monai.transforms.spatial.array

A collection of “vanilla” transforms for spatial operations.

Classes

Affine([rotate_params, shear_params, ...])	Transform img given the affine parameters.
AffineGrid([rotate_params, shear_params, ...])	Affine transforms on the coordinates.
Flip([spatial_axis, lazy])	Reverses the order of elements along the given spatial axis.
GridDistortion(num_cells, distort_steps[, ...])
GridPatch(patch_size[, offset, num_patches, ...])	Extract all the patches sweeping the entire image in a row-major sliding-window manner with possible overlaps.
GridSplit([grid, size])	Split the image into patches based on the provided grid in 2D.
Orientation([axcodes, as_closest_canonical, ...])	Change the input image's orientation into the specified based on axcodes.
Rand2DElastic(spacing, magnitude_range[, ...])	Random elastic deformation and affine in 2D.
Rand3DElastic(sigma_range, magnitude_range)	Random elastic deformation and affine in 3D.
RandAffine([prob, rotate_range, ...])	Random affine transform.
RandAffineGrid([rotate_range, shear_range, ...])	Generate randomised affine grid.
RandAxisFlip([prob, lazy])	Randomly select a spatial axis and flip along it.
RandDeformGrid(spacing, magnitude_range[, ...])	Generate random deformation grid.
RandFlip([prob, spatial_axis, lazy])	Randomly flips the image along axes.
RandGridDistortion([num_cells, prob, ...])
RandGridPatch(patch_size[, min_offset, ...])	Extract all the patches sweeping the entire image in a row-major sliding-window manner with possible overlaps, and with random offset for the minimal corner of the image, (0,0) for 2D and (0,0,0) for 3D.
RandRotate([range_x, range_y, range_z, ...])	Randomly rotate the input arrays.
RandRotate90([prob, max_k, spatial_axes, lazy])	With probability prob, input arrays are rotated by 90 degrees in the plane specified by spatial_axes.
RandSimulateLowResolution([prob, ...])	Random simulation of low resolution corresponding to nnU-Net's SimulateLowResolutionTransform (MIC-DKFZ/batchgenerators) First, the array/tensor is resampled at lower resolution as determined by the zoom_factor which is uniformly sampled from the zoom_range.
RandZoom([prob, min_zoom, max_zoom, mode, ...])	Randomly zooms input arrays with given probability within given zoom range.
Resample([mode, padding_mode, norm_coords, ...])
ResampleToMatch([mode, padding_mode, ...])	Resample an image to match given metadata.
Resize(spatial_size[, size_mode, mode, ...])	Resize the input image to given spatial size (with scaling, not cropping/padding).
Rotate(angle[, keep_size, mode, ...])	Rotates an input image by given angle using monai.networks.layers.AffineTransform.
Rotate90([k, spatial_axes, lazy])	Rotate an array by 90 degrees in the plane specified by axes.
Spacing(pixdim[, diagonal, mode, ...])	Resample input image into the specified pixdim.
SpatialResample([mode, padding_mode, ...])	Resample input image from the orientation/spacing defined by src_affine affine matrix into the ones specified by dst_affine affine matrix.
Zoom(zoom[, mode, padding_mode, ...])	Zooms an ND image using torch.nn.functional.interpolate.