imports: deprecate from pkg root [3/n] Image (#1696)

src/torchmetrics/__init__.py

@@ -47,18 +47,24 @@
 from torchmetrics.collections import MetricCollection  # noqa: E402
 from torchmetrics.detection._deprecated import _ModifiedPanopticQuality as ModifiedPanopticQuality  # noqa: E402
 from torchmetrics.detection._deprecated import _PanopticQuality as PanopticQuality  # noqa: E402
-from torchmetrics.image import (  # noqa: E402
-    ErrorRelativeGlobalDimensionlessSynthesis,
-    MultiScaleStructuralSimilarityIndexMeasure,
-    PeakSignalNoiseRatio,
-    RelativeAverageSpectralError,
-    RootMeanSquaredErrorUsingSlidingWindow,
-    SpectralAngleMapper,
-    SpectralDistortionIndex,
-    StructuralSimilarityIndexMeasure,
-    TotalVariation,
-    UniversalImageQualityIndex,
+from torchmetrics.image._deprecated import (  # noqa: E402
+    _ErrorRelativeGlobalDimensionlessSynthesis as ErrorRelativeGlobalDimensionlessSynthesis,
 )
+from torchmetrics.image._deprecated import (  # noqa: E402
+    _MultiScaleStructuralSimilarityIndexMeasure as MultiScaleStructuralSimilarityIndexMeasure,
+)
+from torchmetrics.image._deprecated import _PeakSignalNoiseRatio as PeakSignalNoiseRatio  # noqa: E402
+from torchmetrics.image._deprecated import _RelativeAverageSpectralError as RelativeAverageSpectralError  # noqa: E402
+from torchmetrics.image._deprecated import (  # noqa: E402
+    _RootMeanSquaredErrorUsingSlidingWindow as RootMeanSquaredErrorUsingSlidingWindow,
+)
+from torchmetrics.image._deprecated import _SpectralAngleMapper as SpectralAngleMapper  # noqa: E402
+from torchmetrics.image._deprecated import _SpectralDistortionIndex as SpectralDistortionIndex  # noqa: E402
+from torchmetrics.image._deprecated import (  # noqa: E402
+    _StructuralSimilarityIndexMeasure as StructuralSimilarityIndexMeasure,
+)
+from torchmetrics.image._deprecated import _TotalVariation as TotalVariation  # noqa: E402
+from torchmetrics.image._deprecated import _UniversalImageQualityIndex as UniversalImageQualityIndex  # noqa: E402
 from torchmetrics.metric import Metric  # noqa: E402
 from torchmetrics.nominal import CramersV  # noqa: E402
 from torchmetrics.nominal import PearsonsContingencyCoefficient  # noqa: E402

src/torchmetrics/functional/__init__.py

@@ -41,19 +41,27 @@
 from torchmetrics.functional.classification.stat_scores import stat_scores
 from torchmetrics.functional.detection._deprecated import _modified_panoptic_quality as modified_panoptic_quality
 from torchmetrics.functional.detection._deprecated import _panoptic_quality as panoptic_quality
-from torchmetrics.functional.image.d_lambda import spectral_distortion_index
-from torchmetrics.functional.image.ergas import error_relative_global_dimensionless_synthesis
-from torchmetrics.functional.image.gradients import image_gradients
-from torchmetrics.functional.image.psnr import peak_signal_noise_ratio
-from torchmetrics.functional.image.rase import relative_average_spectral_error
-from torchmetrics.functional.image.rmse_sw import root_mean_squared_error_using_sliding_window
-from torchmetrics.functional.image.sam import spectral_angle_mapper
-from torchmetrics.functional.image.ssim import (
-    multiscale_structural_similarity_index_measure,
-    structural_similarity_index_measure,
+from torchmetrics.functional.image._deprecated import (
+    _error_relative_global_dimensionless_synthesis as error_relative_global_dimensionless_synthesis,
 )
-from torchmetrics.functional.image.tv import total_variation
-from torchmetrics.functional.image.uqi import universal_image_quality_index
+from torchmetrics.functional.image._deprecated import _image_gradients as image_gradients
+from torchmetrics.functional.image._deprecated import (
+    _multiscale_structural_similarity_index_measure as multiscale_structural_similarity_index_measure,
+)
+from torchmetrics.functional.image._deprecated import _peak_signal_noise_ratio as peak_signal_noise_ratio
+from torchmetrics.functional.image._deprecated import (
+    _relative_average_spectral_error as relative_average_spectral_error,
+)
+from torchmetrics.functional.image._deprecated import (
+    _root_mean_squared_error_using_sliding_window as root_mean_squared_error_using_sliding_window,
+)
+from torchmetrics.functional.image._deprecated import _spectral_angle_mapper as spectral_angle_mapper
+from torchmetrics.functional.image._deprecated import _spectral_distortion_index as spectral_distortion_index
+from torchmetrics.functional.image._deprecated import (
+    _structural_similarity_index_measure as structural_similarity_index_measure,
+)
+from torchmetrics.functional.image._deprecated import _total_variation as total_variation
+from torchmetrics.functional.image._deprecated import _universal_image_quality_index as universal_image_quality_index
 from torchmetrics.functional.nominal.cramers import cramers_v, cramers_v_matrix
 from torchmetrics.functional.nominal.pearson import (
     pearsons_contingency_coefficient,

