Packing List OCR

 

This article walks you through the building process of an OCR API that extracts data from Packing List forms using our deep learning engine. 

 

 

Prerequisites

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

 

 

Define your Packing List use case

 

First, we’re going to define what fields we want to extract from your Packing List. 

 

 

Packing List OCR API

 

 

  • Exporter: The name of the exporter

 

  • Exporter address: The exporter's address 

 

  • Consignee: The consignee's name

 

  • Consignee Address: The consignee's address where the package must be delivered

 

  • Consignee Phone Number: The consignee's phone number

 

  • Method of dispatch: how the package is carried (sea)

 

  • Export Invoice Date: Issue date of the export invoice

 

  • Export Invoice Number: Identification number of the export invoice

 

  • Country of Origin: where the package comes from 

 

  • Country of Final Destination: the package final destination 

 

  • Total Weight: total weight of package carried 

 

 

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:

 

 

Set up your Packing List 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.


 

Exporter Name: type String that never contains numeric characters.

 

Exporter Name field for Packing List  OCR

 

Exporter Address: type String without specifications.  

 

Exporter address field for Packing List  OCR

 

Consignee Name: type String that never contains alpha characters. 

 

Consignee name field for Packing List OCR

 

Consignee Address: type String without specifications. 

 

Consignee address for Packing List OCR

 

Consignee phone number: type Phone Number. 

 

Consignee phone number field for Packing List OCR

 

Method of Dispatch: type String that never contains alpha characters. 

 

Method of Dispatch field for Packing List OCR

 

Export Invoice Date: type Date with US format. 

 

Export invoice date field for Packing List OCR

 

Export Invoice Number: type Number without specifications

 

Export invoice number field for Packing List OCR

 

Country of Origin: type String that never contains numeric characters. 

 

Country of origin field for Packing List OCR

 

Country of Final Destination: type String that never contains numeric characters. 

 

Country of final Destination field for Packing List OCR

 

Total Weight: type Number without specifications. 

 

Total Weight field for Packing List OCR

 

 

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 Packing List OCR

 

 

Deep learning Packing List  OCR API

 

 

You’re all set! 

 

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

 

In a few hours (minutes if you're fast), you’ll get your first model trained and will be able to use your custom OCR API for parsing Packing List 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!