Energy performance diagnostic OCR

 

This article walks you through the building process of an OCR API that extracts data from energy performance diagnostics using our deep learning engine. It will work for any kind of EPD template. 

 

 

Prerequisites

  1. You’ll need a free beta account. Sign up and confirm your email to login.
  2. You’ll need at least 20 energy performance diagnostic images or pdfs to train your OCR.

 

 

Define your Energy performance diagnostic (DPE) use case

 

First, we’re going to define what fields we want to extract from your energy performance diagnostic. 

 

 

 

Energy performance diagnostic

 

  • validation date: 30/06/2022

 

  • annual energy consumption : 43430 KW/h

 

  • habitation energy rating : D

 

  • address: 12 Basse Rue, 85200 SAINT MARTIN DE FREIGNEAU

 

  • annual energy price: 3063€

 

 

That’s it for our use case. Feel free to add any other relevant data to fit your requirements.

 

 

Deploy your API

 

Once you have defined the list of fields you want to extract, head over to the platform and press the ‘build a new endpoint’ button.

 

You land now on the setup page. Here is the image you can use for setting up the API, and my setup looks like this:

 

 

Setup your energy performance diagnostic OCR API

 

Once you’re ready, click on the “next step” button. We are going to specify the data types for each of the fields we want our API to extract.


 

To go further, you can download this json config to set up your data model or do it manually.


 

validation date: type Date in the European default format

 

validation date field for energy performance diagnostic

 

 

annual energy consumption: type Number/Integer

 

annual energy consumption field for energy perfomance diagnostic OCR

 

 

Habitation energy rating: type string contains only alpha characters

 

habitation energy rating for energy performance diagnostic OCR

 

address: type string with both numeric and alpha characters.

 

address for energy performance diagnostic OCR

 

annual energy price: Amount type

 

 

annual energy price for energy performance diagnostic

 

 

Once you’re done setting up your data model, press the Data model ready? start training button at the top of the screen.

 

 

Train your custom energy performance diagnostic OCR API.

 

 

 

Deep learning energy performance diagnostic OCR training

 

 

You’re all set! 

 

Now is the time to train your DPE deep learning model in the Training section of our API. 

 

You should get your first model trained in a few hours and you will be soon able to use your custom OCR API for parsing energy performance diagnostic in your application.

 

To get more information about the training phase, please refer to the getting started tutorial. If you have any questions regarding your use case, feel free to reach out!