tf.image.central_crop

TensorFlow 1 version View source on GitHub

Crop the central region of the image(s).

Used in the notebooks

Used in the tutorials

Remove the outer parts of an image but retain the central region of the image along each dimension. If we specify central_fraction = 0.5, this function returns the region marked with "X" in the below diagram.

 --------
|        |
|  XXXX  |
|  XXXX  |
|        |   where "X" is the central 50% of the image.
 --------

This function works on either a single image (image is a 3-D Tensor), or a batch of images (image is a 4-D Tensor).

Usage Example:

x = [[[1.0, 2.0, 3.0],
      [4.0, 5.0, 6.0],
      [7.0, 8.0, 9.0],
      [10.0, 11.0, 12.0]],
    [[13.0, 14.0, 15.0],
      [16.0, 17.0, 18.0],
      [19.0, 20.0, 21.0],
      [22.0, 23.0, 24.0]],
    [[25.0, 26.0, 27.0],
      [28.0, 29.0, 30.0],
      [31.0, 32.0, 33.0],
      [34.0, 35.0, 36.0]],
    [[37.0, 38.0, 39.0],
      [40.0, 41.0, 42.0],
      [43.0, 44.0, 45.0],
      [46.0, 47.0, 48.0]]]
tf.image.central_crop(x, 0.5)
<tf.Tensor: shape=(2, 2, 3), dtype=float32, numpy=
array([[[16., 17., 18.],
        [19., 20., 21.]],
       [[28., 29., 30.],
        [31., 32., 33.]]], dtype=float32)>

image Either a 3-D float Tensor of shape [height, width, depth], or a 4-D Tensor of shape [batch_size, height, width, depth].
central_fraction float (0, 1], fraction of size to crop

ValueError if central_crop_fraction is not within (0, 1].

3-D / 4-D float Tensor, as per the input.