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visualizing results #18
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Do you mean that the visdom not working? |
Sorry, I mean for running Test_model.py |
Oh yes I did not add the visualization code in Test_model.py You can edit by referring the main.py if args.visualize:
if train_config["loss"] == "Lovasz":
grid_outputs = torchvision.utils.make_grid(color_transform((save_est[0] > 0).cpu().data), nrow=6)
else:
grid_outputs = torchvision.utils.make_grid(color_transform(save_est[0].unsqueeze(0).cpu().max(1)[1].data), nrow=6)
my_logger.image_summary(torchvision.utils.make_grid(save_input[0], normalize=True),
opts = dict(title=f'VAL img (epoch: {epoch})',caption=f'VAL img (epoch: {epoch})'))
my_logger.image_summary(grid_outputs,
opts=dict(title=f'VAL output (epoch: {epoch}, step: {str(mIOU_val)})',
caption=f'VAL output (epoch: {epoch}, step: {str(mIOU_val)})', ))
grid_gt = torchvision.utils.make_grid((100 * save_gt[0].cpu()).type('torch.ByteTensor').data,
nrow=6)
my_logger.image_summary(grid_gt,
opts=dict(title=f'VAL gt (epoch: {epoch}, step: {str(mIOU_val)})',
caption=f'VAL gt (epoch: {epoch}, step: {str(mIOU_val)})', )) |
Hello @NhatRio
save_est is the output of the validation function.
save_est is an estimation result from model.
Thanks for your asking
…On Wed, 19 Aug 2020 at 16:25, NhatRio ***@***.***> wrote:
Hi @HYOJINPARK <https://github.com/HYOJINPARK>,
Thanks a lot for your impressive work.
What is "save_est" here? I tried your code above but there is a error from
"save_est".
Have a nice day!
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Setting --visualize to True doesn't appear to do anything.
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