rising Documentation¶
rising is a highly performant, PyTorch only, framework for efficient data augmentation with native
support for volumetric data
Getting Started
Python API
- rising.loading
- rising.ops
- rising.random
- rising.transforms
- Transformation Base Classes
- Compose Transforms
- Affine Transforms
- Channel Transforms
- Cropping Transforms
- Format Transforms
- Intensity Transforms
ClampExponentialNoiseGammaCorrectionGaussianNoiseInvertAmplitudeNoiseNormMeanStdNormMinMaxNormRangeNormZeroMeanUnitStdRandomAddValueRandomBezierTransformRandomScaleValueRandomValuePerChannel- Clamp
- NormRange
- NormMinMax
- NormZeroMeanUnitStd
- NormMeanStd
- Noise
- GaussianNoise
- ExponentialNoise
- GammaCorrection
- RandomValuePerChannel
- RandomAddValue
- RandomScaleValue
- Kernel Transforms
- Spatial Transforms
- Tensor Transforms
- Utility Transforms
- rising.transforms.functional
- Affine Transforms
affine_image_transform()affine_point_transform()create_rotation()create_scale()create_translation()parametrize_matrix()- affine_image_transform
- affine_point_transform
- parametrize_matrix
- create_rotation
- create_rotation_2d
- create_rotation_3d
- create_rotation_3d_0
- create_rotation_3d_1
- create_rotation_3d_2
- create_scale
- create_translation
- expand_scalar_param
- Channel Transforms
- Cropping Transforms
- Intensity Transforms
- Spatial Transforms
- Tensor Transforms
- Utility Transforms
- Affine Transforms
- rising.utils
- Affines
deg_to_rad()get_batched_eye()matrix_revert_coordinate_order()matrix_to_cartesian()matrix_to_homogeneous()points_to_cartesian()points_to_homogeneous()unit_box()- points_to_homogeneous
- matrix_to_homogeneous
- matrix_to_cartesian
- points_to_cartesian
- matrix_revert_coordinate_order
- get_batched_eye
- deg_to_rad
- unit_box
- Type Checks
- Reshaping
- Affines
Community
