From b0df2457211d2de8f65f3d9d2cdf635a57fb3fc7 Mon Sep 17 00:00:00 2001 From: Nic Ma Date: Thu, 30 Sep 2021 11:22:54 +0800 Subject: [PATCH 1/2] [DLMED] fix spacing dtype Signed-off-by: Nic Ma --- monai/transforms/spatial/array.py | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/monai/transforms/spatial/array.py b/monai/transforms/spatial/array.py index 62ac5d2c3e..27d25cf2bc 100644 --- a/monai/transforms/spatial/array.py +++ b/monai/transforms/spatial/array.py @@ -13,7 +13,6 @@ https://github.com/Project-MONAI/MONAI/wiki/MONAI_Design """ import warnings -from copy import deepcopy from typing import Any, List, Optional, Sequence, Tuple, Union import numpy as np @@ -200,9 +199,8 @@ def __call__( # no resampling if it's identity transform if np.allclose(transform, np.diag(np.ones(len(transform))), atol=1e-3): - output_data, *_ = convert_data_type(deepcopy(data_array), dtype=_dtype) + output_data, *_ = convert_data_type(data_array, dtype=torch.float32) new_affine = to_affine_nd(affine, new_affine) # type: ignore - else: # resample affine_xform = AffineTransform( @@ -220,7 +218,7 @@ def __call__( convert_data_type(transform, torch.Tensor, data_array_t.device, dtype=_dtype)[0], spatial_size=output_shape if output_spatial_shape is None else output_spatial_shape, ).squeeze(0) - output_data, *_ = convert_to_dst_type(output_data, data_array, dtype=_dtype) + output_data, *_ = convert_to_dst_type(output_data, data_array, dtype=torch.float32) new_affine = to_affine_nd(affine, new_affine) # type: ignore return output_data, affine, new_affine From 019ca309de05ed2779a18c941d77c8d56dfd7af4 Mon Sep 17 00:00:00 2001 From: Nic Ma Date: Thu, 30 Sep 2021 11:31:04 +0800 Subject: [PATCH 2/2] [DLMED] fix dtype Signed-off-by: Nic Ma --- monai/transforms/intensity/array.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/monai/transforms/intensity/array.py b/monai/transforms/intensity/array.py index 0e9f922888..2dc1ed1a94 100644 --- a/monai/transforms/intensity/array.py +++ b/monai/transforms/intensity/array.py @@ -739,7 +739,8 @@ def __call__(self, img: NdarrayOrTensor) -> NdarrayOrTensor: epsilon = 1e-7 img_min = img.min() img_range = img.max() - img_min - return ((img - img_min) / float(img_range + epsilon)) ** self.gamma * img_range + img_min + ret: NdarrayOrTensor = ((img - img_min) / float(img_range + epsilon)) ** self.gamma * img_range + img_min + return ret class RandAdjustContrast(RandomizableTransform):