Purpose: Predict type of expenses from imaged receipt, using Microsoft's OCR and AzureML.
Accompanying post.
-
ORC.py contains code for converting unstructured image data into structured text data, which is then used to build a predictive model. The code is then adapted so that it can be hosted within Azure ML's Python Module and make the modelling process self-contained within Azure ML Studio.
-
This model is trained on ~1100 imaged American receipts for categories: Dining, snack, clothes, feul, groceries, entertainment
This is a single page Xamarin Forms based cross platform mobile application which takes an image and calls the partner(Agitare) api to store it in Azure blob storage. Once we get a stored URL to the image, we then pass this URL to Machine learning web service end point to obtain probability scores of different classification groups. The results are shown in a CardViewCell control in a Xamarin forms page. The app uses MVVM pattern to implement this functionality.