INNER CODE UNIT · Python
result
wenhaochai/StableVideo · app.py:232
result = alpha * result
# buffer for training
result_copy = result.clone().cuda()
result_copy.requires_grad = True
result_list.append(result_copy)
# map to atlas
uv = (self.crops['foreground_uvs'][i].reshape(-1, 2) * 0.5 + 0.5) * res
for c in range(3):
interpolated = scipy.interpolate.griddata(
points=uv.cpu().numpy(),
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