tfm.vision.preprocess_ops.resize_and_crop_image_v2

Resizes the input image to output size (Faster R-CNN style).

tfm.vision.preprocess_ops.resize_and_crop_image_v2(
    image,
    short_side,
    long_side,
    padded_size,
    aug_scale_min=1.0,
    aug_scale_max=1.0,
    seed=1,
    method=tf.image.ResizeMethod.BILINEAR
)

Resize and pad images given the specified short / long side length and the stride size.

Here are the preprocessing steps.

  1. For a given image, keep its aspect ratio and first try to rescale the short side of the original image to short_side.
  2. If the scaled image after 1 has a long side that exceeds long_side, keep the aspect ratio and rescale the long side of the image to long_side.
  3. (Optional) Apply random jittering according to aug_scale_min and aug_scale_max. By default this step is skipped.
  4. Pad the rescaled image to the padded_size.

image a Tensor of shape [height, width, 3] representing an image.
short_side a scalar Tensor or int representing the desired short side to be rescaled to.
long_side a scalar Tensor or int representing the desired long side to be rescaled to.
padded_size a Tensor or int list/tuple of two elements representing [height, width] of the padded output image size.
aug_scale_min a float with range between [0, 1.0] representing minimum random scale applied for training scale jittering.
aug_scale_max a float with range between [1.0, inf] representing maximum random scale applied for training scale jittering.
seed seed for random scale jittering.
method function to resize input image to scaled image.

output_image Tensor of shape [height, width, 3] where [height, width] equals to output_size.
image_info a 2D Tensor that encodes the information of the image and the applied preprocessing. It is in the format of [[original_height, original_width], [desired_height, desired_width], [y_scale, x_scale], [y_offset, x_offset]], where [desired_height, desired_width] is the actual scaled image size, and [y_scale, x_scale] is the scaling factor, which is the ratio of scaled dimension / original dimension.