tfm.vision.preprocess_ops.random_crop

Randomly crop the image and boxes, filtering labels.

tfm.vision.preprocess_ops.random_crop(
    image,
    boxes,
    labels,
    min_scale=0.3,
    aspect_ratio_range=(0.5, 2.0),
    min_overlap_params=(0.0, 1.4, 0.2, 0.1),
    max_retry=50,
    seed=None
)

image a 'Tensor' of shape [height, width, 3] representing the input image.
boxes a 'Tensor' of shape [N, 4] representing the ground-truth bounding boxes with (ymin, xmin, ymax, xmax).
labels a 'Tensor' of shape [N,] representing the class labels of the boxes.
min_scale a 'float' in [0.0, 1.0) indicating the lower bound of the random scale variable.
aspect_ratio_range a list of two 'float' that specifies the lower and upper bound of the random aspect ratio.
min_overlap_params a list of four 'float' representing the min value, max value, step size, and offset for the minimum overlap sample.
max_retry an 'int' representing the number of trials for cropping. If it is exhausted, no cropping will be performed.
seed the random number seed of int, but could be None.

image a Tensor representing the random cropped image. Can be the original image if max_retry is exhausted.
boxes a Tensor representing the bounding boxes in the cropped image.
labels a Tensor representing the new bounding boxes' labels.