The treatment of the image datasets in `WideDeepDataset` replicates that of `Pytorch`. In particular this source code:
if isinstance(pic, np.ndarray):
handle numpy array
if pic.ndim == 2:
pic = pic[:, :, None]
In addition, I have added the possibility of using each of the model components in isolation and independently. This is, one could now use the `wide`, `deepdense` (either `DeepDense` or `DeepDenseResnet`), `deeptext` and `deepimage` independently.