Resize quantized images to size using quantized bilinear interpolation.
tf.raw_ops.QuantizedResizeBilinear(
images, size, min, max, align_corners=False, half_pixel_centers=False, name=None
)
Input images and output images must be quantized types.
Args | |
|---|---|
images
|
A Tensor. Must be one of the following types: quint8, qint32, float32.
4-D with shape [batch, height, width, channels].
|
size
|
A 1-D int32 Tensor of 2 elements: new_height, new_width. The
new size for the images.
|
min
|
A Tensor of type float32.
|
max
|
A Tensor of type float32.
|
align_corners
|
An optional bool. Defaults to False.
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.
|
half_pixel_centers
|
An optional bool. Defaults to False.
|
name
|
A name for the operation (optional). |
Returns | |
|---|---|
A tuple of Tensor objects (resized_images, out_min, out_max).
|
|
resized_images
|
A Tensor. Has the same type as images.
|
out_min
|
A Tensor of type float32.
|
out_max
|
A Tensor of type float32.
|