iSeeBetter: Spatio-Temporal Video Super Resolution using Recurrent-Generative Back-Projection Networks | Python3 | PyTorch | GANs | CNNs | ResNets | RNNs | Published in Springer Journal of Computational Visual Media, September 2020, Tsinghua University Press
I don't understand this part of the test code,I think testing_data_loader is the test set data,only one image ,Why does batch have a lot of data,such as batch[0]、batch[1].......
code:
for batch in testing_data_loader:
import pdb;pdb.set_trace()
input, target, neigbor, flow, bicubic = batch[0], batch[1], batch[2], batch[3], batch[4]
with torch.no_grad():
if cuda:
input = Variable(input).cuda(gpus_list[0])
bicubic = Variable(bicubic).cuda(gpus_list[0])
neigbor = [Variable(j).cuda(gpus_list[0]) for j in neigbor]
flow = [Variable(j).cuda(gpus_list[0]).float() for j in flow]
else:
input = Variable(input).to(device=device, dtype=torch.float)
bicubic = Variable(bicubic).to(device=device, dtype=torch.float)
neigbor = [Variable(j).to(device=device, dtype=torch.float) for j in neigbor]
flow = [Variable(j).to(device=device, dtype=torch.float) for j in flow]
I don't understand this part of the test code,I think testing_data_loader is the test set data,only one image ,Why does batch have a lot of data,such as batch[0]、batch[1]....... code: for batch in testing_data_loader:
import pdb;pdb.set_trace()