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 . |
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/raw_ops/QuantizedResizeBilinear