ML Community Day is November 9! Join us for updates from TensorFlow, JAX, and more Learn more

tf.summary.image

Write an image summary.

Used in the notebooks

Used in the tutorials

See also tf.summary.scalar, tf.summary.SummaryWriter.

Writes a collection of images to the current default summary writer. Data appears in TensorBoard's 'Images' dashboard. Like tf.summary.scalar points, each collection of images is associated with a step and a name. All the image collections with the same name constitute a time series of image collections.

This example writes 2 random grayscale images:

w = tf.summary.create_file_writer('test/logs')
with w.as_default():
  image1 = tf.random.uniform(shape=[8, 8, 1])
  image2 = tf.random.uniform(shape=[8, 8, 1])
  tf.summary.image("grayscale_noise", [image1, image2], step=0)

To avoid clipping, data should be converted to one of the following:

  • floating point values in the range [0,1], or
  • uint8 values in the range [0,255]
# Convert the original dtype=int32 `Tensor` into `dtype=float64`.
rgb_image_float = tf.constant([
  [[1000, 0, 0], [0, 500, 1000]],
]) / 1000
tf.summary.image("picture", [rgb_image_float], step=0)

# Convert original dtype=uint8 `Tensor` into proper range.
rgb_image_uint8 = tf.constant([
  [[1, 1, 0], [0, 0, 1]],
], dtype=tf.uint8) * 255
tf.summary.image("picture", [rgb_image_uint8], step=1)

name A name for this summary. The summary tag used for TensorBoard will be this name prefixed by any active name scopes.
data A Tensor representing pixel data with shape [k, h, w, c], where k is the number of images, h and w are the height and width of the images, and c is the number of channels, which should be 1, 2, 3, or 4 (grayscale, grayscale with alpha, RGB, RGBA). Any of the dimensions may be statically unknown (i.e., None). Floating point data will be clipped to the range [0,1]. Other data types will be clipped into an allowed range for safe casting to uint8, using tf.image.convert_image_dtype.
step Explicit int64-castable monotonic step value for this summary. If omitted, this defaults to tf.summary.experimental.get_step(), which must not be None.
max_outputs Optional int or rank-0 integer Tensor. At most this many images will be emitted at each step. When more than max_outputs many images are provided, the first max_outputs many images will be used and the rest silently discarded.
description Optional long-form description for this summary, as a constant str. Markdown is supported. Defaults to empty.

True on success, or false if no summary was emitted because no default summary writer was available.

ValueError if a default writer exists, but no step was provided and tf.summary.experimental.get_step() is None.