Module: tf.image

Image ops.

The tf.image module contains various functions for image processing and decoding-encoding Ops.

Many of the encoding/decoding functions are also available in the core module.

Image processing


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.

The Class tf.image.ResizeMethod provides various resize methods like bilinear, nearest_neighbor.

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 Tensor represents batch_size images.