DocumentLab-x64 1.3.0

Getting started

You can write scripts in the query language or use the C# API. The C# fluent interface is easier to get started quickly. The raw text scripting interface allows more versatility and configurability in a production context.

Definitions

• Pattern: A description of how information is presented in a document as well as which data to capture
  • e.g: Text(Total amount) Right [Amount]
• Table: A description of which table column labels to match in a document and which text types are represented in each column
  • e.g: Table 'ItemNo': [Number(Item number)] 'Description': [Text(Description)] 'Price': [Amount(...
• Query: A named set of patterns prioritized first to last
  • e.g: IncoiceNumber: *pattern 1*; *pattern 2*; ... *pattern n*;
• Script: A collection of queries to execute in one go. Output properties will have the query name

From here...

• Configure C# build settings
• Query language documentation
  • C# Example: Executing scripts
• Fluent C# interface documentation

Quick examples

Below are a few select examples with comments on how DocumentLab can be used.

C# Fluent Query Example

using (var dl = new Document((Bitmap)Image.FromFile("pathToSomeImage.png")))
{
  // Here we ask DocumentLab to specifically find a date value for the specified possible labels
  string dueDate = dl.Query().FindValueForLabel(TextType.Date, "Due date", "Payment date");

  // Here we ask DocumentLab to specifically find a date value for the specified label in a specific direction 
  string customerNumber = dl.Query().GetValueForLabel(Direction.Right, "Customer number");

  // We can build patterns using predicates, directions and capture operations that return the value matched in the document
  // Patterns allow us to recognize and capture data by contextual information, i.e., how we'd read for example receiver information from an invoice
  string receiverName = dl
    .Query()
    .Match("PostCode") // Text classification using contextual data files can be referenced by string
    .Up()
    .Match("Town")
    .Up()
    .Match("City")
    .Up()
    .Capture(TextType.Text); // All text type operations can also use the statically defined text type enum
} 

Script example

• Your document has a label "Customer number:" and a value to the right of it
  • Query: CustomerNumber: Text(Customer number) Right [Text];
  • Match text labels with implicit starts with and Levensthein distance 2 comparison
• Your document has a label "Invoice date" and a date below it
  • Query: InvoiceDate: Text(Invoice date) Down [Date];
  • You can capture a variety of text types. Even if the document contains additional text at the capture you'll only get back a standardized ISO date.
• Want to capture invoice receiver info in one query?
  • Query: Receiver: 'Name': [Text] Down 'Address': [StreetAddress] Down 'City': [Town] Down 'PostalCode': [PostalCode];
  • Json output will name properties according to the query predicate naming parameters
• You want to capture all amounts in a document?
  • Query: AllAmounts: Any [Amount];
  • When we use any, results are returned in a json array