Outputs a Summary protocol buffer with images.
tf.raw_ops.ImageSummary(
tag,
tensor,
max_images=3,
bad_color=_execute.make_tensor(\n 'dtype: DT_UINT8 tensor_shape { dim { size: 4 } } int_val: 255 int_val: 0 int_val: 0 int_val: 255 '\n , 'bad_color'),
name=None
)
The summary has up to max_images summary values containing images. The
images are built from tensor which must be 4-D with shape [batch_size,
height, width, channels] and where channels can be:
- 1:
tensoris interpreted as Grayscale. - 3:
tensoris interpreted as RGB. - 4:
tensoris interpreted as RGBA.
The images have the same number of channels as the input tensor. For float
input, the values are normalized one image at a time to fit in the range
[0, 255]. uint8 values are unchanged. The op uses two different
normalization algorithms:
If the input values are all positive, they are rescaled so the largest one is 255.
If any input value is negative, the values are shifted so input value 0.0 is at 127. They are then rescaled so that either the smallest value is 0, or the largest one is 255.
The tag argument is a scalar Tensor of type string. It is used to
build the tag of the summary values:
- If
max_imagesis 1, the summary value tag is 'tag/image'. - If
max_imagesis greater than 1, the summary value tags are generated sequentially as 'tag/image/0', 'tag/image/1', etc.
The bad_color argument is the color to use in the generated images for
non-finite input values. It is a uint8 1-D tensor of length channels.
Each element must be in the range [0, 255] (It represents the value of a
pixel in the output image). Non-finite values in the input tensor are
replaced by this tensor in the output image. The default value is the color
red.
Returns | |
|---|---|
A Tensor of type string.
|