Train Ticket

This section describes how to build your custom OCR API to extract data from Train Tickets using the API Builder. A Train Ticket is a ticket issued by a railway operator that enables the bearer to travel on the operator's network or a partner's network

Prerequisites

You’ll need at least 20 train ticket images or PDFs to train your OCR.

Define your Train Ticket Use Case

Using the Train Ticket below, we’re going to define the fields we want to extract from it.

• Passenger name: The full name of the passenger traveling (Jane Martin)
• Reservation number: The reservation number of your train ticket (925D90)
• Departure Date: The date of departure
• Departure station code: The 3 letters identification code for your departure station (WAS)
• Arrival station code: The 3 letters identification code for your arrival station (NYP)
• Departure Time: The train departure time from the departure station (01:50 PM)

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 Train Ticket, 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.

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.

• Upload a JSON config file
• Manually add data

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": "passenger_name",
          "public_name": "Passenger name",
          "semantics": "word"
        },
        {
          "cfg": { "filter": { "alpha": -1, "numeric": -1 } },
          "handwritten": false,
          "name": "reservation_number",
          "public_name": "Reservation number",
          "semantics": "word"
        },
        {
          "cfg": { "filter": { "convention": "US" } },
          "handwritten": false,
          "name": "departure_date",
          "public_name": "Departure Date",
          "semantics": "date"
        },
        {
          "cfg": { "filter": { "alpha": -1, "numeric": 0 } },
          "handwritten": false,
          "name": "departure_station_code",
          "public_name": "Departure Station Code",
          "semantics": "word"
        },
        {
          "cfg": { "filter": { "alpha": -1, "numeric": 0 } },
          "handwritten": false,
          "name": "arrival_station_code",
          "public_name": "Arrival Station Code",
          "semantics": "word"
        },
        {
          "cfg": { "filter": { "alpha": -1, "numeric": -1 } },
          "handwritten": false,
          "name": "departure_time",
          "public_name": "Departure Time",
          "semantics": "word"
        }
      ],
      "features_name": [
        "passenger_name",
        "reservation_number",
        "departure_date",
        "departure_station_code",
        "arrival_station_code",
        "departure_time"
      ]
    }
  }
}

2. Click on Upload a JSON config.
3. The data model will be automatically filled.
4. Click on Create API at the bottom of the screen.

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:

• Passenger name: type String that never contains numeric characters.
• Reservation number: type String without specifications.
• Departure Date: Date with US format.
• Departure Station Code: type String that never contains numeric characters.
• Arrival Station Code: type String that never contains numeric characters.
• Departure Time: type String without specifications.

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

Train your Train Ticket OCR

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

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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