INNER CODE UNIT · Python
values
wenhaochai/StableVideo · app.py:244
values=result[c].reshape(-1, 1).cpu().numpy(),
xi=indices.reshape(-1, 2).cpu().numpy(),
method="linear",
).reshape(res, res)
interpolated = torch.from_numpy(interpolated).float()
interpolated[interpolated.isnan()] = 0.0
f_atlas[i, :, :, c] = interpolated
f_atlas = f_atlas.permute(0, 3, 2, 1)
# aggregate via simple median as begining
agg_atlas, _ = torch.median(f_atlas, dim=0)
if if_net == True:
#####################################
# aggregate net #
#####################################
lr, n_epoch = 1e-3, 500