Consider this toy example:
np_array = np.random.randn(2,3,4)
print(np_array.shape, np_array.dtype, np_array.max())
>>((2, 3, 4), dtype('float64'), 2.2915268560525193)
tensor = torch.from_numpy(np_array)
print(tensor.shape, tensor.dtype, tensor.max())
>>torch.Size([2, 3, 4]) torch.float64 tensor(2.3412, dtype=torch.float64)

Everything is as expected. Notice, that default numpy float type is float64, torch is float32. So, you may convert float64 to float32 and have possible overflow (which I am a bit doubt). I would also suggest to carefully review if you may change imagefinal somewhere in the code before converting to tensor.