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assert_array_equal(S, S_exp)
img.astype(float)
img_float.astype(img_type)
max_tree(img_float, connectivity=2)
assert_array_equal(P, P_exp)
assert_array_equal(S, S_exp)
test_area_closing(self)
Closing (2 thresholds, all types)
_full_type_test(img, 2, expected_2, area_closing, connectivity=2)
_full_type_test(img, 4, expected_4, area_closing, connectivity=2)
max_tree(invert(img)
test_area_opening(self)
Opening (2 thresholds, all types)
_full_type_test(img, 2, expected_2, area_opening, connectivity=2)
_full_type_test(img, 4, expected_4, area_opening, connectivity=2)
max_tree(img, connectivity=2)
test_diameter_closing(self)
Opening (2 thresholds, all types)
_full_type_test(img, 2, ex2, diameter_closing, connectivity=2)
_full_type_test(img, 4, ex4, diameter_closing, connectivity=2)
max_tree(invert(img)
test_diameter_opening(self)
Opening (2 thresholds, all types)
_full_type_test(img, 2, ex2, diameter_opening, connectivity=2)
_full_type_test(img, 4, ex4, diameter_opening, connectivity=2)
max_tree(img, connectivity=2)
test_local_maxima(self)
data.astype(dtype)
max_tree_local_maxima(test_data, connectivity=1)
assert_array_equal(expected_result, out_bin)
np.max(out)
max_tree(test_data)
assert_array_equal(expected_result, out_bin)
np.max(out)
test_extrema_float(self)
max_tree_local_maxima(data, connectivity=1)
assert_array_equal(expected_result, out_bin)
np.max(out)
test_3d(self)
np.zeros((8, 8, 8)
np.zeros((8, 8, 8)
max_tree_local_maxima(img)
assert_array_equal(local_maxima, out_bin)
np.max(out)
URISC(Dataset)
super(URISC, self)
__init__()
transforms.Normalize(mean=0.520, std=0.185)
transforms.Normalize(mean=0.518, std=0.190)
transforms.ToTensor()
os.path.join(dir, data_rank, mode, filename)
os.listdir(os.path.join(dir, data_rank, mode)
RuntimeError(f'No input file found in {os.path.join(dir, data_rank, mode)
logging.info(f'Creating dataset with {len(self.ids)
__len__(self)
len(self.ids)
__getitem__(self, idx)
cv2.imread(self.ids[idx])
print(image.shape)
self.transform(image=image)
image.float()
contiguous()
replace(self.mode, "label/"+self.mode)
cv2.imread(mask_path, cv2.IMREAD_GRAYSCALE)
print(mask)
self.transform(image=image, mask=mask)
self.transform_totensor(transformed_image)
self.transform_normalize(transformed_image)
self.transform_totensor(transformed_mask)
np.transpose(transformed_image, (2, 0, 1)
np.expand_dims(transformed_mask, axis=0)
Copyright (C)
FeatureMatchingLoss(nn.Module)
__init__(self, criterion='l1')
super(FeatureMatchingLoss, self)
__init__()
nn.L1Loss()
nn.MSELoss()
ValueError('Criterion %s is not recognized' % criterion)
forward(self, fake_features, real_features)
fake_features (list of lists)
real_features (list of lists)
len(fake_features)
new_tensor(0)
range(num_d)
range(len(fake_features[i])
detach()
logging.getLogger(__name__)
CONF.import_opt('driver_use_ssl', 'cinder.volume.driver')
CONF.register_opts(d_opts, group=configuration.SHARED_CONF_GROUP)
six.add_metaclass(utils.TraceWrapperWithABCMetaclass)
DateraDriver(san.SanISCSIDriver, api2.DateraApi, api21.DateraApi)
format(VERSION)
TODO(jsbryant)
__init__(self, *args, **kwargs)
super(DateraDriver, self)
__init__(*args, **kwargs)
self.configuration.append_config_values(d_opts)
str(uuid.uuid4()
utils.setup_tracing(['method'])