|TensorFlow 1 version|
tf.image module contains various functions for image
processing and decoding-encoding Ops.
Many of the encoding/decoding functions are also available in the
The resizing Ops accept input images as tensors of several types. They always output resized images as float32 tensors.
The convenience function
tf.image.resize supports both 4-D
and 3-D tensors as input and output. 4-D tensors are for batches of images,
3-D tensors for individual images.
Resized images will be distorted if their original aspect ratio is not the same as size. To avoid distortions see tf.image.resize_with_pad.
tf.image.ResizeMethod provides various resize methods like
Converting Between Colorspaces
Image ops work either on individual images or on batches of images, depending on the shape of their input Tensor.
If 3-D, the shape is
[height, width, channels], and the Tensor represents one
image. If 4-D, the shape is
[batch_size, height, width, channels], and the