Nutrition Facts label OCR
This article walks you through the building process of an OCR API that extracts data from Nutrition Facts labels using our deep learning engine. It will work for any food brand or label template.
- You’ll need a free account. Sign up and confirm your email to login.
- You’ll need at least 20 nutrition facts labels or pdfs to train your OCR.
Define your Nutrition fact label use case
First, we’re going to define what fields we want to extract from your Nutrition fact label.
- Serving size: 170 gram
- total fat gram: 2 gram
- total fat daily value : 3%
- calories per serving: 150
That’s it for our use case. Remember this is an example 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 ‘Create a new API’ 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:
Once you’re ready, click on the “next” 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.
Serving size: type Integer
Total fat gram: type Number
Total fat daily value: type String that never contains alpha characters
Calories per serving: type Integer
Once you’re done setting up your data model, press the Start training your model button at the bottom of the screen.
Train your Nutrition facts labels OCR
You’re all set!
Now is the time to train your nutrition facts to train deep learning model in the Training section of our API.
After 20 annotated data, your first model is trained and you're now able to use your custom OCR API for parsing nutrition facts labels 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 using our chat!