src/torchmetrics/functional/image/__init__.py

@@ -11,16 +11,30 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from torchmetrics.functional.image.d_lambda import spectral_distortion_index  # noqa: F401
-from torchmetrics.functional.image.ergas import error_relative_global_dimensionless_synthesis  # noqa: F401
-from torchmetrics.functional.image.gradients import image_gradients  # noqa: F401
-from torchmetrics.functional.image.psnr import peak_signal_noise_ratio  # noqa: F401
-from torchmetrics.functional.image.rase import relative_average_spectral_error  # noqa: F401
-from torchmetrics.functional.image.rmse_sw import root_mean_squared_error_using_sliding_window  # noqa: F401
-from torchmetrics.functional.image.sam import spectral_angle_mapper  # noqa: F401
-from torchmetrics.functional.image.ssim import (  # noqa: F401
+from torchmetrics.functional.image.d_lambda import spectral_distortion_index
+from torchmetrics.functional.image.ergas import error_relative_global_dimensionless_synthesis
+from torchmetrics.functional.image.gradients import image_gradients
+from torchmetrics.functional.image.psnr import peak_signal_noise_ratio
+from torchmetrics.functional.image.rase import relative_average_spectral_error
+from torchmetrics.functional.image.rmse_sw import root_mean_squared_error_using_sliding_window
+from torchmetrics.functional.image.sam import spectral_angle_mapper
+from torchmetrics.functional.image.ssim import (
     multiscale_structural_similarity_index_measure,
     structural_similarity_index_measure,
 )
-from torchmetrics.functional.image.tv import total_variation  # noqa: F401
-from torchmetrics.functional.image.uqi import universal_image_quality_index  # noqa: F401
+from torchmetrics.functional.image.tv import total_variation
+from torchmetrics.functional.image.uqi import universal_image_quality_index
+
+__all__ = [
+    "spectral_distortion_index",
+    "error_relative_global_dimensionless_synthesis",
+    "image_gradients",
+    "peak_signal_noise_ratio",
+    "relative_average_spectral_error",
+    "root_mean_squared_error_using_sliding_window",
+    "spectral_angle_mapper",
+    "multiscale_structural_similarity_index_measure",
+    "structural_similarity_index_measure",
+    "total_variation",
+    "universal_image_quality_index",
+]

