Instead of working with image files such as .png and .jpg, I’ve extracted three variables u, v, w  from a NETCDF file, with dimension as (hours, number of grid points in X, number of grid points in Y). The u,v,w components can be seen as three separate channels, just like an image has RGB channels. Afterwards, I transform all the components into tensors using torch.from_numpy, and reshape them into (hours, channel, gridX, gridY), and concatenate them to get my data. Thus the tensor dimension is (745, 3, 132, 132).
Now I want to plug it in an ESRGAN, https://github.com/xinntao/ESRGAN 2 .
The problem is, the dataloader is using ImageSetFolder class, and take images on the form .png as inputs. In PyTorch we usually use dataloader ImageSetfolder which loads the images automaticailly. However, now my data is already given in tensor form. What I can do from here? For practical use, the tensor data can be treated as RGB images. Thinking about maybe utilizing TensorData class? Or just removing the whole dataloader and sample from my dataset or something.
Help appreciated!