fovi.utils.std_transforms
- fovi.utils.std_transforms.get_std_transforms(where, flip, color_jitter, gray, blur, device, dtype, pointcloud_mode=False, solarize=False, normalize=True)[source]
Build standard augmentation pipelines for training.
Creates three transform pipelines (loader, pre-warp, post-warp) that can be applied at different stages of the data processing pipeline.
- Parameters:
where (str) – Where to apply transforms. One of ‘loader’, ‘pre_warp’, or ‘post_warp’. Determines which pipeline contains the augmentations.
flip (bool) – Whether to include random horizontal flip.
color_jitter (bool) – Whether to include color jitter augmentation.
gray (bool) – Whether to include random grayscale.
blur (bool) – Whether to include Gaussian blur.
device – Device to place transforms on.
dtype – Data type for tensors.
pointcloud_mode (bool, optional) – Whether to use pointcloud-compatible transforms. Defaults to False.
solarize (bool, optional) – Whether to include random solarization. Defaults to False.
normalize (bool, optional) – Whether to include ImageNet normalization. Defaults to True.
- Returns:
- (loader_transforms, pre_transforms, post_transforms) where each
is either a Compose object or None if empty.
- Return type: