From 69bd73091deb7321a55400d25b96e6baf0d6a31f Mon Sep 17 00:00:00 2001 From: Rich <33289025+rijobro@users.noreply.github.com> Date: Wed, 24 Feb 2021 16:33:39 +0000 Subject: [PATCH 1/3] enhance random range parameters If element `i` is iterable, then `uniform[-rotate_range[i][0], rotate_range[i][1])` will be used to generate the rotation parameter for the ith dimension. If not, `uniform[-rotate_range[i], rotate_range[i])` will be used. This can be altered on a per-dimension basis. E.g., `((0,3), 1, ...)`: for dim0, rotation will be in range `[0, 3]`, and for dim1 `[-1, 1]` will be used. Setting a single value will use `[-x, x]` for dim0 and nothing for the remaining dimensions. Signed-off-by: Richard Brown <33289025+rijobro@users.noreply.github.com> --- monai/transforms/spatial/array.py | 151 ++++++++++++------------- monai/transforms/spatial/dictionary.py | 90 +++++++-------- 2 files changed, 109 insertions(+), 132 deletions(-) diff --git a/monai/transforms/spatial/array.py b/monai/transforms/spatial/array.py index df10480188..a6d74b1aa4 100644 --- a/monai/transforms/spatial/array.py +++ b/monai/transforms/spatial/array.py @@ -965,30 +965,24 @@ class RandAffineGrid(Randomizable, Transform): def __init__( self, - rotate_range: Optional[Union[Sequence[float], float]] = None, - shear_range: Optional[Union[Sequence[float], float]] = None, - translate_range: Optional[Union[Sequence[float], float]] = None, - scale_range: Optional[Union[Sequence[float], float]] = None, + rotate_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, + shear_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, + translate_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, + scale_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, as_tensor_output: bool = True, device: Optional[torch.device] = None, ) -> None: """ Args: - rotate_range: angle range in radians. rotate_range[0] with be used to generate the 1st rotation - parameter from `uniform[-rotate_range[0], rotate_range[0])`. Similarly, `rotate_range[1]` and - `rotate_range[2]` are used in 3D affine for the range of 2nd and 3rd axes. - shear_range: shear_range[0] with be used to generate the 1st shearing parameter from - `uniform[-shear_range[0], shear_range[0])`. Similarly, `shear_range[1]` to - `shear_range[N]` controls the range of the uniform distribution used to generate the 2nd to - N-th parameter. - translate_range : translate_range[0] with be used to generate the 1st shift parameter from - `uniform[-translate_range[0], translate_range[0])`. Similarly, `translate_range[1]` - to `translate_range[N]` controls the range of the uniform distribution used to generate - the 2nd to N-th parameter. - scale_range: scaling_range[0] with be used to generate the 1st scaling factor from - `uniform[-scale_range[0], scale_range[0]) + 1.0`. Similarly, `scale_range[1]` to - `scale_range[N]` controls the range of the uniform distribution used to generate the 2nd to - N-th parameter. + rotate_range: angle range in radians. If element `i` is iterable, then + `uniform[-rotate_range[i][0], rotate_range[i][1])` will be used to generate the rotation parameter + for the ith dimension. If not, `uniform[-rotate_range[i], rotate_range[i])` will be used. This can + be altered on a per-dimension basis. E.g., `((0,3), 1, ...)`: for dim0, rotation will be in range + `[0, 3]`, and for dim1 `[-1, 1]` will be used. Setting a single value will use `[-x, x]` for dim0 + and nothing for the remaining dimensions. + shear_range: shear_range with format matching `rotate_range`. + translate_range: translate_range with format matching `rotate_range`. + scale_range: scaling_range with format matching `rotate_range`. as_tensor_output: whether to output tensor instead of numpy array. defaults to True. device: device to store the output grid data. @@ -1012,15 +1006,22 @@ def __init__( self.as_tensor_output = as_tensor_output self.device = device + def _get_rand_param(self, param_range): + out_param = [] + for f in param_range: + if issequenceiterable(f): + if len(f) != 2: + raise ValueError("If giving range as [min,max], should only have two elements per dim.") + out_param.append(self.R.uniform(f[0], f[1])) + elif f is not None: + out_param.append(self.R.uniform(-f, f)) + return out_param + def randomize(self, data: Optional[Any] = None) -> None: - if self.rotate_range: - self.rotate_params = [self.R.uniform(-f, f) for f in self.rotate_range if f is not None] - if self.shear_range: - self.shear_params = [self.R.uniform(-f, f) for f in self.shear_range if f is not None] - if self.translate_range: - self.translate_params = [self.R.uniform(-f, f) for f in self.translate_range if f is not None] - if self.scale_range: - self.scale_params = [self.R.uniform(-f, f) + 1.0 for f in self.scale_range if f is not None] + self.rotate_params = self._get_rand_param(self.rotate_range) + self.shear_params = self._get_rand_param(self.shear_range) + self.translate_params = self._get_rand_param(self.translate_range) + self.scale_params = self._get_rand_param(self.scale_range) def __call__( self, spatial_size: Optional[Sequence[int]] = None, grid: Optional[Union[np.ndarray, torch.Tensor]] = None @@ -1282,11 +1283,11 @@ class RandAffine(Randomizable, Transform): def __init__( self, prob: float = 0.1, - rotate_range: Optional[Union[Sequence[float], float]] = None, - shear_range: Optional[Union[Sequence[float], float]] = None, - translate_range: Optional[Union[Sequence[float], float]] = None, - scale_range: Optional[Union[Sequence[float], float]] = None, - spatial_size: Optional[Union[Sequence[float], float]] = None, + rotate_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, + shear_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, + translate_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, + scale_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, + spatial_size: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, mode: Union[GridSampleMode, str] = GridSampleMode.BILINEAR, padding_mode: Union[GridSamplePadMode, str] = GridSamplePadMode.REFLECTION, as_tensor_output: bool = True, @@ -1296,21 +1297,15 @@ def __init__( Args: prob: probability of returning a randomized affine grid. defaults to 0.1, with 10% chance returns a randomized grid. - rotate_range: angle range in radians. rotate_range[0] with be used to generate the 1st rotation - parameter from `uniform[-rotate_range[0], rotate_range[0])`. Similarly, `rotate_range[1]` and - `rotate_range[2]` are used in 3D affine for the range of 2nd and 3rd axes. - shear_range: shear_range[0] with be used to generate the 1st shearing parameter from - `uniform[-shear_range[0], shear_range[0])`. Similarly, `shear_range[1]` to - `shear_range[N]` controls the range of the uniform distribution used to generate the 2nd to - N-th parameter. - translate_range : translate_range[0] with be used to generate the 1st shift parameter from - `uniform[-translate_range[0], translate_range[0])`. Similarly, `translate_range[1]` - to `translate_range[N]` controls the range of the uniform distribution used to generate - the 2nd to N-th parameter. - scale_range: scaling_range[0] with be used to generate the 1st scaling factor from - `uniform[-scale_range[0], scale_range[0]) + 1.0`. Similarly, `scale_range[1]` to - `scale_range[N]` controls the range of the uniform distribution used to generate the 2nd to - N-th parameter. + rotate_range: angle range in radians. If element `i` is iterable, then + `uniform[-rotate_range[i][0], rotate_range[i][1])` will be used to generate the rotation parameter + for the ith dimension. If not, `uniform[-rotate_range[i], rotate_range[i])` will be used. This can + be altered on a per-dimension basis. E.g., `((0,3), 1, ...)`: for dim0, rotation will be in range + `[0, 3]`, and for dim1 `[-1, 1]` will be used. Setting a single value will use `[-x, x]` for dim0 + and nothing for the remaining dimensions. + shear_range: shear_range with format matching `rotate_range`. + translate_range: translate_range with format matching `rotate_range`. + scale_range: scaling_range with format matching `rotate_range`. spatial_size: output image spatial size. if `spatial_size` and `self.spatial_size` are not defined, or smaller than 1, the transform will use the spatial size of `img`. @@ -1404,11 +1399,11 @@ def __init__( spacing: Union[Tuple[float, float], float], magnitude_range: Tuple[float, float], prob: float = 0.1, - rotate_range: Optional[Union[Sequence[float], float]] = None, - shear_range: Optional[Union[Sequence[float], float]] = None, - translate_range: Optional[Union[Sequence[float], float]] = None, - scale_range: Optional[Union[Sequence[float], float]] = None, - spatial_size: Optional[Union[Sequence[int], int]] = None, + rotate_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, + shear_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, + translate_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, + scale_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, + spatial_size: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, mode: Union[GridSampleMode, str] = GridSampleMode.BILINEAR, padding_mode: Union[GridSamplePadMode, str] = GridSamplePadMode.REFLECTION, as_tensor_output: bool = False, @@ -1421,17 +1416,15 @@ def __init__( prob: probability of returning a randomized elastic transform. defaults to 0.1, with 10% chance returns a randomized elastic transform, otherwise returns a ``spatial_size`` centered area extracted from the input image. - rotate_range: angle range in radians. rotate_range[0] with be used to generate the 1st rotation - parameter from `uniform[-rotate_range[0], rotate_range[0])`. - shear_range: shear_range[0] with be used to generate the 1st shearing parameter from - `uniform[-shear_range[0], shear_range[0])`. Similarly, `shear_range[1]` controls - the range of the uniform distribution used to generate the 2nd parameter. - translate_range : translate_range[0] with be used to generate the 1st shift parameter from - `uniform[-translate_range[0], translate_range[0])`. Similarly, `translate_range[1]` controls - the range of the uniform distribution used to generate the 2nd parameter. - scale_range: scaling_range[0] with be used to generate the 1st scaling factor from - `uniform[-scale_range[0], scale_range[0]) + 1.0`. Similarly, `scale_range[1]` controls - the range of the uniform distribution used to generate the 2nd parameter. + rotate_range: angle range in radians. If element `i` is iterable, then + `uniform[-rotate_range[i][0], rotate_range[i][1])` will be used to generate the rotation parameter + for the ith dimension. If not, `uniform[-rotate_range[i], rotate_range[i])` will be used. This can + be altered on a per-dimension basis. E.g., `((0,3), 1, ...)`: for dim0, rotation will be in range + `[0, 3]`, and for dim1 `[-1, 1]` will be used. Setting a single value will use `[-x, x]` for dim0 + and nothing for the remaining dimensions. + shear_range: shear_range with format matching `rotate_range`. + translate_range: translate_range with format matching `rotate_range`. + scale_range: scaling_range with format matching `rotate_range`. spatial_size: specifying output image spatial size [h, w]. if `spatial_size` and `self.spatial_size` are not defined, or smaller than 1, the transform will use the spatial size of `img`. @@ -1532,11 +1525,11 @@ def __init__( sigma_range: Tuple[float, float], magnitude_range: Tuple[float, float], prob: float = 0.1, - rotate_range: Optional[Union[Sequence[float], float]] = None, - shear_range: Optional[Union[Sequence[float], float]] = None, - translate_range: Optional[Union[Sequence[float], float]] = None, - scale_range: Optional[Union[Sequence[float], float]] = None, - spatial_size: Optional[Union[Sequence[int], int]] = None, + rotate_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, + shear_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, + translate_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, + scale_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, + spatial_size: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, mode: Union[GridSampleMode, str] = GridSampleMode.BILINEAR, padding_mode: Union[GridSamplePadMode, str] = GridSamplePadMode.REFLECTION, as_tensor_output: bool = False, @@ -1551,19 +1544,15 @@ def __init__( prob: probability of returning a randomized elastic transform. defaults to 0.1, with 10% chance returns a randomized elastic transform, otherwise returns a ``spatial_size`` centered area extracted from the input image. - rotate_range: angle range in radians. rotate_range[0] with be used to generate the 1st rotation - parameter from `uniform[-rotate_range[0], rotate_range[0])`. Similarly, `rotate_range[1]` and - `rotate_range[2]` are used in 3D affine for the range of 2nd and 3rd axes. - shear_range: shear_range[0] with be used to generate the 1st shearing parameter from - `uniform[-shear_range[0], shear_range[0])`. Similarly, `shear_range[1]` and `shear_range[2]` - controls the range of the uniform distribution used to generate