Bill of Lading

This section describes how to build your custom OCR API to extract data from Bill of Lading using the API Builder. A Bill of Lading is a legal document between a shipper and carrier detailing the type, quantity, and destination of goods being shipped.

Prerequisites

You’ll need at least 20 Bill of Lading images or pdfs to train your OCR.

Define Your Bill of Lading Use Case

Using the Bill of Lading below, we’re going to define the fields we want to extract from it.

Bill of LadingBill of Lading

  • Shipper's name: The full name of the company shipping products
  • Consignee's name: The full name of the company receiving products
  • Ship Date: Represents the date when the shipper sent listed products
  • Due Date: Represents the estimated date of delivery to the consignee
  • Carrier: The name of the company carrying listed products from shipper to consignee

That’s it for this example. Feel free to add any other relevant data that fits your requirement.

Deploy Your API

Once you have defined the list of fields you want to extract from your Bill of Landing, head over to the platform and follow these steps:

  1. Click on the Create a new API button on the right.

  2. Next, fill in the basic information about the API you want to create as seen below.

Set up your APISet up your API

  1. Click on the Next button. The following page allows you to define and add your data model.

Define Your Model

There are two ways to add fields to your data model.

Data ModelData Model

Upload a JSON Config

To add data fields using JSON config upload.

  1. Copy the following JSON into a file.
{
  "problem_type": {
    "classificator": { "features": [], "features_name": [] },
    "selector": {
      "features": [
        {
          "cfg": { "filter": { "alpha": -1, "numeric": 0 } },
          "handwritten": false,
          "name": "shipper_s_name",
          "public_name": "Shipper's name",
          "semantics": "word"
        },
        {
          "cfg": { "filter": { "alpha": -1, "numeric": 0 } },
          "handwritten": false,
          "name": "consignee_s_name",
          "public_name": "Consignee's Name",
          "semantics": "word"
        },
        {
          "cfg": { "filter": { "convention": "US" } },
          "handwritten": false,
          "name": "ship_date",
          "public_name": "Ship Date",
          "semantics": "date"
        },
        {
          "cfg": { "filter": { "convention": "US" } },
          "handwritten": false,
          "name": "due_date",
          "public_name": "Due Date",
          "semantics": "date"
        },
        {
          "cfg": { "filter": { "alpha": -1, "numeric": 0 } },
          "handwritten": false,
          "name": "carrier",
          "public_name": "Carrier",
          "semantics": "word"
        }
      ],
      "features_name": [
        "shipper_s_name",
        "consignee_s_name",
        "ship_date",
        "due_date",
        "carrier"
      ]
    }
  }
}
  1. Click on Upload a JSON config.
  2. The data model will be automatically filled.
  3. Click on Create API at the bottom of the screen.

Document Data Model filledDocument Data Model filled

Manually Add Data

Using the interface, you can manually add each field for the data you are extracting. For this example, here are the different field configurations used:

  • Shipper's name: type String that never contains numeric characters.
  • Consignee's Name: type String that never contains numeric characters.
  • Ship Date: type Date with US format.
  • Due Date: type Date with US format.
  • Carrier: type String that never contains numeric characters.

Once you’re done setting up your data model, click the Create API button at the bottom of the screen.

Document Data Model filledDocument Data Model filled

Train your Bill of Lading OCR

You’re all set! Now it's time to train your Bill of Lading deep learning model in the Training section of our API.

Train your modelTrain your model

  1. Upload one file at a time or a zip bundle of many files.
  2. Click on the field input on the right, and the blue box on the left highlights all the corresponding field candidates in the document.
  3. Next, click on the validate arrow for all the field inputs.
  4. Once you have selected the proper box(es) for each of your fields as displayed on the right-hand side, click on the validate button located at the right-side bottom to send an annotation for the model you have created.
  5. Repeat this process until you have trained 20 documents to create a trained model.

To get more information about the training phase, please refer to the Getting Started tutorial.

 

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