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Index fix for aug dicts #70

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Index fix for aug dicts #70

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c26b49a
Index fix
ashnair1 Aug 9, 2024
b67ff5b
Add test for dict input
ashnair1 Aug 10, 2024
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13 changes: 10 additions & 3 deletions kornia/augmentation/container/augment.py
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Original file line number Diff line number Diff line change
Expand Up @@ -498,15 +498,22 @@ def __call__(
if len(inputs) == 1 and isinstance(inputs[0], dict):
original_keys, in_data_keys, inputs, invalid_data = self._preproc_dict_data(inputs[0])
else:
in_data_keys = kwargs["data_keys"] if "data_keys" in kwargs else self.data_keys
in_data_keys = kwargs.get("data_keys", self.data_keys)
data_keys = self.transform_op.preproc_datakeys(in_data_keys)

if len(data_keys) > 1 and data_keys.index(DataKey.INPUT):
if len(data_keys) > 1 and DataKey.INPUT in data_keys:
# NOTE: we may update it later for more supports of drawing boxes, etc.
idx = data_keys.index(DataKey.INPUT)
if output_type == "tensor":
self._output_image = _output_image
self._output_image[idx] = self._detach_tensor_to_cpu(_output_image[idx])
if isinstance(_output_image, dict):
self._output_image[original_keys[idx]] = self._detach_tensor_to_cpu(
_output_image[original_keys[idx]]
)
else:
self._output_image[idx] = self._detach_tensor_to_cpu(_output_image[idx])
elif isinstance(_output_image, dict):
self._output_image[original_keys[idx]] = _output_image[original_keys[idx]]
else:
self._output_image[idx] = _output_image[idx]
else:
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22 changes: 22 additions & 0 deletions tests/augmentation/test_augmentation_mix.py
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Original file line number Diff line number Diff line change
Expand Up @@ -520,6 +520,28 @@ def test_data_keys(self, wrapper, device, dtype):
self.assert_close(image_out, image_out2)
self.assert_close(mask_out, mask_out2)

@pytest.mark.parametrize("wrapper", [AugmentationSequential])
def test_dict_input(self, wrapper, device, dtype):
torch.manual_seed(22)
image = torch.rand(4, 3, 10, 10, device=device, dtype=dtype)
mask = torch.randint(0, 2, (4, 10, 10), device=device, dtype=dtype)

f = wrapper(RandomTransplantation(p=1), data_keys=None)
torch.manual_seed(22)
dict_input = {"image": image, "mask": mask}
aug_dict_output = f(dict_input)
torch.manual_seed(22)
dict_input2 = {"mask": mask, "image": image}
aug_dict_output2 = f(dict_input2)

image_out = aug_dict_output["image"]
mask_out = aug_dict_output["mask"]
image_out2 = aug_dict_output2["image"]
mask_out2 = aug_dict_output2["mask"]

self.assert_close(image_out, image_out2)
self.assert_close(mask_out, mask_out2)

@pytest.mark.parametrize("n_spatial", [2, 3])
def test_sequential(self, n_spatial, device, dtype):
torch.manual_seed(22)
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