I was trying trying to run tensorboard module in Pytorch with 3D image data with the following code:
class GetTB(object):
def __init__(self, img, lbl, model):
self.image = img
self.label = lbl
self.model = model
def WorkTB(self):
tb = SummaryWriter()
grid = torchvision.utils.make_grid(self.image)
tb.add_image("images", grid)
tb.add_graph(model, self.image)
tb.close()
A = GetTB(images, labels, model).WorkTB()
A bit about the images and labels is: images have B,C,H,W,D
dimensions. which is C=1 for images and C=5/6 for the one-hot encoded label.
Now in my search the make_grid()
documentation mentions images to be:
Args:
tensor (Tensor or list): 4D mini-batch Tensor of shape (B x C x H x W)
or a list of images all of the same size.
Does it indicate tensorboard
only works with RGB image data?
I also couldn’t find any sort of implementation tutorial/article for specific 3D data. If anyone updates would be highly appreciated.
Thanks