Certificate of Origin

This section describes how to build your custom OCR API to extract data from Certificate of Origin using the API Builder. A Certificate of Origin (CO) is an important international trade document that certifies that goods in a particular export shipment are wholly obtained, produced, manufactured, or processed in a particular country.


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

Define Your Certificate of Origin Use Case

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

  • Agent Name: The full name of the agent
  • Name and Address of shipper: The full name and address of the shipper
  • Name and Address of consignee: The full name and address of the consignee
  • Package Weight: The total package weight
  • Package Description: The package description

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 Certificate of Origin, 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
    Set up your API

  3. 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.

Document data 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": "agent_name",
          "public_name": "Agent Name",
          "semantics": "word"
          "cfg": { "filter": { "alpha": -1, "numeric": -1 } },
          "handwritten": false,
          "name": "name_and_address_of_shipper",
          "public_name": "Name and Address of shipper",
          "semantics": "word"
          "cfg": { "filter": { "alpha": -1, "numeric": -1 } },
          "handwritten": false,
          "name": "name_and_address_of_consignee",
          "public_name": "Name and Address of consignee",
          "semantics": "word"
          "cfg": { "filter": { "is_integer": -1 } },
          "handwritten": false,
          "name": "package_weight",
          "public_name": "Package weight",
          "semantics": "amount"
          "cfg": { "filter": { "alpha": -1, "numeric": -1 } },
          "handwritten": false,
          "name": "package_description",
          "public_name": "Package Description",
          "semantics": "word"
      "features_name": [
  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 filled

Manually Add Data

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

  • Agent name: type String that never contains numeric characters.
  • Name and Address of shipper: type String without specifications.
  • Name and Address of consignee: type String without specifications.
  • Package weight: type Number without specifications.
  • Package Description: type String without specifications.

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

Document data model filled

Train Your Certificate of Origin OCR

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

Train 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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