the 2nd and 3rd parameters. - translate_range : translate_range[0] with be used to generate the 1st shift parameter from - `uniform[-translate_range[0], translate_range[0])`. Similarly, `translate_range[1]` and - `translate_range[2]` controls the range of the uniform distribution used to generate - the 2nd and 3rd parameters. - scale_range: scaling_range[0] with be used to generate the 1st scaling factor from - `uniform[-scale_range[0], scale_range[0]) + 1.0`. Similarly, `scale_range[1]` and `scale_range[2]` - controls the range of the uniform distribution used to generate the 2nd and 3rd parameters. + rotate_range: angle range in radians. If element `i` is iterable, then + `uniform[-rotate_range[i][0], rotate_range[i][1])` will be used to generate the rotation parameter + for the ith dimension. If not, `uniform[-rotate_range[i], rotate_range[i])` will be used. This can + be altered on a per-dimension basis. E.g., `((0,3), 1, ...)`: for dim0, rotation will be in range + `[0, 3]`, and for dim1 `[-1, 1]` will be used. Setting a single value will use `[-x, x]` for dim0 + and nothing for the remaining dimensions. + shear_range: shear_range with format matching `rotate_range`. + translate_range: translate_range with format matching `rotate_range`. + scale_range: scaling_range with format matching `rotate_range`. spatial_size: specifying output image spatial size [h, w, d]. if `spatial_size` and `self.spatial_size` are not defined, or smaller than 1, the transform will use the spatial size of `img`. diff --git a/monai/transforms/spatial/dictionary.py b/monai/transforms/spatial/dictionary.py index e612a25ef8..657e022e5c 100644 --- a/monai/transforms/spatial/dictionary.py +++ b/monai/transforms/spatial/dictionary.py @@ -374,10 +374,10 @@ def __init__( keys: KeysCollection, spatial_size: Optional[Union[Sequence[int], int]] = None, prob: float = 0.1, - rotate_range: Optional[Union[Sequence[float], float]] = None, - shear_range: Optional[Union[Sequence[float], float]] = None, - translate_range: Optional[Union[Sequence[float], float]] = None, - scale_range: Optional[Union[Sequence[float], float]] = None, + rotate_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, + shear_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, + translate_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, + scale_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, mode: GridSampleModeSequence = GridSampleMode.BILINEAR, padding_mode: GridSamplePadModeSequence = GridSamplePadMode.REFLECTION, as_tensor_output: bool = True, @@ -394,21 +394,15 @@ def __init__( to `(32, 64)` if the second spatial dimension size of img is `64`. prob: probability of returning a randomized affine grid. defaults to 0.1, with 10% chance returns a randomized grid. - rotate_range: angle range in radians. rotate_range[0] with be used to generate the 1st rotation - parameter from `uniform[-rotate_range[0], rotate_range[0])`. Similarly, `rotate_range[1]` and - `rotate_range[2]` are used in 3D affine for the range of 2nd and 3rd axes. - shear_range: shear_range[0] with be used to generate the 1st shearing parameter from - `uniform[-shear_range[0], shear_range[0])`. Similarly, `shear_range[1]` to - `shear_range[N]` controls the range of the uniform distribution used to generate the 2nd to - N-th parameter. - translate_range : translate_range[0] with be used to generate the 1st shift parameter from - `uniform[-translate_range[0], translate_range[0])`. Similarly, `translate_range[1]` - to `translate_range[N]` controls the range of the uniform distribution used to generate - the 2nd to N-th parameter. - scale_range: scaling_range[0] with be used to generate the 1st scaling factor from - `uniform[-scale_range[0], scale_range[0]) + 1.0`. Similarly, `scale_range[1]` to - `scale_range[N]` controls the range of the uniform distribution used to generate the 2nd to - N-th parameter. + rotate_range: angle range in radians. If element `i` is iterable, then + `uniform[-rotate_range[i][0], rotate_range[i][1])` will be used to generate the rotation parameter + for the ith dimension. If not, `uniform[-rotate_range[i], rotate_range[i])` will be used. This can + be altered on a per-dimension basis. E.g., `((0,3), 1, ...)