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Fix affine balanxced scale 1 #2005

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Oct 21, 2024
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2 changes: 1 addition & 1 deletion .pre-commit-config.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -81,7 +81,7 @@ repos:
hooks:
- id: pyproject-fmt
- repo: https://github.com/pre-commit/mirrors-mypy
rev: v1.12.0
rev: v1.12.1
hooks:
- id: mypy
files: ^albumentations/
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42 changes: 25 additions & 17 deletions albumentations/augmentations/geometric/transforms.py
Original file line number Diff line number Diff line change
Expand Up @@ -756,28 +756,36 @@ def apply_to_keypoints(

@staticmethod
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def get_scale(
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scale: dict[str, tuple[float, float]],
scale: dict[str, float | tuple[float, float]],
keep_ratio: bool,
balanced_scale: bool,
) -> fgeometric.ScaleDict:
result_scale = {}
if balanced_scale:
for key, value in scale.items():
lower_interval = (value[0], 1.0) if value[0] < 1 else None
upper_interval = (1.0, value[1]) if value[1] > 1 else None

if lower_interval is not None and upper_interval is not None:
selected_interval = random.choice([lower_interval, upper_interval])
elif lower_interval is not None:
selected_interval = lower_interval
elif upper_interval is not None:
selected_interval = upper_interval
for key, value in scale.items():
if isinstance(value, (int, float)):
result_scale[key] = float(value)
elif isinstance(value, tuple):
if balanced_scale:
lower_interval = (value[0], 1.0) if value[0] < 1 else None
upper_interval = (1.0, value[1]) if value[1] > 1 else None

if lower_interval is not None and upper_interval is not None:
selected_interval = random.choice([lower_interval, upper_interval])
elif lower_interval is not None:
selected_interval = lower_interval
elif upper_interval is not None:
selected_interval = upper_interval
else:
result_scale[key] = 1.0
continue

result_scale[key] = random.uniform(*selected_interval)
else:
raise ValueError(f"Both lower_interval and upper_interval are None for key: {key}")

result_scale[key] = random.uniform(*selected_interval)
else:
result_scale = {key: random.uniform(*value) for key, value in scale.items()}
result_scale[key] = random.uniform(*value)
else:
raise TypeError(
f"Invalid scale value for key {key}: {value}. Expected a float or a tuple of two floats.",
)

if keep_ratio:
result_scale["y"] = result_scale["x"]
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34 changes: 34 additions & 0 deletions tests/functional/test_affine.py
Original file line number Diff line number Diff line change
Expand Up @@ -846,3 +846,37 @@ def test_rotate_by_90_bboxes_symmetric_bbox(transform_class, transform_params, f
bbox_out1 = transform(image=img, bboxes=[bbox], cl=[0])["bboxes"][0]

np.testing.assert_allclose(bbox_out1, bbox, atol=1e-6)



@pytest.mark.parametrize("scale, keep_ratio, balanced_scale, expected", [
({"x": 1, "y": 1}, False, False, {"x": 1, "y": 1}),
({"x": 1, "y": 1}, True, False, {"x": 1, "y": 1}),
({"x": (0.5, 1.5), "y": (0.5, 1.5)}, False, False, {"x": pytest.approx(1, abs=0.5), "y": pytest.approx(1, abs=0.5)}),
({"x": (0.5, 1.5), "y": (0.5, 1.5)}, True, False, lambda x: x["x"] == x["y"] and 0.5 <= x["x"] <= 1.5),
({"x": (0.5, 1.5), "y": (0.5, 1.5)}, False, True, lambda x: all(0.5 <= v <= 1.5 for v in x.values())),
({"x": (0.5, 2.0), "y": 1}, False, False, lambda x: 0.5 <= x["x"] <= 2.0 and x["y"] == 1),
({"x": 0.5, "y": (0.5, 1.5)}, True, False, lambda x: x["x"] == 0.5 and x["y"] == 0.5),
({"x": (0.8, 1.2), "y": (0.8, 1.2)}, False, True, lambda x: all(0.8 <= v <= 1.2 for v in x.values())),
])
def test_get_scale(scale, keep_ratio, balanced_scale, expected):
result = A.Affine.get_scale(scale, keep_ratio, balanced_scale)

if callable(expected):
assert expected(result)
else:
assert result == expected
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def test_get_scale_balanced_scale_behavior():
scale = {"x": (0.5, 2.0), "y": (0.5, 2.0)}
result = A.Affine.get_scale(scale, keep_ratio=False, balanced_scale=True)

assert all(0.5 <= v <= 2.0 for v in result.values())
assert any(v < 1.0 for v in result.values()) or any(v > 1.0 for v in result.values())

def test_get_scale_keep_ratio():
scale = {"x": (0.5, 1.5), "y": (0.8, 1.2)}
result = A.Affine.get_scale(scale, keep_ratio=True, balanced_scale=False)

assert result["x"] == result["y"]
assert 0.5 <= result["x"] <= 1.5
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