U-SQL Advanced Analytics: Introducing Cognitive scenarios for Text and Imaging

Yesterday we introduced you to U-SQL Advanced Analytics and showed how Python can be used with U-SQL. Today, we'll show U-SQL's built-in support for Cognitive scenarios for images and text.

Currently U-SQL Supports these cognitive scenarios:

• Detecting Objects in Images (Tagging)
• Detecting Emotion in Faces in Images
• Detecting Text in Images (OCR)
• Text Key Phrase Extraction
• Text Sentiment Analysis

Over time, we'll add more support and enhance the integration in many ways.

Here's an example of how U-SQL can be used to detect objects in images:

 REFERENCE ASSEMBLY ImageCommon;
REFERENCE ASSEMBLY FaceSdk;
REFERENCE ASSEMBLY ImageEmotion;
REFERENCE ASSEMBLY ImageTagging;
REFERENCE ASSEMBLY ImageOcr;

@imgs =
    EXTRACT FileName string, ImgData byte[]
    FROM @"/images/{FileName}.jpg"
    USING new Cognition.Vision.ImageExtractor();

// Extract the number of objects on each image and tag them 
@objects =
    PROCESS @imgs 
    PRODUCE FileName,
            NumObjects int,
            Tags string
    READONLY FileName
    USING new Cognition.Vision.ImageTagger();

OUTPUT @objects 
    TO "/objects.tsv"
    USING Outputters.Tsv();

In this sample the Cognition.Vision.ImageTagger() processor is used to detect objects and place a text description of them in the Tags column.

Here's an example of how U-SQL can be used to understand text:

 REFERENCE ASSEMBLY [TextCommon];
REFERENCE ASSEMBLY [TextSentiment];
REFERENCE ASSEMBLY [TextKeyPhrase];

@WarAndPeace =
    EXTRACT No int,
            Year string,
            Book string,
            Chapter string,
            Text string
    FROM @"/usqlext/samples/cognition/war_and_peace.csv"
    USING Extractors.Csv();

@sentiment =
    PROCESS @WarAndPeace
    PRODUCE No,
            Year,
            Book,
            Chapter,
            Text,
            Sentiment string,
            Conf double
    READONLY No,
             Year,
             Book,
             Chapter,
             Text
    USING new Cognition.Text.SentimentAnalyzer(true);

 OUTPUT @sentiment 
    TO "/sentiment.tsv"
    USING Outputters.Tsv();

In this sample the Cognition.Text.SentimentAnalyzer() processor is used to detect objects and place a text description of them in the Sentiment column.

To learn more about our support for U-SQL Advanced Analytics and how to enable it in your Data Lake Analytics Accounts, see our Getting Started guide .