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Merged
wyli merged 3 commits into from
May 26, 2022
Merged

4343 adds interp mode #4344

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ec83c5b
adds interp mode
wyli May 25, 2022
30152f4
update docstrings
wyli May 25, 2022
797de42
Merge branch 'dev' into 4343-interpolate-mode
wyli May 25, 2022
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4 changes: 2 additions & 2 deletions monai/apps/detection/transforms/dictionary.py
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Expand Up @@ -264,7 +264,7 @@ class ZoomBoxd(MapTransform, InvertibleTransform):
zoom: The zoom factor along the spatial axes.
If a float, zoom is the same for each spatial axis.
If a sequence, zoom should contain one value for each spatial axis.
mode: {``"nearest"``, ``"linear"``, ``"bilinear"``, ``"bicubic"``, ``"trilinear"``, ``"area"``}
mode: {``"nearest"``, ``"nearest-exact"``, ``"linear"``, ``"bilinear"``, ``"bicubic"``, ``"trilinear"``, ``"area"``}
The interpolation mode. Defaults to ``"area"``.
See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.interpolate.html
It also can be a sequence of string, each element corresponds to a key in ``keys``.
Expand Down Expand Up @@ -401,7 +401,7 @@ class RandZoomBoxd(RandomizableTransform, MapTransform, InvertibleTransform):
to keep the original spatial shape ratio.
If a sequence, max_zoom should contain one value for each spatial axis.
If 2 values provided for 3D data, use the first value for both H & W dims to keep the same zoom ratio.
mode: {``"nearest"``, ``"linear"``, ``"bilinear"``, ``"bicubic"``, ``"trilinear"``, ``"area"``}
mode: {``"nearest"``, ``"nearest-exact"``, ``"linear"``, ``"bilinear"``, ``"bicubic"``, ``"trilinear"``, ``"area"``}
The interpolation mode. Defaults to ``"area"``.
See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.interpolate.html
It also can be a sequence of string, each element corresponds to a key in ``keys``.
Expand Down
2 changes: 1 addition & 1 deletion monai/data/png_writer.py
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Expand Up @@ -38,7 +38,7 @@ def write_png(
data: input data to write to file.
file_name: expected file name that saved on disk.
output_spatial_shape: spatial shape of the output image.
mode: {``"nearest"``, ``"linear"``, ``"bilinear"``, ``"bicubic"``, ``"trilinear"``, ``"area"``}
mode: {``"nearest"``, ``"nearest-exact"``, ``"linear"``, ``"bilinear"``, ``"bicubic"``, ``"trilinear"``, ``"area"``}
The interpolation mode. Defaults to ``"bicubic"``.
See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.interpolate.html
scale: {``255``, ``65535``} postprocess data by clipping to [0, 1] and scaling to
Expand Down
14 changes: 8 additions & 6 deletions monai/transforms/spatial/array.py
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Expand Up @@ -617,7 +617,7 @@ class Resize(Transform):
which must be an int number in this case, keeping the aspect ratio of the initial image, refer to:
https://albumentations.ai/docs/api_reference/augmentations/geometric/resize/
#albumentations.augmentations.geometric.resize.LongestMaxSize.
mode: {``"nearest"``, ``"linear"``, ``"bilinear"``, ``"bicubic"``, ``"trilinear"``, ``"area"``}
mode: {``"nearest"``, ``"nearest-exact"``, ``"linear"``, ``"bilinear"``, ``"bicubic"``, ``"trilinear"``, ``"area"``}
The interpolation mode. Defaults to ``"area"``.
See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.interpolate.html
align_corners: This only has an effect when mode is
Expand Down Expand Up @@ -663,7 +663,8 @@ def __call__(
"""
Args:
img: channel first array, must have shape: (num_channels, H[, W, ..., ]).
mode: {``"nearest"``, ``"linear"``, ``"bilinear"``, ``"bicubic"``, ``"trilinear"``, ``"area"``}
mode: {``"nearest"``, ``"nearest-exact"``, ``"linear"``,
``"bilinear"``, ``"bicubic"``, ``"trilinear"``, ``"area"``}
The interpolation mode. Defaults to ``self.mode``.
See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.interpolate.html
align_corners: This only has an effect when mode is
Expand Down Expand Up @@ -856,7 +857,7 @@ class Zoom(Transform):
zoom: The zoom factor along the spatial axes.
If a float, zoom is the same for each spatial axis.
If a sequence, zoom should contain one value for each spatial axis.
mode: {``"nearest"``, ``"linear"``, ``"bilinear"``, ``"bicubic"``, ``"trilinear"``, ``"area"``}
mode: {``"nearest"``, ``"nearest-exact"``, ``"linear"``, ``"bilinear"``, ``"bicubic"``, ``"trilinear"``, ``"area"``}
The interpolation mode. Defaults to ``"area"``.
See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.interpolate.html
padding_mode: available modes for numpy array:{``"constant"``, ``"edge"``, ``"linear_ramp"``, ``"maximum"``,
Expand Down Expand Up @@ -903,7 +904,8 @@ def __call__(
"""
Args:
img: channel first array, must have shape: (num_channels, H[, W, ..., ]).
mode: {``"nearest"``, ``"linear"``, ``"bilinear"``, ``"bicubic"``, ``"trilinear"``, ``"area"``}
mode: {``"nearest"``, ``"nearest-exact"``, ``"linear"``,
``"bilinear"``, ``"bicubic"``, ``"trilinear"``, ``"area"``}
The interpolation mode. Defaults to ``self.mode``.