`: for dim0, rotation will be in range + `[0, 3]`, and for dim1 `[-1, 1]` will be used. Setting a single value will use `[-x, x]` for dim0 + and nothing for the remaining dimensions. + shear_range: shear_range with format matching `rotate_range`. + translate_range: translate_range with format matching `rotate_range`. + scale_range: scaling_range with format matching `rotate_range`. mode: {``"bilinear"``, ``"nearest"``} Interpolation mode to calculate output values. Defaults to ``"bilinear"``. See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample @@ -478,10 +472,10 @@ def __init__( magnitude_range: Tuple[float, float], spatial_size: Optional[Union[Sequence[int], int]] = None, prob: float = 0.1, - rotate_range: Optional[Union[Sequence[float], float]] = None, - shear_range: Optional[Union[Sequence[float], float]] = None, - translate_range: Optional[Union[Sequence[float], float]] = None, - scale_range: Optional[Union[Sequence[float], float]] = None, + rotate_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, + shear_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, + translate_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, + scale_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, mode: GridSampleModeSequence = GridSampleMode.BILINEAR, padding_mode: GridSamplePadModeSequence = GridSamplePadMode.REFLECTION, as_tensor_output: bool = False, @@ -502,17 +496,15 @@ def __init__( prob: probability of returning a randomized affine grid. defaults to 0.1, with 10% chance returns a randomized grid, otherwise returns a ``spatial_size`` centered area extracted from the input image. - rotate_range: angle range in radians. rotate_range[0] with be used to generate the 1st rotation - parameter from `uniform[-rotate_range[0], rotate_range[0])`. - shear_range: shear_range[0] with be used to generate the 1st shearing parameter from - `uniform[-shear_range[0], shear_range[0])`. Similarly, `shear_range[1]` controls - the range of the uniform distribution used to generate the 2nd parameter. - translate_range : translate_range[0] with be used to generate the 1st shift parameter from - `uniform[-translate_range[0], translate_range[0])`. Similarly, `translate_range[1]` controls - the range of the uniform distribution used to generate the 2nd parameter. - scale_range: scaling_range[0] with be used to generate the 1st scaling factor from - `uniform[-scale_range[0], scale_range[0]) + 1.0`. Similarly, `scale_range[1]` controls - the range of the uniform distribution used to generate the 2nd parameter. + rotate_range: angle range in radians. If element `i` is iterable, then + `uniform[-rotate_range[i][0], rotate_range[i][1])` will be used to generate the rotation parameter + for the ith dimension. If not, `uniform[-rotate_range[i], rotate_range[i])` will be used. This can + be altered on a per-dimension basis. E.g., `((0,3), 1, ...)`: for dim0, rotation will be in range + `[0, 3]`, and for dim1 `[-1, 1]` will be used. Setting a single value will use `[-x, x]` for dim0 + and nothing for the remaining dimensions. + shear_range: shear_range with format matching `rotate_range`. + translate_range: translate_range with format matching `rotate_range`. + scale_range: scaling_range with format matching `rotate_range`. mode: {``"bilinear"``, ``"nearest"``} Interpolation mode to calculate output values. Defaults to ``"bilinear"``. See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample @@ -596,10 +588,10 @@ def __init__( magnitude_range: Tuple[float, float], spatial_size: Optional[Union[Sequence[int], int]] = None, prob: float = 0.1, - rotate_range: Optional[Union[Sequence[float], float]] = None, - shear_range: Optional[Union[Sequence[float], float]] = None, - translate_range: Optional[Union[Sequence[float], float]] = None, - scale_range: Optional[Union[Sequence[float], float]] = None, + rotate_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, + shear_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, + translate_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, + scale_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, mode: GridSampleModeSequence = GridSampleMode.BILINEAR, padding_mode: GridSamplePadModeSequence = GridSamplePadMode.REFLECTION, as_tensor_output: bool = False, @@ -621,19 +613,15 @@ def __init__( prob: probability of returning a randomized affine grid. defaults to 0.1, with 10% chance returns a randomized grid, otherwise returns a ``spatial_size`` centered