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])
def _image3_animated_gif(tag: str,
image: Union[np.array, torch.Tensor],
scale_factor: float = 1):
"""Function to actually create the animated gif.
Args:
tag (str): Data identifier
image (np.array or Tensor): 3D image tensors expected to be in `HWD` format
scale_factor (float): 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
"""
assert len(
image.shape
) == 3, "3D image tensors expected to be in `HWD` format, len(image.shape) != 3"
ims = [(np.asarray((image[:, :, i])) * scale_factor).astype(np.uint8)
for i in range(image.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])
def _image3_animated_gif(tag, ims):
check_module('PIL')
import PIL
from PIL.GifImagePlugin import Image as GIF
# x=numpy.random.randint(0,256,[10,10,10],numpy.uint8)
ims = [np.asarray((ims[i, :, :]).astype(np.uint8))
for i in range(ims.shape[0])]
ims = [GIF.fromarray(im) for im in ims]
s = b''
for b in PIL.GifImagePlugin.getheader(ims[0])[0]:
s += b
s += 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 in PIL.GifImagePlugin.getdata(i):
s += b
s += b'\x3B'
if IS_PYTHON2:
s = str(s)
summary_image_str = summary_pb2.Summary.Image(
height=10, width=10, colorspace=1, encoded_image_string=s)
image_summary = summary_pb2.Summary.Value(
tag=tag, image=summary_image_str)
return [summary_pb2.Summary(value=[image_summary]).SerializeToString()]
def _image3_animated_gif(tag, ims):
PIL = require_module('PIL')
from PIL.GifImagePlugin import Image as GIF
# x=numpy.random.randint(0,256,[10,10,10],numpy.uint8)
ims = [np.asarray((ims[i, :, :]).astype(np.uint8))
for i in range(ims.shape[0])]
ims = [GIF.fromarray(im) for im in ims]
s = b''
for b in PIL.GifImagePlugin.getheader(ims[0])[0]:
s += b
s += 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 in PIL.GifImagePlugin.getdata(i):
s += b
s += b'\x3B'
if IS_PYTHON2:
s = str(s)
summary_image_str = summary_pb2.Summary.Image(
height=10, width=10, colorspace=1, encoded_image_string=s)
image_summary = summary_pb2.Summary.Value(
tag=tag, image=summary_image_str)
return [summary_pb2.Summary(value=[image_summary]).SerializeToString()]
