Bus Ticket

This section describes how to build your custom OCR API to extract data from Bus Ticket using the API Builder. A Bus Ticket is a commercial document showing that the holder is entitled to ride on public transportation.

Prerequisites

You’ll need at least 20 Bus Ticket images or pdfs to train your OCR.

Define Your Bus Ticket Use Case

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

Bus TicketBus Ticket

  • Bus Company: The name of the company that sold the ticket (megabus.com)
  • Reservation Number: The reservation number that will be asked when you board the bus (67-2722-033018-M10R-1415-LAS-ANA)
  • Date: The date of departure (March 30, 2018)
  • Departure city: The city of departure for your travel by bus (Las Vegas)
  • Arrival city: The city of destination (Anaheim)
  • Departure Time: The bus departure time from the departure city (2:15 PM)
  • Price: The total amount paid for the bus ticket ($41,75)

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 Bus 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
    Set up your APISet 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.

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": "bus_company",
          "public_name": "Bus company",
          "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": "date",
          "public_name": "Date",
          "semantics": "date"
        },
        {
          "cfg": { "filter": { "alpha": -1, "numeric": 0 } },
          "handwritten": false,
          "name": "departure_city",
          "public_name": "Departure city",
          "semantics": "word"
        },
        {
          "cfg": { "filter": { "alpha": -1, "numeric": 0 } },
          "handwritten": false,
          "name": "arrival_city",
          "public_name": "Arrival city",
          "semantics": "word"
        },
        {
          "cfg": { "filter": { "alpha": -1, "numeric": -1 } },
          "handwritten": false,
          "name": "departure_time",
          "public_name": "Departure Time",
          "semantics": "word"
        },
        {
          "cfg": { "filter": { "is_integer": -1 } },
          "handwritten": false,
          "name": "price",
          "public_name": "Price",
          "semantics": "amount"
        }
      ],
      "features_name": [
        "bus_company",
        "reservation_number",
        "date",
        "departure_city",
        "arrival_city",
        "departure_time",
        "price"
      ]
    }
  }
}
  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:

  • Bus company: type String that never contains numeric characters.
  • Reservation number: type String without specifications.
  • Date: type String without specifications.
  • Departure city: type String that never contains numeric characters.
  • Arrival city: type String that never contains numeric characters.
  • Departure Time: type String without specifications.
  • Price: type Number 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 filledDocument Data Model filled

Train Your Bus Ticket OCR

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

  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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