Each of these tensors should take approx. 6.3MB as seen here:
x = torch.randn(7, 368, 640)
print('expected size ', x.nelement() * 4 / 1024**2, 'MB')
> expected size  6.2890625 MB
torch.save(x, 'tmp.pt')

print('file size ', os.stat('tmp.pt').st_size / 1024**2, 'MB')
> file size  6.289786338806152 MB

Even if you could reduce the size by zipping the data, you would still need to process it later and thus unzip it.
Based on the shape it seems you won’t be able to compress the outputs using an image format.