tf.image.resize_with_crop_or_pad | TensorFlow v2.16.1 (original) (raw)
tf.image.resize_with_crop_or_pad
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Crops and/or pads an image to a target width and height.
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Compat aliases for migration
SeeMigration guide for more details.
tf.compat.v1.image.resize_image_with_crop_or_pad, tf.compat.v1.image.resize_with_crop_or_pad
tf.image.resize_with_crop_or_pad(
image, target_height, target_width
)
Used in the notebooks
| Used in the tutorials |
|---|
| Data augmentation Artistic Style Transfer with TensorFlow Lite |
Resizes an image to a target width and height by either centrally cropping the image or padding it evenly with zeros.
If width or height is greater than the specified target_width ortarget_height respectively, this op centrally crops along that dimension.
For example:
image = np.arange(75).reshape(5, 5, 3) # create 3-D image input
image[:,:,0] # print first channel just for demo purposes
array([[ 0, 3, 6, 9, 12],
[15, 18, 21, 24, 27],
[30, 33, 36, 39, 42],
[45, 48, 51, 54, 57],
[60, 63, 66, 69, 72]])
image = tf.image.resize_with_crop_or_pad(image, 3, 3) # crop
# print first channel for demo purposes; centrally cropped output
image[:,:,0]
<tf.Tensor: shape=(3, 3), dtype=int64, numpy=
array([[18, 21, 24],
[33, 36, 39],
[48, 51, 54]])>
If width or height is smaller than the specified target_width ortarget_height respectively, this op centrally pads with 0 along that dimension.
For example:
image = np.arange(1, 28).reshape(3, 3, 3) # create 3-D image input
image[:,:,0] # print first channel just for demo purposes
array([[ 1, 4, 7],
[10, 13, 16],
[19, 22, 25]])
image = tf.image.resize_with_crop_or_pad(image, 5, 5) # pad
# print first channel for demo purposes; we should see 0 paddings
image[:,:,0]
<tf.Tensor: shape=(5, 5), dtype=int64, numpy=
array([[ 0, 0, 0, 0, 0],
[ 0, 1, 4, 7, 0],
[ 0, 10, 13, 16, 0],
[ 0, 19, 22, 25, 0],
[ 0, 0, 0, 0, 0]])>
| Args | |
|---|---|
| image | 4-D Tensor of shape [batch, height, width, channels] or 3-D Tensor of shape [height, width, channels]. |
| target_height | Target height. |
| target_width | Target width. |
| Raises | |
|---|---|
| ValueError | if target_height or target_width are zero or negative. |
| Returns |
|---|
| Cropped and/or padded image. If images was 4-D, a 4-D float Tensor of shape[batch, new_height, new_width, channels]. If images was 3-D, a 3-D float Tensor of shape[new_height, new_width, channels]. |