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- import pytest
- import paddle
- import patta as tta
-
-
- def test_compose_1():
- transform = tta.Compose(
- [
- tta.HorizontalFlip(),
- tta.VerticalFlip(),
- tta.Rotate90(angles=[0, 90, 180, 270]),
- tta.Scale(scales=[1, 2, 4], interpolation="nearest"),
- ]
- )
-
- assert len(transform) == 2 * 2 * 4 * 3 # all combinations for aug parameters
-
- dummy_label = paddle.ones((2,), paddle.float32).reshape((2, 1))
- dummy_image = paddle.arange(2 * 3 * 4 * 5).reshape((2, 3, 4, 5)).astype(paddle.float32)
- dummy_model = lambda x: {"label": dummy_label, "mask": x}
-
- for augmenter in transform:
- augmented_image = augmenter.augment_image(dummy_image)
- model_output = dummy_model(augmented_image)
- deaugmented_mask = augmenter.deaugment_mask(model_output["mask"])
- deaugmented_label = augmenter.deaugment_label(model_output["label"])
- assert paddle.allclose(deaugmented_mask, dummy_image)
- assert paddle.allclose(deaugmented_label, dummy_label)
-
-
- @pytest.mark.parametrize(
- "case",
- [
- ("mean", 0.5),
- ("gmean", 0.0),
- ("max", 1.0),
- ("min", 0.0),
- ("sum", 1.5),
- ("tsharpen", 0.56903558),
- ],
- )
- def test_merger(case):
- merge_type, output = case
- input = [1.0, 0.0, 0.5]
- merger = tta.base.Merger(type=merge_type, n=len(input))
- for i in input:
- merger.append(paddle.to_tensor(i))
- assert paddle.allclose(merger.result, paddle.to_tensor(output))
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