def _image3_animated_gif(tag: str,
image: Union[np.ndarray, torch.Tensor],
scale_factor: float = 1.0) -> Summary:
"""Function to actually create the animated gif.
Args:
tag: Data identifier
image: 3D image tensors expected to be in `HWD` format
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
"""
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.Image(height=10,
width=10,
colorspace=1,
encoded_image_string=img_str)
image_summary = Summary.Value(tag=tag, image=summary_image_str)
return Summary(value=[image_summary])
def _ImageSummary(tag, height, width, colorspace, encoded_image):
from tensorboard.compat.proto.summary_pb2 import Summary
image = Summary.Image(height=height,
width=width,
colorspace=colorspace,
encoded_image_string=encoded_image)
return Summary(value=[Summary.Value(tag=tag, image=image)])
def make_image(tensor, rescale=1, rois=None):
"""Convert a numpy representation of an image to Image protobuf"""
from PIL import Image
height, width, channel = tensor.shape
scaled_height = int(height * rescale)
scaled_width = int(width * rescale)
image = Image.fromarray(tensor)
if rois is not None:
image = draw_boxes(image, rois)
image = image.resize((scaled_width, scaled_height), Image.ANTIALIAS)
import io
output = io.BytesIO()
image.save(output, format='PNG')
image_string = output.getvalue()
output.close()
return Summary.Image(height=height,
width=width,
colorspace=channel,
encoded_image_string=image_string)
def make_video(tensor, fps):
try:
import moviepy # noqa: F401
except ImportError:
print("add_video needs package moviepy")
return
try:
from moviepy import editor as mpy
except ImportError:
print(
"moviepy is installed, but can't import moviepy.editor.",
"Some packages could be missing [imageio, requests]",
)
return
import tempfile
t, h, w, c = tensor.shape
# encode sequence of images into gif string
clip = mpy.ImageSequenceClip(list(tensor), fps=fps)
filename = tempfile.NamedTemporaryFile(suffix=".gif", delete=False).name
try: # newer version of moviepy use logger instead of progress_bar argument.
clip.write_gif(filename, verbose=False, logger=None)
except TypeError:
try: # older version of moviepy does not support progress_bar argument.
clip.write_gif(filename, verbose=False, progress_bar=False)
except TypeError:
clip.write_gif(filename, verbose=False)
with open(filename, "rb") as f:
tensor_string = f.read()
try:
os.remove(filename)
except OSError:
logger.warning("The temporary file used by moviepy cannot be deleted.")
return Summary.Image(height=h,
width=w,
colorspace=c,
encoded_image_string=tensor_string)
def make_video(tensor, fps):
try:
import moviepy # noqa: F401
except ImportError:
print('add_video needs package moviepy')
return
try:
from moviepy import editor as mpy
except ImportError:
print("moviepy is installed, but can't import moviepy.editor.",
"Some packages could be missing [imageio, requests]")
return
import tempfile
t, h, w, c = tensor.shape
# encode sequence of images into gif string
clip = mpy.ImageSequenceClip(list(tensor), fps=fps)
with tempfile.NamedTemporaryFile() as f:
filename = f.name + '.gif'
try:
clip.write_gif(filename, verbose=False, progress_bar=False)
except TypeError:
clip.write_gif(filename, verbose=False)
with open(filename, 'rb') as f:
tensor_string = f.read()
try:
os.remove(filename)
except OSError:
pass
return Summary.Image(height=h,
width=w,
colorspace=c,
encoded_image_string=tensor_string)
def Image(**kw):
from tensorboard.compat.proto.summary_pb2 import Summary
return Summary.Image(**kw)