
Missing inference/preprocessing transforms: The user is forced to define the necessary transforms prior using the model. The inference transforms are usually linked to the training process and dataset used to estimate the weights. Any minor discrepancies in these transforms (such as interpolation value, resize/crop sizes etc) can lead to major reductions in accuracy or unusable models.
Lack of meta-data: Critical pieces of information in relation to the weights are unavailable to the users. For example, one needs to look into external sources and the documentation to find things like the category labels, the training recipe, the accuracy metrics etc.

The new API addresses the above limitations and reduces the amount of boilerplate code needed for standard tasks.
Overview of the prototype API
Let’s see how we can achieve exactly the same results as above using the new API:
```Python
from PIL import Image