- Overview
- Document Understanding Process
- Quickstart tutorials
- Framework components
- ML packages
- Overview
- Document Understanding - ML package
- DocumentClassifier - ML package
- ML packages with OCR capabilities
- 1040 - ML package
- 1040 Schedule C - ML package
- 1040 Schedule D - ML package
- 1040 Schedule E - ML package
- 4506T - ML package
- 990 - ML Package - Preview
- ACORD125 - ML package
- ACORD126 - ML package
- ACORD131 - ML package
- ACORD140 - ML package
- ACORD25 - ML package
- Bank Statements - ML package
- Bills Of Lading - ML package
- Certificate of Incorporation - ML package
- Certificate of Origin - ML package
- Checks - ML package
- Children Product Certificate - ML package
- CMS 1500 - ML package
- EU Declaration of Conformity - ML package
- Financial Statements - ML package
- FM1003 - ML package
- I9 - ML package
- ID Cards - ML package
- Invoices - ML package
- Invoices Australia - ML package
- Invoices China - ML package
- Invoices India - ML package
- Invoices Japan - ML package
- Invoices Shipping - ML package
- Packing Lists - ML package
- Passports - ML package
- Payslips - ML package
- Purchase Orders - ML package
- Receipts - ML Package
- Remittance Advices - ML package
- UB04 - ML package
- Utility Bills - ML package
- Vehicle Titles - ML package
- W2 - ML package
- W9 - ML package
- Other Out-of-the-box ML Packages
- Public Endpoints
- Hardware requirements
- Pipelines
- Document Manager
- OCR services
- Deep Learning
- Document Understanding deployed in Automation Suite
- Document Understanding deployed in AI Center standalone
- Licensing
- Activities
- UiPath.Abbyy.Activities
- UiPath.AbbyyEmbedded.Activities
- UiPath.DocumentProcessing.Contracts
- UiPath.DocumentUnderstanding.ML.Activities
- UiPath.DocumentUnderstanding.OCR.LocalServer.Activities
- UiPath.IntelligentOCR.Activities
- UiPath.OCR.Activities
- UiPath.OCR.Contracts
- UiPath.OmniPage.Activities
- UiPath.PDF.Activities
Form Extractor
The Form Extractor is an extraction approach best suited for use cases in which non-variable format documents need to be processed, with data extracted from them. In other words, if your documents have little to no variation in the document layouts, then the Form Extractor is a good choice.
The Form Extractor relies on templates defined up-front, at the design stage. A complex set of rules applies the configured templates to incoming documents that are to be processed, thus identifying and reporting the expected information.
You can use this activity for handwriting recognition and handwritten data extraction or signature detection. These features make Form Extractor a very good fit for processing forms that are either printed or handwritten or if you need to check wheter the form is signed or not.
The activity comes with a configuration wizard that assists you in defining the templates for the document types and fields you want to target for data extraction.
The activity supports both simple field and table field extraction.
It is recommended to look into other extraction methods, in case:
- there are many layouts that need to be handled
- documents are not only skewed, rotated, or come in different sizes, but also manifest "warping" (curving in certain areas).
Note:
For fixed form extraction, to evaluate if layouts of two files are the same, try overlapping them in a tool, with some transparency, to see if all non-variable content overlaps (after de-rotation, de-skewing and bringing the two images to the same scale).
If you notice variability (non-variable content appears more to the left / right / top / bottom for certain areas of the document), then the layouts are not considered the same.
The Form Extractor allows you to define multiple templates for the same document type, and, at run-time, it:
- identifies the best matching template for the incoming document and document type
- applies the template matching algorithm, based on page-level anchors, to each page from where data needs to be extracted (missing or repeating pages are not supported)
- applies all field-level anchor settings to each page, to capture values associated with any potential matches
- reports the identified information from the target value areas.
It also supports fine-tuning of checkbox / boolean field processing, by allowing the configuration of "Synonyms for Yes" or "Synonyms for No" value, according to your use case.
This extractor does not have learning (training) capabilities and requires configuration.
You need to use your Automation Cloud Document Understanding API Key, or host your own instance of the Form Extractor in AI Center on-premises, to use this extractor.
Anchors functionality is now available in the Template Editor, allowing you to define anchor-based rules for data extraction, for simple fields from a fixed document type. Here you can find more information about using and configuring anchors.