See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.interpolate.html
padding_mode: available modes for numpy array:{``"constant"``, ``"edge"``, ``"linear_ramp"``, ``"maximum"``,
Expand Down Expand Up @@ -1231,7 +1233,7 @@ class RandZoom(RandomizableTransform):
to keep the original spatial shape ratio.
If a sequence, max_zoom should contain one value for each spatial axis.
If 2 values provided for 3D data, use the first value for both H & W dims to keep the same zoom ratio.
mode: {``"nearest"``, ``"linear"``, ``"bilinear"``, ``"bicubic"``, ``"trilinear"``, ``"area"``}
mode: {``"nearest"``, ``"nearest-exact"``, ``"linear"``, ``"bilinear"``, ``"bicubic"``, ``"trilinear"``, ``"area"``}
The interpolation mode. Defaults to ``"area"``.
See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.interpolate.html
padding_mode: available modes for numpy array:{``"constant"``, ``"edge"``, ``"linear_ramp"``, ``"maximum"``,
Expand Down Expand Up @@ -1299,7 +1301,7 @@ def __call__(
"""
Args:
img: channel first array, must have shape 2D: (nchannels, H, W), or 3D: (nchannels, H, W, D).
mode: {``"nearest"``, ``"linear"``, ``"bilinear"``, ``"bicubic"``, ``"trilinear"``, ``"area"``}
mode: {``"nearest"``, ``"nearest-exact"``, ``"linear"``, ``"bilinear"``, ``"bicubic"``, ``"trilinear"``, ``"area"``}
The interpolation mode. Defaults to ``self.mode``.
See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.interpolate.html
padding_mode: available modes for numpy array:{``"constant"``, ``"edge"``, ``"linear_ramp"``, ``"maximum"``,
Expand Down
6 changes: 3 additions & 3 deletions monai/transforms/spatial/dictionary.py
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Original file line number Diff line number Diff line change
Expand Up @@ -806,7 +806,7 @@ class Resized(MapTransform, InvertibleTransform):
which must be an int number in this case, keeping the aspect ratio of the initial image, refer to:
https://albumentations.ai/docs/api_reference/augmentations/geometric/resize/
#albumentations.augmentations.geometric.resize.LongestMaxSize.
mode: {``"nearest"``, ``"linear"``, ``"bilinear"``, ``"bicubic"``, ``"trilinear"``, ``"area"``}
mode: {``"nearest"``, ``"nearest-exact"``, ``"linear"``, ``"bilinear"``, ``"bicubic"``, ``"trilinear"``, ``"area"``}
The interpolation mode. Defaults to ``"area"``.
See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.interpolate.html
It also can be a sequence of string, each element corresponds to a key in ``keys``.
Expand Down Expand Up @@ -1829,7 +1829,7 @@ class Zoomd(MapTransform, InvertibleTransform):
zoom: The zoom factor along the spatial axes.
If a float, zoom is the same for each spatial axis.
If a sequence, zoom should contain one value for each spatial axis.
mode: {``"nearest"``, ``"linear"``, ``"bilinear"``, ``"bicubic"``, ``"trilinear"``, ``"area"``}
mode: {``"nearest"``, ``"nearest-exact"``, ``"linear"``, ``"bilinear"``, ``"bicubic"``, ``"trilinear"``, ``"area"``}
The interpolation mode. Defaults to ``"area"``.
See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.interpolate.html
It also can be a sequence of string, each element corresponds to a key in ``keys``.
Expand Down Expand Up @@ -1929,7 +1929,7 @@ class RandZoomd(RandomizableTransform, MapTransform, InvertibleTransform):
to keep the original spatial shape ratio.
If a sequence, max_zoom should contain one value for each spatial axis.
If 2 values provided for 3D data, use the first value for both H & W dims to keep the same zoom ratio.
mode: {``"nearest"``, ``"linear"``, ``"bilinear"``, ``"bicubic"``, ``"trilinear"``, ``"area"``}
mode: {``"nearest"``, ``"nearest-exact"``, ``"linear"``, ``"bilinear"``, ``"bicubic"``, ``"trilinear"``, ``"area"``}
The interpolation mode. Defaults to ``"area"``.
See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.interpolate.html
It also can be a sequence of string, each element corresponds to a key in ``keys``.
Expand Down
1 change: 1 addition & 0 deletions monai/utils/enums.py
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Original file line number Diff line number Diff line change
Expand Up @@ -82,6 +82,7 @@ class InterpolateMode(Enum):
"""

NEAREST = "nearest"
NEAREST_EXACT = "nearest-exact"
LINEAR = "linear"
BILINEAR = "bilinear"
BICUBIC = "bicubic"
Expand Down
4 changes: 3 additions & 1 deletion tests/test_resize.py
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Expand Up @@ -17,7 +17,7 @@
from parameterized import parameterized

from monai.transforms import Resize
from tests.utils import TEST_NDARRAYS, NumpyImageTestCase2D, assert_allclose
from tests.utils import TEST_NDARRAYS, NumpyImageTestCase2D, assert_allclose, pytorch_after

TEST_CASE_0 = [{"spatial_size": 15}, (6, 10, 15)]

Expand Down Expand Up @@ -46,9 +46,11 @@ def test_invalid_inputs(self):
((32, 32), "area", False),
((32, 32, 32), "trilinear", True),
((256, 256), "bilinear", False),
((256, 256), "nearest-exact" if pytorch_after(1, 11) else "nearest", False),
]
)
def test_correct_results(self, spatial_size, mode, anti_aliasing):
"""resize 'spatial_size' and 'mode'"""
resize = Resize(spatial_size, mode=mode, anti_aliasing=anti_aliasing)
_order = 0
if mode.endswith("linear"):
Expand Down