Pipelining augmentations with Albumentations

albumetations_pipelining.py

# Compose a complex augmentation pipeline
augmentation_pipeline = A.Compose(
    [
        A.HorizontalFlip(p = 0.5), # apply horizontal flip to 50% of images
        A.OneOf(
            [
                # apply one of transforms to 50% of images
                A.RandomContrast(), # apply random contrast
                A.RandomGamma(), # apply random gamma
                A.RandomBrightness(), # apply random brightness
            ],
            p = 0.5
        ),
        A.OneOf(
            [
                # apply one of transforms to 50% images
                A.ElasticTransform(
                    alpha = 120,
                    sigma = 120 * 0.05,
                    alpha_affine = 120 * 0.03
                ),
                A.GridDistortion(),
                A.OpticalDistortion(
                    distort_limit = 2,
                    shift_limit = 0.5
                ),
            ],
            p = 0.5
        )
    ],
    p = 1
)

# Apply pipeline to sample image
images_aug = np.array([augmentation_pipeline(image = image)['image'] for _ in range(16)])