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View Code? Open in Web Editor NEWA Dual Camera System for High Spatiotemporal Resolution Video Acquisition (TPAMI 2020)
Home Page: https://NJUVISION.github.io/AWnet
License: MIT License
A Dual Camera System for High Spatiotemporal Resolution Video Acquisition (TPAMI 2020)
Home Page: https://NJUVISION.github.io/AWnet
License: MIT License
Hi
I am playing around with your code and I learnt that these lines are non-differentiable and do not let the gradient compute. Can you please guide me on how you solved that? or its just me who is having this issue.
mask = torch.autograd.Variable(torch.ones(x.size())).cuda()
mask = nn.functional.grid_sample(mask, vgrid)
# if W==128:
# np.save('mask.npy', mask.cpu().data.numpy())
# np.save('warp.npy', output.cpu().data.numpy())
mask[mask<0.9999] = 0
mask[mask>0] = 1
return output*mask,mask
for the simplest code to reproduce the error,
import torch
use_cuda = torch.cuda.is_available()
device = torch.device("cuda" if use_cuda else "cpu")
torch.cuda.set_device(0)
criteria = torch.nn.L1Loss()
# import awnet_pwcnet #please adjust as per your code
net = awnet_pwcnet.PWCDCNet().cuda()
#net = torch.nn.Conv2d(6, 3, 1).cuda()
optimizer = torch.optim.Adam(net.parameters(), lr = 0.1)
inp = Variable(torch.rand(1,3,256,448).to(device),requires_grad = True)
snd = Variable(torch.rand(1,3,256,448).to(device),requires_grad = True)
gt = Variable(torch.rand(1,2,256,448).to(device),requires_grad = True)
x = torch.cat((inp,snd),1)
# for layer in net.children():
# for param in layer.parameters():
# print(param)
for i in range(1,5):
optimizer.zero_grad()
out = net(x)
out = F.interpolate(out,scale_factor=4,mode='bilinear',align_corners=False)*20
loss = criteria(out,gt)
print(out.shape)
loss.backward()#retain_graph= True)
print(net.state_dict())
optimizer.step()
and i get this error which is caused by these lines as when I replaced the warping function with this one, it started to train.
RuntimeError: one of the variables needed for gradient computation has been modified by an inplace operation
Thanks alot.
Hi,
Can you please guide me which toolkit you used for the calculation of evaluation metrics? SSIM/PSNR?
Thanks a lot.
Hi,
When I try to download the pretrain-model, find the web link for pretrain-model is "Could Not Connect". Is there another way that we can acquire the pretrain-model. Thanks ~
Hi,
Its an amazing work. please upload the pre-trained weights to play around with. Thanks.
Hello, in the paper you mentioned using pretrained PWC_Net to initialize our FlowNet, I want to ask how to get this pretrained PWC_Net? Thank you!
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