area extracted from the input image. - rotate_range: angle range in radians. rotate_range[0] with be used to generate the 1st rotation - parameter from `uniform[-rotate_range[0], rotate_range[0])`. Similarly, `rotate_range[1]` and - `rotate_range[2]` are used in 3D affine for the range of 2nd and 3rd axes. - shear_range: shear_range[0] with be used to generate the 1st shearing parameter from - `uniform[-shear_range[0], shear_range[0])`. Similarly, `shear_range[1]` and `shear_range[2]` - controls the range of the uniform distribution used to generate the 2nd and 3rd parameters. - translate_range : translate_range[0] with be used to generate the 1st shift parameter from - `uniform[-translate_range[0], translate_range[0])`. Similarly, `translate_range[1]` and - `translate_range[2]` controls the range of the uniform distribution used to generate - the 2nd and 3rd parameters. - scale_range: scaling_range[0] with be used to generate the 1st scaling factor from - `uniform[-scale_range[0], scale_range[0]) + 1.0`. Similarly, `scale_range[1]` and `scale_range[2]` - controls the range of the uniform distribution used to generate the 2nd and 3rd parameters. + rotate_range: angle range in radians. If element `i` is iterable, then + `uniform[-rotate_range[i][0], rotate_range[i][1])` will be used to generate the rotation parameter + for the ith dimension. If not, `uniform[-rotate_range[i], rotate_range[i])` will be used. This can + be altered on a per-dimension basis. E.g., `((0,3), 1, ...)`: for dim0, rotation will be in range + `[0, 3]`, and for dim1 `[-1, 1]` will be used. Setting a single value will use `[-x, x]` for dim0 + and nothing for the remaining dimensions. + shear_range: shear_range with format matching `rotate_range`. + translate_range: translate_range with format matching `rotate_range`. + scale_range: scaling_range with format matching `rotate_range`. mode: {``"bilinear"``, ``"nearest"``} Interpolation mode to calculate output values. Defaults to ``"bilinear"``. See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample From db4f6ca2457385f3b6b566e9bf613f3b0d980a99 Mon Sep 17 00:00:00 2001 From: Rich <33289025+rijobro@users.noreply.github.com> Date: Wed, 24 Feb 2021 16:55:33 +0000 Subject: [PATCH 2/3] add missing import Signed-off-by: Richard Brown <33289025+rijobro@users.noreply.github.com> --- monai/transforms/spatial/array.py | 1 + 1 file changed, 1 insertion(+) diff --git a/monai/transforms/spatial/array.py b/monai/transforms/spatial/array.py index a6d74b1aa4..0ec86cfc93 100644 --- a/monai/transforms/spatial/array.py +++ b/monai/transforms/spatial/array.py @@ -42,6 +42,7 @@ ensure_tuple_rep, ensure_tuple_size, fall_back_tuple, + issequenceiterable, optional_import, ) From 0d8bdae2209ff0b5704f1bf7e7de9b9c49240eab Mon Sep 17 00:00:00 2001 From: Rich <33289025+rijobro@users.noreply.github.com> Date: Thu, 25 Feb 2021 09:24:14 +0000 Subject: [PATCH 3/3] bug fixes Signed-off-by: Richard Brown <33289025+rijobro@users.noreply.github.com> --- monai/transforms/spatial/array.py | 60 ++++++++++++++------------ monai/transforms/spatial/dictionary.py | 13 +++--- 2 files changed, 41 insertions(+), 32 deletions(-) diff --git a/monai/transforms/spatial/array.py b/monai/transforms/spatial/array.py index 35229be254..d6dbe56f01 100644 --- a/monai/transforms/spatial/array.py +++ b/monai/transforms/spatial/array.py @@ -70,6 +70,8 @@ "Rand3DElastic", ] +RandRange = Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] + class Spacing(Transform): """ @@ -966,10 +968,10 @@ class RandAffineGrid(Randomizable, Transform): def __init__( self, - rotate_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, - shear_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, - translate_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, - scale_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, + rotate_range: RandRange = None, + shear_range: RandRange = None, + translate_range: RandRange = None, + scale_range: RandRange = None, as_tensor_output: bool = True, device: Optional[torch.device] = None, ) -> None: @@ -983,7 +985,8 @@ def __init__( and nothing for the remaining dimensions. shear_range: shear_range with format matching `rotate_range`. translate_range: translate_range with format matching `rotate_range`. - scale_range: scaling_range with format matching `rotate_range`. + scale_range: scaling_range with format matching `rotate_range`. A value of 1.0 is added to the result. + This allows 0 to correspond to no change (i.e., a scaling of 1). as_tensor_output: whether to output tensor instead of numpy array. defaults to True. device: device to store the output grid data. @@ -1007,22 +1010,22 @@ def __init__( self.as_tensor_output = as_tensor_output self.device = device - def _get_rand_param(self, param_range): + def _get_rand_param(self, param_range, add_scalar: float = 0.0): out_param = [] for f in param_range: if issequenceiterable(f): if len(f) != 2: raise ValueError("If giving range as [min,max], should only have two elements per dim.") - out_param.append(self.R.uniform(f[0], f[1])) + out_param.append(self.R.uniform(f[0], f[1]) + add_scalar) elif f is not None: - out_param.append(self.R.uniform(-f, f)) + out_param.append(self.R.uniform(-f, f) + add_scalar) return out_param def randomize(self, data: Optional[Any] = None) -> None: self.rotate_params = self._get_rand_param(self.rotate_range) self.shear_params = self._get_rand_param(self.shear_range) self.translate_params = self._get_rand_param(self.translate_range) - self.scale_params = self._get_rand_param(self.scale_range) + self.scale_params = self._get_rand_param(self.scale_range, 1.0) def __call__( self, spatial_size: Optional[Sequence[int]] = None, grid: Optional[Union[np.ndarray, torch.Tensor]] = None @@ -1284,11 +1287,11 @@ class RandAffine(Randomizable, Transform): def __init__( self, prob: float = 0.1, - rotate_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, - shear_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, - translate_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, - scale_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, - spatial_size: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, + rotate_range: RandRange = None, + shear_range: RandRange = None, + translate_range: RandRange = None, + scale_range: RandRange = None, + spatial_size: Optional[Union[Sequence[int], int]] = None, mode: Union[GridSampleMode, str] = GridSampleMode.BILINEAR, padding_mode: Union[GridSamplePadMode, str] = GridSamplePadMode.REFLECTION, as_tensor_output: bool = True, @@ -1306,7 +1309,8 @@ def __init__( and nothing for the remaining dimensions. shear_range: shear_range with format matching `rotate_range`. translate_range: translate_range with format matching `rotate_range`. - scale_range: scaling_range with format matching `rotate_range`. + scale_range: scaling_range with format matching `rotate_range`. A value of 1.0 is added to the result. + This allows 0 to correspond to no change (i.e., a scaling of 1). spatial_size: output image spatial size. if `spatial_size` and `self.spatial_size` are not defined, or smaller than 1, the transform will use the spatial size of `img`. @@ -1400,11 +1404,11 @@ def __init__( spacing: Union[Tuple[float, float], float], magnitude_range: Tuple[float, float], prob: float = 0.1, - rotate_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, - shear_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, - translate_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, - scale_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, - spatial_size: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, + rotate_range: RandRange = None, + shear_range: RandRange = None, + translate_range: RandRange = None, + scale_range: RandRange = None, + spatial_size: Optional[Union[Tuple[int, int], int]] = None, mode: Union[GridSampleMode, str] = GridSampleMode.BILINEAR, padding_mode: Union[GridSamplePadMode, str] = GridSamplePadMode.REFLECTION, as_tensor_output: bool = False, @@ -1425,7 +1429,8 @@ def __init__( and nothing for the remaining dimensions. shear_range: shear_range with format matching `rotate_range`. translate_range: translate_range with format matching `rotate_range`. - scale_range: scaling_range with format matching `rotate_range`. + scale_range: scaling_range with format matching `rotate_range`. A value of 1.0 is added to the result. + This allows 0 to correspond to no change (i.e., a scaling of 1). spatial_size: specifying output image spatial size [h, w]. if `spatial_size` and `self.spatial_size` are not defined, or smaller than 1, the transform will use the spatial size of `img`. @@ -1526,11 +1531,11 @@ def __init__( sigma_range: Tuple[float, float], magnitude_range: Tuple[float, float], prob: float = 0.1, - rotate_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, - shear_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, - translate_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, - scale_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, - spatial_size: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, + rotate_range: RandRange = None, + shear_range: RandRange = None, + translate_range: RandRange = None, + scale_range: RandRange = None, + spatial_size: Optional[Union[Tuple[int, int, int], int]] = None, mode: Union[GridSampleMode, str] = GridSampleMode.BILINEAR, padding_mode: Union[GridSamplePadMode, str] = GridSamplePadMode.REFLECTION, as_tensor_output: bool = False, @@ -1553,7 +1558,8 @@ def __init__( and nothing for the remaining dimensions. shear_range: shear_range with format matching `rotate_range`. translate_range: translate_range with format matching `rotate_range`. - scale_range: scaling_range with format matching `rotate_range`. + scale_range: scaling_range with format matching `rotate_range`. A value of 1.0 is added to the result. + This allows 0 to correspond to no change (i.e., a scaling of 1). spatial_size: specifying output image spatial size [h, w, d]. if `spatial_size` and `self.spatial_size` are not defined, or smaller than 1, the transform will use the spatial size of `img`. diff --git a/monai/transforms/spatial/dictionary.py b/monai/transforms/spatial/dictionary.py index bbf3a8222e..2c66cd5f50 100644 --- a/monai/transforms/spatial/dictionary.py +++ b/monai/transforms/spatial/dictionary.py @@ -402,7 +402,8 @@ def __init__( and nothing for the remaining dimensions. shear_range: shear_range with format matching `rotate_range`. translate_range: translate_range with format matching `rotate_range`. - scale_range: scaling_range with format matching `rotate_range`. + scale_range: scaling_range with format matching `rotate_range`. A value of 1.0 is added to the result. + This allows 0 to correspond to no change (i.e., a scaling of 1). mode: {``"bilinear"``, ``"nearest"``} Interpolation mode to calculate output values. Defaults to ``"bilinear"``. See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample @@ -470,7 +471,7 @@ def __init__( keys: KeysCollection, spacing: Union[Tuple[float, float], float], magnitude_range: Tuple[float, float], - spatial_size: Optional[Union[Sequence[int], int]] = None, + spatial_size: Optional[Union[Tuple[int, int], int]] = None, prob: float = 0.1, rotate_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, shear_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, @@ -504,7 +505,8 @@ def __init__( and nothing for the remaining dimensions. shear_range: shear_range with format matching `rotate_range`. translate_range: translate_range with format matching `rotate_range`. - scale_range: scaling_range with format matching `rotate_range`. + scale_range: scaling_range with format matching `rotate_range`. A value of 1.0 is added to the result. + This allows 0 to correspond to no change (i.e., a scaling of 1). mode: {``"bilinear"``, ``"nearest"``} Interpolation mode to calculate output values. Defaults to ``"bilinear"``. See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample @@ -586,7 +588,7 @@ def __init__( keys: KeysCollection, sigma_range: Tuple[float, float], magnitude_range: Tuple[float, float], - spatial_size: Optional[Union[Sequence[int], int]] = None, + spatial_size: Optional[Union[Tuple[int, int, int], int]] = None, prob: float = 0.1, rotate_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, shear_range: Optional[Union[Sequence[Union[Tuple[float, float], float]], float]] = None, @@ -621,7 +623,8 @@ def __init__( and nothing for the remaining dimensions. shear_range: shear_range with format matching `rotate_range`. translate_range: translate_range with format matching `rotate_range`. - scale_range: scaling_range with format matching `rotate_range`. + scale_range: scaling_range with format matching `rotate_range`. A value of 1.0 is added to the result. + This allows 0 to correspond to no change (i.e., a scaling of 1). mode: {``"bilinear"``, ``"nearest"``} Interpolation mode to calculate output values. Defaults to ``"bilinear"``. See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample