Document Understanding 活动

UiPath™.IntelligentOCR.Activities 包含使用完整、开放、可扩展的方法启用文档处理流程的基础架构。

如果您使用的是暂停工作流的“等待”类型活动，并且您正在使用DataTable变量，则DataTable变量必须可序列化。例如，如果使用new System.Data.DataTable初始化DataTable变量，则它将变为不可序列化，这可能导致项目执行失败。为防止出现这种情况，您可以将DataTable变量的默认值留空，或为DataTable变量分配一个名称，例如： new System.Data.DataTable("MyTable") 。

下表显示了已删除的包版本，以及建议使用的版本。

Table 1. The removed versions and their recommended replacements

Updating the UiPath.IntelligentOCR.Activities also requires an update for the UiPath.UIAutomation.Activities package and for UiPath.OCR.Activities package if included in the project.

UiPath.IntelligentOCR.Activities and UiPath.DocumentUnderstanding.Activities should not be used together in the same project. The UiPath.IntelligentOCR.Activities package should be used for Windows (or Legacy) workflows, while the UiPath.DocumentUnderstanding.Activities package should be used for Cross-platform workflows.

“智能 OCR”活动包可以支持以下任何文件类型：.png, .gif, .jpe, .jpg, .jpeg, .tiff, .tif, .bmp 和 .pdf。

从版本 4.10.0 开始， 此活动包已经过验证，可在 C# 项目中使用。

本节显示 Intelligent.OCR 包的多种功能。

You can achieve this using the Digitize Document activity. This retrieves the text from any PDF or image, using, only if necessary, the OCR engine of your choice.

在逐个处理文档时，它们会经历数字化流程。 非数字（扫描）文档的区别在于，您需要应用所选的 OCR 引擎。 此步骤的输出是文档对象模型和包含所有文档文本的字符串变量，并将传递到后续步骤。

You can achieve this using the Classify Document activity. This allows identifying what type of document a file is by using any classification algorithm.

数字化后，文档将进行分类。 如果您在同一个项目中使用多种文档类型，则要正确提取数据，您需要知道正在使用的文档类型。 重要的是，您可以在同一作用域中使用多个分类器，可以配置分类器，并稍后在框架中训练它们。 分类结果有助于在提取中应用正确的策略。

以下列表显示了可用的分类器：

You can achieve this using the Present Classification Station attended activity, which presents a document processing specific user interface for validating and correcting automatic classification outputs.

特别是对于涉及文件拆分的用例，强烈建议使用人工分类验证步骤，以确保用于数据提取的下游处理正常工作。

An alternative to the attended activity is available through the usage of Long-Running Workflows, which are designed to optimally enable human-robot collaboration. The Create Document Classification Action and the Wait For Document Classification Action And Resume activities enable this scenario.

You can achieve this using the Train Classifiers Scope activity. This empowers the closing of the feedback loop to any classification algorithm capable of learning. Drag and drop your classifier trainers within this Scope activity and enable them using the Configure Classifiers wizard to ensure that the information validated by humans through the Classification Station or Validation Station is used by your classifiers to improve their own performance.

分类与所使用的分类器一样有效。 如果文档未正确分类，则表示活动分类器未知该文档。 该框架提供了训练分类器的机会，以提高对文档类的识别。

以下是可用的分类器训练器列表：

You can achieve this using the Data Extraction Scope activity. This allows the usage of any data extraction algorithm for identifying different fields in a classified document.

提取只是从给定的文档类型中获取您感兴趣的数据。 例如，如果要使用字符串操作来从 5 页文档中提取特定数据，则非常麻烦。 在此框架中，您可以在同一数据提取作用域内针对不同的文档结构使用不同的提取程序。 提取结果将进一步传递以进行验证。

以下是可用提取程序的列表：

You can achieve this using the Present Validation Station attended activity, which presents a document processing specific user interface for data validation and correction.

You can achieve this using the Train Extractors Scope activity. This empowers the closing of the feedback loop to any data extraction algorithm capable of learning. Drag and drop your extractor trainers within this Scope activity and enable them using the Configure Extractors wizard to ensure that the information validated by humans through the Validation Station is used by your extractors to improve their own performance.

与所使用的提取器一样，提取效率很高。 如果未正确提取字段值，则表示活动的提取程序不知道这些字段值。 该框架提供了培训提取程序的机会，以提高对字段值的识别。

The Machine Learning Extractor Trainer closes the feedback loop for ML-based data extraction, by collecting the data required for retraining a Machine Learning model hosted in AI Center. This activity is the companion of the Machine Learning Extractor activity.

You can achieve this using the Export Extraction Results activity. This allows you to export the complex structure of extracted data to a simple DataSet (collection of DataTables).

获得经过验证的信息后，您可以按原样使用它，也可以将其保存为数据表格式，该格式可以很容易地转换为 Excel 文件。

The UiPath.IntelligentOCR.Activities package is compatible with any custom classification or data extraction activity that is built based on the public UiPath.DocumentProcessing.Contracts package. It offers full flexibility to build your own algorithm specific to your use case, as well as integrating it with any third-party solution for document classification and data extraction.

以下版本的包已从官方订阅源中删除。 如果您有任何问题，请联系我们的支持团队。