# Copyright 2020 MONAI Consortium
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import numpy as np
import PIL
from PIL.GifImagePlugin import Image as GifImage
from tensorboard.compat.proto import summary_pb2
def _image3_animated_gif(imp, scale_factor=1):
"""
Function to actually create the animated gif.
Args:
imp: tuple of tag and a list of image tensors
scale_factor: amount to multiply values by. if the image data is between 0 and 1, using 255 for this value will
scale it to displayable range
"""
(tag, ims) = imp
ims = [
(np.asarray((ims[:, :, i])) * scale_factor).astype(np.uint8)
for i in range(ims.shape[2])
]
ims = [GifImage.fromarray(im) for im in ims]
img_str = b''
for b_data in PIL.GifImagePlugin.getheader(ims[0])[0]:
img_str += b_data
img_str += b'\x21\xFF\x0B\x4E\x45\x54\x53\x43\x41\x50' \
b'\x45\x32\x2E\x30\x03\x01\x00\x00\x00'
for i in ims:
for b_data in PIL.GifImagePlugin.getdata(i):
img_str += b_data
img_str += b'\x3B'
summary_image_str = summary_pb2.Summary.Image(
height=10, width=10, colorspace=1, encoded_image_string=img_str)
image_summary = summary_pb2.Summary.Value(tag=tag, image=summary_image_str)
return summary_pb2.Summary(value=[image_summary])
[docs]def make_animated_gif_summary(tag,
tensor,
max_out=3,
animation_axes=(3,),
image_axes=(1, 2),
other_indices=None,
scale_factor=1):
"""
Creates an animated gif out of an image tensor and returns Summary.
Args:
tag: Data identifier
tensor: tensor for the image, expected to be in CHWD format
max_out: maximum number of slices to animate through
animation_axes: axis to animate on (not currently used)
image_axes: axes of image (not currently used)
other_indices: (not currently used)
scale_factor: amount to multiply values by.
if the image data is between 0 and 1, using 255 for this value will scale it to displayable range
"""
if max_out == 1:
suffix = '/image'
else:
suffix = '/image/{}'
if other_indices is None:
other_indices = {}
axis_order = [0] + animation_axes + image_axes
slicing = []
for i in range(len(tensor.shape)):
if i in axis_order:
slicing.append(slice(None))
else:
other_ind = other_indices.get(i, 0)
slicing.append(slice(other_ind, other_ind + 1))
tensor = tensor[tuple(slicing)]
for it_i in range(min(max_out, list(tensor.shape)[0])):
inp = [
tag + suffix.format(it_i), tensor[it_i, :, :, :]
]
summary_op = _image3_animated_gif(inp, scale_factor)
return summary_op
[docs]def add_animated_gif(writer, tag, image_tensor, max_out, scale_factor, global_step=None):
"""
Creates an animated gif out of an image tensor and writes it with SummaryWriter.
Args:
writer: Tensorboard SummaryWriter to write to
tag: Data identifier
image_tensor: tensor for the image to add, expected to be in CDHW format
max_out: maximum number of slices to animate through
scale_factor: amount to multiply values by. If the image data is between 0 and 1, using 255 for this value will
scale it to displayable range
global_step: Global step value to record
"""
writer._get_file_writer().add_summary(make_animated_gif_summary(tag, image_tensor, max_out=max_out,
animation_axes=[1], image_axes=[2, 3],
scale_factor=scale_factor), global_step)
[docs]def add_animated_gif_no_channels(writer, tag, image_tensor, max_out, scale_factor, global_step=None):
"""
Creates an animated gif out of an image tensor and writes it with SummaryWriter.
Args:
writer: Tensorboard SummaryWriter to write to
tag: Data identifier
image_tensor: tensor for the image to add, expected to be in DHW format
max_out: maximum number of slices to animate through
scale_factor: amount to multiply values by. If the image data is between 0 and 1, using 255 for this value will
scale it to displayable range
global_step: Global step value to record
"""
writer._get_file_writer().add_summary(make_animated_gif_summary(tag, image_tensor.unsqueeze(0),
max_out=max_out, animation_axes=[1],
image_axes=[2, 3], scale_factor=scale_factor),
global_step)