp_right,
2) > 0.15:
raise AssertionError