src/torchmetrics/functional/image/_deprecated.py

@@ -0,0 +1,255 @@
+from typing import Optional, Sequence, Tuple, Union
+
+from torch import Tensor
+from typing_extensions import Literal
+
+from torchmetrics.functional.image.d_lambda import spectral_distortion_index
+from torchmetrics.functional.image.ergas import error_relative_global_dimensionless_synthesis
+from torchmetrics.functional.image.gradients import image_gradients
+from torchmetrics.functional.image.psnr import peak_signal_noise_ratio
+from torchmetrics.functional.image.rase import relative_average_spectral_error
+from torchmetrics.functional.image.rmse_sw import root_mean_squared_error_using_sliding_window
+from torchmetrics.functional.image.sam import spectral_angle_mapper
+from torchmetrics.functional.image.ssim import (
+    multiscale_structural_similarity_index_measure,
+    structural_similarity_index_measure,
+)
+from torchmetrics.functional.image.tv import total_variation
+from torchmetrics.functional.image.uqi import universal_image_quality_index
+from torchmetrics.utilities.prints import _deprecated_root_import_func
+
+
+def _spectral_distortion_index(
+    preds: Tensor,
+    target: Tensor,
+    p: int = 1,
+    reduction: Literal["elementwise_mean", "sum", "none"] = "elementwise_mean",
+) -> Tensor:
+    """Wrapper for deprecated import.
+
+    >>> import torch
+    >>> _ = torch.manual_seed(42)
+    >>> preds = torch.rand([16, 3, 16, 16])
+    >>> target = torch.rand([16, 3, 16, 16])
+    >>> _spectral_distortion_index(preds, target)
+    tensor(0.0234)
+    """
+    _deprecated_root_import_func("spectral_distortion_index", "image")
+    return spectral_distortion_index(preds=preds, target=target, p=p, reduction=reduction)
+
+
+def _error_relative_global_dimensionless_synthesis(
+    preds: Tensor,
+    target: Tensor,
+    ratio: Union[int, float] = 4,
+    reduction: Literal["elementwise_mean", "sum", "none", None] = "elementwise_mean",
+) -> Tensor:
+    """Wrapper for deprecated import.
+
+    >>> import torch
+    >>> preds = torch.rand([16, 1, 16, 16], generator=torch.manual_seed(42))
+    >>> target = preds * 0.75
+    >>> ergds = _error_relative_global_dimensionless_synthesis(preds, target)
+    >>> torch.round(ergds)
+    tensor(154.)
+    """
+    _deprecated_root_import_func("error_relative_global_dimensionless_synthesis", "image")
+    return error_relative_global_dimensionless_synthesis(preds=preds, target=target, ratio=ratio, reduction=reduction)
+
+
+def _image_gradients(img: Tensor) -> Tuple[Tensor, Tensor]:
+    """Wrapper for deprecated import.
+
+    >>> import torch
+    >>> image = torch.arange(0, 1*1*5*5, dtype=torch.float32)
+    >>> image = torch.reshape(image, (1, 1, 5, 5))
+    >>> dy, dx = _image_gradients(image)
+    >>> dy[0, 0, :, :]
+    tensor([[5., 5., 5., 5., 5.],
+            [5., 5., 5., 5., 5.],
+            [5., 5., 5., 5., 5.],
+            [5., 5., 5., 5., 5.],
+            [0., 0., 0., 0., 0.]])
+    """
+    _deprecated_root_import_func("image_gradients", "image")
+    return image_gradients(img=img)
+
+
+def _peak_signal_noise_ratio(
+    preds: Tensor,
+    target: Tensor,
+    data_range: Optional[Union[float, Tuple[float, float]]] = None,
+    base: float = 10.0,
+    reduction: Literal["elementwise_mean", "sum", "none", None] = "elementwise_mean",
+    dim: Optional[Union[int, Tuple[int, ...]]] = None,
+) -> Tensor:
+    """Wrapper for deprecated import.
+
+    >>> from torch import tensor
+    >>> pred = tensor([[0.0, 1.0], [2.0, 3.0]])
+    >>> target = tensor([[3.0, 2.0], [1.0, 0.0]])
+    >>> _peak_signal_noise_ratio(pred, target)
+    tensor(2.5527)
+    """
+    _deprecated_root_import_func("peak_signal_noise_ratio", "image")
+    return peak_signal_noise_ratio(
+        preds=preds, target=target, data_range=data_range, base=base, reduction=reduction, dim=dim
+    )
+
+
+def _relative_average_spectral_error(preds: Tensor, target: Tensor, window_size: int = 8) -> Tensor:
+    """Wrapper for deprecated import.
+
+    >>> import torch
+    >>> g = torch.manual_seed(22)
+    >>> preds = torch.rand(4, 3, 16, 16)
+    >>> target = torch.rand(4, 3, 16, 16)
+    >>> _relative_average_spectral_error(preds, target)
+    tensor(5114.6641)
+    """
+    _deprecated_root_import_func("relative_average_spectral_error", "image")
+    return relative_average_spectral_error(preds=preds, target=target, window_size=window_size)
+
+
+def _root_mean_squared_error_using_sliding_window(
+    preds: Tensor, target: Tensor, window_size: int = 8, return_rmse_map: bool = False
+) -> Union[Optional[Tensor], Tuple[Optional[Tensor], Tensor]]:
+    """Wrapper for deprecated import.
+
+    >>> import torch
+    >>> g = torch.manual_seed(22)
+    >>> preds = torch.rand(4, 3, 16, 16)
