Bundle pre-processing steps to Tensorflow SavedModel

Question

I have built an Image Classifier model using Inception V3 and I have saved the model in "SavedModel" format to deploy it to production. I am wondering how I can bundle the pre-processing steps to the final model so that the model ingest data in its natural form.

The pre-processing steps that I have are:

- resizing the image to target_size of 299, 299 using keras load_model
- change the image to numpy array
- expand dimensions
- pre_process input using inception_v3 import preprocess_input call

Answer 1

When a model is deployed, as per my understanding what actually is deployed is the python code for inference utilising the model. In this python code you can write code for all your preprocessing using openCV or any other python libraries and pass the image as an argument to this python code.

eg inferenceFile.py imageToInfer.png

An out of the box thought would be to write a different deep learning model to which as input your non-preprocessed image and output the preprocessed image you feed to the model, Not sure if this could be achievable.