tf.image.resize_images

Resize images to size using the specified method.

View aliases

Main aliases

tf.image.resize

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.image.resize, tf.compat.v1.image.resize_images

tf.image.resize_images(
    images, size, method=ResizeMethodV1.BILINEAR, align_corners=False,
    preserve_aspect_ratio=False, name=None
)

Resized images will be distorted if their original aspect ratio is not the same as size. To avoid distortions see tf.compat.v1.image.resize_image_with_pad.

method can be one of:

• ResizeMethod.BILINEAR: Bilinear interpolation.
• ResizeMethod.NEAREST_NEIGHBOR: Nearest neighbor interpolation.
• ResizeMethod.BICUBIC: Bicubic interpolation.
• ResizeMethod.AREA: Area interpolation.

The return value has the same type as images if method is ResizeMethod.NEAREST_NEIGHBOR. It will also have the same type as images if the size of images can be statically determined to be the same as size, because images is returned in this case. Otherwise, the return value has type float32.

Args
images	4-D Tensor of shape [batch, height, width, channels] or 3-D Tensor of shape [height, width, channels].
size	A 1-D int32 Tensor of 2 elements: new_height, new_width. The new size for the images.
method	ResizeMethod. Defaults to ResizeMethod.BILINEAR.
align_corners	bool. If True, the centers of the 4 corner pixels of the input and output tensors are aligned, preserving the values at the corner pixels. Defaults to False.
preserve_aspect_ratio	Whether to preserve the aspect ratio. If this is set, then images will be resized to a size that fits in size while preserving the aspect ratio of the original image. Scales up the image if size is bigger than the current size of the image. Defaults to False.
name	A name for this operation (optional).

Raises
ValueError	if the shape of images is incompatible with the shape arguments to this function
ValueError	if size has invalid shape or type.
ValueError	if an unsupported resize method is specified.

Returns
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].