+    >>> target = torch.rand(4, 3, 16, 16)
+    >>> _root_mean_squared_error_using_sliding_window(preds, target)
+    tensor(0.3999)
+    """
+    _deprecated_root_import_func("root_mean_squared_error_using_sliding_window", "image")
+    return root_mean_squared_error_using_sliding_window(
+        preds=preds, target=target, window_size=window_size, return_rmse_map=return_rmse_map
+    )
+
+
+def _spectral_angle_mapper(
+    preds: Tensor,
+    target: Tensor,
+    reduction: Literal["elementwise_mean", "sum", "none", None] = "elementwise_mean",
+) -> Tensor:
+    """Wrapper for deprecated import.
+
+    >>> import torch
+    >>> preds = torch.rand([16, 3, 16, 16], generator=torch.manual_seed(42))
+    >>> target = torch.rand([16, 3, 16, 16], generator=torch.manual_seed(123))
+    >>> _spectral_angle_mapper(preds, target)
+    tensor(0.5943)
+    """
+    _deprecated_root_import_func("spectral_angle_mapper", "image")
+    return spectral_angle_mapper(preds=preds, target=target, reduction=reduction)
+
+
+def _multiscale_structural_similarity_index_measure(
+    preds: Tensor,
+    target: Tensor,
+    gaussian_kernel: bool = True,
+    sigma: Union[float, Sequence[float]] = 1.5,
+    kernel_size: Union[int, Sequence[int]] = 11,
+    reduction: Literal["elementwise_mean", "sum", "none", None] = "elementwise_mean",
+    data_range: Optional[Union[float, Tuple[float, float]]] = None,
+    k1: float = 0.01,
+    k2: float = 0.03,
+    betas: Tuple[float, ...] = (0.0448, 0.2856, 0.3001, 0.2363, 0.1333),
+    normalize: Optional[Literal["relu", "simple"]] = "relu",
+) -> Tensor:
+    """Wrapper for deprecated import.
+
+    >>> import torch
+    >>> preds = torch.rand([3, 3, 256, 256], generator=torch.manual_seed(42))
+    >>> target = preds * 0.75
+    >>> _multiscale_structural_similarity_index_measure(preds, target, data_range=1.0)
+    tensor(0.9627)
+    """
+    _deprecated_root_import_func("multiscale_structural_similarity_index_measure", "image")
+    return multiscale_structural_similarity_index_measure(
+        preds=preds,
+        target=target,
+        gaussian_kernel=gaussian_kernel,
+        sigma=sigma,
+        kernel_size=kernel_size,
+        reduction=reduction,
+        data_range=data_range,
+        k1=k1,
+        k2=k2,
+        betas=betas,
+        normalize=normalize,
+    )
+
+
+def _structural_similarity_index_measure(
+    preds: Tensor,
+    target: Tensor,
+    gaussian_kernel: bool = True,
+    sigma: Union[float, Sequence[float]] = 1.5,
+    kernel_size: Union[int, Sequence[int]] = 11,
+    reduction: Literal["elementwise_mean", "sum", "none", None] = "elementwise_mean",
+    data_range: Optional[Union[float, Tuple[float, float]]] = None,
+    k1: float = 0.01,
+    k2: float = 0.03,
+    return_full_image: bool = False,
+    return_contrast_sensitivity: bool = False,
+) -> Union[Tensor, Tuple[Tensor, Tensor]]:
+    """Wrapper for deprecated import.
+
+    >>> import torch
+    >>> preds = torch.rand([3, 3, 256, 256])
+    >>> target = preds * 0.75
+    >>> _structural_similarity_index_measure(preds, target)
+    tensor(0.9219)
+    """
+    _deprecated_root_import_func("spectral_angle_mapper", "image")
+    return structural_similarity_index_measure(
+        preds=preds,
+        target=target,
+        gaussian_kernel=gaussian_kernel,
+        sigma=sigma,
+        kernel_size=kernel_size,
+        reduction=reduction,
+        data_range=data_range,
+        k1=k1,
+        k2=k2,
+        return_full_image=return_full_image,
+        return_contrast_sensitivity=return_contrast_sensitivity,
+    )
+
+
+def _total_variation(img: Tensor, reduction: Literal["mean", "sum", "none", None] = "sum") -> Tensor:
+    """Wrapper for deprecated import.
+
+    >>> import torch
+    >>> _ = torch.manual_seed(42)
+    >>> img = torch.rand(5, 3, 28, 28)
+    >>> _total_variation(img)
+    tensor(7546.8018)
+    """
+    _deprecated_root_import_func("total_variation", "image")
+    return total_variation(img=img, reduction=reduction)
+
+
+def _universal_image_quality_index(
+    preds: Tensor,
+    target: Tensor,
+    kernel_size: Sequence[int] = (11, 11),
+    sigma: Sequence[float] = (1.5, 1.5),
+    reduction: Optional[Literal["elementwise_mean", "sum", "none"]] = "elementwise_mean",
+    data_range: Optional[float] = None,
+) -> Tensor:
+    """Wrapper for deprecated import.
+
+    >>> import torch
+    >>> preds = torch.rand([16, 1, 16, 16])
+    >>> target = preds * 0.75
+    >>> _universal_image_quality_index(preds, target)
+    tensor(0.9216)
+    """
+    _deprecated_root_import_func("universal_image_quality_index", "image")
+    return universal_image_quality_index(
+        preds=preds, target=target, kernel_size=kernel_size, sigma=sigma, reduction=reduction, data_range=data_range
+    )