I’ve been working with TensorFlow’s pretrained models extensively and have noticed a recurring issue in many tutorials. Often, these tutorials fine-tune the model or freeze it and use it as a feature extractor, appending different output layers based on the task at hand. However, I’ve noticed that many of these tutorials seem to skip the step for preprocessing the data, even though each model requires different input or the data are only scaled between 0-1.