- Overview
- Document Understanding Process
- Quickstart Tutorials
- Framework Components
- ML Packages
- Pipelines
- Data Manager
- OCR Services
- Document Understanding deployed in Automation Suite
- Document Understanding deployed in AI Center standalone
- Licensing
- References
- UiPath.Abbyy.Activities
- UiPath.AbbyyEmbedded.Activities
- UiPath.DocumentUnderstanding.ML.Activities
- UiPath.DocumentUnderstanding.OCR.LocalServer.Activities
- UiPath.IntelligentOCR.Activities
- UiPath.OCR.Activities
- UiPath.OCR.Contracts
- UiPath.DocumentProcessing.Contracts
- UiPath.OmniPage.Activities
- UiPath.PDF.Activities
About Data Manager
UiPath Document Manager is a lightweight web application that allows users to prepare, review and make corrections to datasets required for Training and Evaluation of Document Understanding Machine Learning models.
Here is the On Premises deployment methods:
- Data Manager in AI Center On Premises. This is Generally Available and it is fully supported for Production scenarios. There is no limitation on the size of datasets that can be imported, with the exception of Auto-retraining which still has the 2000 pages or 2GB limit per import. For all the AI Center deployment methods available for On Premises, please see this page.
Data Manager enables multiple users to perform a variety of operations involved with managing data batches, data preparation and model configuration:
Define and configure the fields to be extracted by an ML model.
Import documents for labeling.
Prelabel documents using a preexisting ML model such as Invoice Extraction or Receipt Extraction provided by UiPath out-of-the-box, or by using a model trained using AI Center.
Label documents.
Export documents in the format expected by the AI Center Training pipelines.
The Data Manager interface contains the following panels:
Displayed at the top of the page in Data Manager.
Enables you to perform multiple operations: navigate in between documents, delete/restore a document, search/filter documents, run AI model predictions, import and export documents.
Here are the options available in the management bar:
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Option |
Icon |
Description |
|---|---|---|
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Navigation |
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Navigate between documents that match the active filter. In between the two arrows, a counter is displayed. It illustrates the number of the current document out of the total number of documents that match the active search/filter. |
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Search or filter documents. Filter is also applied when exporting documents. You can also filter by words from a document or by document names. | |
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Delete / Restore |
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Delete or restore a document. Deleted documents can be found under the deleted filter. |
|
Predict |
|
Run AI model predictions and display the results. After configuring Prelabelling, the button is enabled in the management bar. Click it to prelabel the current document. At the moment, using the Predict option with Public Endpoints prelabels only the first 10 pages of a document. This is a known issue and a fix is in the working. Using the Predict option with ML Skills in AI Center, however, does not impose such a limitation. |
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Open Import data dialog box. | |
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Open Export files dialog box. | |
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Click on the icon to download a Zip file containing the original document. | |
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Configure OCR and Prelabelling settings or access the How to... panel. See below. |
/ 
Download
.jpeg images are downloaded as well.
Document name, type and session name
On the right-hand side of the icon, you can see the name of the currently active document, its type and the session name.
There are three type of documents:
- Training document
- Validation document
- Evaluation document
Training and Validation documents are part of training datasets used by Training Pipelines.
Evaluation documents are ignored by Training Pipelines and are intended to only be used by Evaluation pipelines in AI Center. These documents are the ones that were marked as evaluation by selecting the Make this an evaluation set checkbox in the Import data dialog box.
Settings
The settings button has two available options:
- Settings where you can configure the OCR service or Prelabelling
- How to... which has the purpose of a help menu
OCR
In order to import documents into Data Manager, it is mandatory to configure an OCR service.
The following options are available:
Choosing the OCR engine to be used for importing documents into Data Manager is a critical decision.
It is recommended to use the same OCR to import training data (train time) as it will be used when the model is deployed (run time).
Ideally, you should try a few different ones to see which works best on your documents, and only then decide.
The on-premises options are:
- UiPath OCR container which supports the main Western European languages;
- Microsoft Read container (available as preview from Microsoft) also good language coverage;
- UiPath OCR ML Skills deployed in AI Center on-premises v2020.10 or later.
The cloud-based options are:
- UiPath Document OCR - https://du.uipath.com/ocr;
- Google Cloud Vision OCR which has the best language coverage;
- Google Cloud Vision OCR for Japanese optimal for reading Japanese documents;
- Microsoft Read OCR.
Configuring the OCR requires the OCR service to have a URL. Here are the possible URLs you can use:
- public URLs such as https://du.uipath.com/ocr or third-party URLs from Google Vision OCR or Microsoft Read OCR
- URLs of UiPath Document OCR standalone container provided by UiPath deployed on-premises
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URLs of OCR ML Package deployed as ML Skills which have been made Public in AI Center on-premises v2020.10 or later
Important:If you are running the OCR on the same machine as Data Manager, then do not uselocalhostto refer to the local machine, but rather use the IP address or Domain Name of the local machine.In the case of URLs of OCR deployed as Public ML Skill in AI Center on-premises, use the URL as it appears in the AI Center ML Skill details screen.
The corresponding API Key for the selected OCR engine. For example, for UiPath Document OCR, you need to use the Document Understanding API Key. Mandatory for Data Manager Cloud and Data Manager On-Prem Online. It is not required for Data Manager On-Prem Air-gapped.
Prelabelling
If you already have a model which can extract some of the fields that need labeling, and there are only a few extra fields that require manual labeling, you can save a lot of time by using Data Manager’s Prelabelling feature.
The following options are available:
Prelabelling requires the ML model has a URL. Here are the possible URLs you can use:
- public URLs such as https://du.uipath.com/ie/invoices or https://du.uipath.com/ie/purchase_orders
- see the full list of endpoints here
- URLs of ML Skills which have been made public in AI Center on-premises or in AI Center Cloud
ML Skills in AI Center on-premises deployed in air-gapped environments cannot be used for prelabelling.
localhost to refer to the local machine, but rather use the IP address or Domain Name of the local machine.
In the case of URLs of Public ML Skills in AI Center on-premises, use the URL as it appears in the AI Center ML Skill details screen.
The Document Understanding API Key. Mandatory for Data Manager Cloud and Data Manager On-Prem Online. It is not required for Data Manager On-Prem Air-gapped.
How to...
The How to... option accesses the Data Manager help menu.
Here you can find:
- The Data Manager version
- The Documentation link leading to this documentation page.
- The Labeling Controls section which displays the controls to be used when handling data.
- The Document Shortcuts section which displays the shortcuts used to perform various operations such as navigation and UI scaling.
- The Configuration section which displays details about the instance configuration as performed during installation.
Column fields have the following options:
- Create new column field
- Edit field
- Expand/collapse column field values
For more details on column fields, visit this section.
Regular fields have the following options:
- Create a new regular field
- Edit field
For more details on regular fields, visit this section.
Classification fields have the following options:
- Create a new classification field
- Edit field
For more details on classification fields, visit this section.
Ctrl + mouse scroll.
You can label documents by selecting the word boxes and assigning them to a field by pressing a key. You can also right-click the word box and verify the extracted information.
For more details on how to label documents, visit this page.
When you open a new Data Manager session or when you have an empty filter, certain guidelines are displayed in document view:
Also, loading failures are also displayed in document view:
