Crop images
to a specified height
and width
.
tf.keras.ops.image.crop_images(
images,
top_cropping=None,
left_cropping=None,
target_height=None,
target_width=None,
bottom_cropping=None,
right_cropping=None
)
Args |
images
|
4-D batch of images of shape (batch, height, width, channels)
or 3-D single image of shape (height, width, channels) .
|
top_cropping
|
Number of columns to crop from the top.
|
bottom_cropping
|
Number of columns to crop from the bottom.
|
left_cropping
|
Number of columns to crop from the left.
|
right_cropping
|
Number of columns to crop from the right.
|
target_height
|
Height of the output images.
|
target_width
|
Width of the output images.
|
Returns |
If images were 4D, a 4D float Tensor of shape
(batch, target_height, target_width, channels)
If images were 3D, a 3D float Tensor of shape
(target_height, target_width, channels)
|
Example:
images = np.reshape(np.arange(1, 28, dtype="float32"), [3, 3, 3])
images[:,:,0] # print the first channel of the images
array([[ 1., 4., 7.],
[10., 13., 16.],
[19., 22., 25.]], dtype=float32)
cropped_images = keras.image.crop_images(images, 0, 0, 2, 2)
cropped_images[:,:,0] # print the first channel of the cropped images
array([[ 1., 4.],
[10., 13.]], dtype=float32)