def image(tag, tensor, rescale=1, dataformats="CHW"):
"""Outputs a `Summary` protocol buffer with images. The summary has up to
`max_images` summary values containing images. The images are built from
`tensor` which must be 3-D with shape `[height, width, channels]` and where
`channels` can be:
* 1: `tensor` is interpreted as Grayscale.
* 3: `tensor` is interpreted as RGB.
* 4: `tensor` is interpreted as RGBA.
Args:
tag: A name for the generated node. Will also serve as a series name in
TensorBoard.
tensor: A 3-D `uint8` or `float32` `Tensor` of shape `[height, width,
channels]` where `channels` is 1, 3, or 4.
'tensor' can either have values in [0, 1] (float32) or [0, 255] (uint8).
The image() function will scale the image values to [0, 255] by applying
a scale factor of either 1 (uint8) or 255 (float32).
Returns:
A scalar `Tensor` of type `string`. The serialized `Summary` protocol
buffer.
"""
tag = tbxsummary._clean_tag(tag)
tensor = tbxmake_np(tensor)
tensor = convert_to_HWC(tensor, dataformats)
# Do not assume that user passes in values in [0, 255], use data type to detect
if tensor.dtype != np.uint8:
tensor = (tensor * 255.0).astype(np.uint8)
image = tbxsummary.make_image(tensor, rescale=rescale)
return TBXSummary(value=[TBXSummary.Value(tag=tag, image=image)])
def add_video(writer,
tag,
tensor_thwc,
global_step=None,
fps=30,
walltime=None):
"""found that add_video from tbX is buggy"""
tag = _clean_tag(tag)
video = make_video(tensor_thwc, fps)
summary = Summary(value=[Summary.Value(tag=tag, image=video)])
writer.file_writer.add_summary(summary, global_step, walltime)
def add_mpl_plot(self, tag, fig, global_step):
if self.__show_mpl:
import matplotlib.pyplot as plt
plt.show()
else:
from PIL import Image
import io
fig.canvas.draw()
pil_image = Image.frombytes('RGB', fig.canvas.get_width_height(),
fig.canvas.tostring_rgb())
output = io.BytesIO()
pil_image.save(output, format='PNG')
pil_image_string = output.getvalue()
output.close()
img_summary = Summary.Image(height=pil_image.height,
width=pil_image.width,
colorspace=3,
encoded_image_string=pil_image_string)
summary = Summary(
value=[Summary.Value(tag=_clean_tag(tag), image=img_summary)])
self.file_writer.add_summary(summary, global_step=global_step)
def _video(self, tag, vid):
tag = tbxsummary._clean_tag(tag)
return TBXSummary(value=[TBXSummary.Value(tag=tag, image=vid)])
def _video(tag, vid):
# noinspection PyProtectedMember
tag = tbxsummary._clean_tag(tag)
return TBXSummary(value=[TBXSummary.Value(tag=tag, image=vid)])
def histogram(name, values, bins, collections=None):
name = _clean_tag(name)
values = make_np(values)
hist = make_histogram(values.astype(float), bins)
return Summary(value=[Summary.Value(tag=name, histo=hist)])
def counter(name, counter_dict):
name = _clean_tag(name)
hist = make_histogram_from_counter(counter_dict)
return Summary(value=[Summary.Value(tag=name, histo=hist)])
def _to_image_summary_safe(tag, tensor):
tag = _clean_tag(tag)
img = make_image_summary(to_image(tensor))
return Summary(value=[Summary.Value(tag=tag, image=img)])
