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azure-ai-vision-imageanalysis-java

Build image analysis applications with Azure AI Vision SDK for Java. Use when implementing image captioning, OCR text extraction, object detection, tagging, or smart cropping.

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Repository
administrakt0r/ai-agents-safe-coding-skills
Letzte Quellaktivität
4. September 2026 um 08:56
Erkannte Sprache von SKILL.md
Englisch
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SKILL.md
Quellanweisungen · Schreibgeschützte Vorschau
name
azure-ai-vision-imageanalysis-java
description
Build image analysis applications with Azure AI Vision SDK for Java. Use when implementing image captioning, OCR text extraction, object detection, tagging, or smart cropping.
risk
unknown
source
community
date_added
2026-02-27
# Azure AI Vision Image Analysis SDK for Java Build image analysis applications using the Azure AI Vision Image Analysis SDK for Java. ## Installation ```xml <dependency> <groupId>com.azure</groupId> <artifactId>azure-ai-vision-imageanalysis</artifactId> <version>1.0.1</version> </dependency> ``` ## Client Creation ### With API Key ```java import com.azure.ai.vision.imageanalysis.ImageAnalysisClient; import com.azure.ai.vision.imageanalysis.ImageAnalysisClientBuilder; import com.azure.core.credential.KeyCredential; String endpoint = System.getenv("VISION_ENDPOINT"); String key = System.getenv("VISION_KEY"); ImageAnalysisClient client = new ImageAnalysisClientBuilder() .endpoint(endpoint) .credential(new KeyCredential(key)) .buildClient(); ``` ### Async Client ```java import com.azure.ai.vision.imageanalysis.ImageAnalysisAsyncClient; ImageAnalysisAsyncClient asyncClient = new ImageAnalysisClientBuilder() .endpoint(endpoint) .credential(new KeyCredential(key)) .buildAsyncClient(); ``` ### With DefaultAzureCredential ```java import com.azure.identity.DefaultAzureCredentialBuilder; ImageAnalysisClient client = new ImageAnalysisClientBuilder() .endpoint(endpoint) .credential(new DefaultAzureCredentialBuilder().build()) .buildClient(); ``` ## Visual Features | Feature | Description | |---------|-------------| | `CAPTION` | Generate human-readable image description | | `DENSE_CAPTIONS` | Captions for up to 10 regions | | `READ` | OCR - Extract text from images | | `TAGS` | Content tags for objects, scenes, actions | | `OBJECTS` | Detect objects with bounding boxes | | `SMART_CROPS` | Smart thumbnail regions | | `PEOPLE` | Detect people with locations | ## Core Patterns ### Generate Caption ```java import com.azure.ai.vision.imageanalysis.models.*; import com.azure.core.util.BinaryData; import java.io.File; import java.util.Arrays; // From file BinaryData imageData = BinaryData.fromFile(new File("image.jpg").toPath()); ImageAnalysisResult result = client.analyze( imageData, Arrays.asList(VisualFeatures.CAPTION), new ImageAnalysisOptions().setGenderNeutralCaption(true)); System.out.printf("Caption: \"%s\" (confidence: %.4f)%n", result.getCaption().getText(), result.getCaption().getConfidence()); ``` ### Generate Caption from URL ```java ImageAnalysisResult result = client.analyzeFromUrl( "https://example.com/image.jpg", Arrays.asList(VisualFeatures.CAPTION), new ImageAnalysisOptions().setGenderNeutralCaption(true)); System.out.printf("Caption: \"%s\"%n", result.getCaption().getText()); ``` ### Extract Text (OCR) ```java ImageAnalysisResult result = client.analyze( BinaryData.fromFile(new File("document.jpg").toPath()), Arrays.asList(VisualFeatures.READ), null); for (DetectedTextBlock block : result.getRead().getBlocks()) { for (DetectedTextLine line : block.getLines()) { System.out.printf("Line: '%s'%n", line.getText()); System.out.printf(" Bounding polygon: %s%n", line.getBoundingPolygon()); for (DetectedTextWord word : line.getWords()) { System.out.printf(" Word: '%s' (confidence: %.4f)%n", word.getText(), word.getConfidence()); } } } ``` ### Detect Objects ```java ImageAnalysisResult result = client.analyzeFromUrl( imageUrl, Arrays.asList(VisualFeatures.OBJECTS), null); for (DetectedObject obj : result.getObjects()) { System.out.printf("Object: %s (confidence: %.4f)%n", obj.getTags().get(0).getName(), obj.getTags().get(0).getConfidence()); ImageBoundingBox box = obj.getBoundingBox(); System.out.printf(" Location: x=%d, y=%d, w=%d, h=%d%n", box.getX(), box.getY(), box.getWidth(), box.getHeight()); } ``` ### Get Tags ```java ImageAnalysisResult result = client.analyzeFromUrl( imageUrl, Arrays.asList(VisualFeatures.TAGS), null); for (DetectedTag tag : result.getTags()) { System.out.printf("Tag: %s (confidence: %.4f)%n", tag.getName(), tag.getConfidence()); } ``` ### Detect People ```java ImageAnalysisResult result = client.analyzeFromUrl( imageUrl, Arrays.asList(VisualFeatures.PEOPLE), null); for (DetectedPerson person : result.getPeople()) { ImageBoundingBox box = person.getBoundingBox(); System.out.printf("Person at x=%d, y=%d (confidence: %.4f)%n", box.getX(), box.getY(), person.getConfidence()); } ``` ### Smart Cropping ```java ImageAnalysisResult result = client.analyzeFromUrl( imageUrl, Arrays.asList(VisualFeatures.SMART_CROPS), new ImageAnalysisOptions().setSmartCropsAspectRatios(Arrays.asList(1.0, 1.5))); for (CropRegion crop : result.getSmartCrops()) { System.out.printf("Crop region: aspect=%.2f, x=%d, y=%d, w=%d, h=%d%n", crop.getAspectRatio(), crop.getBoundingBox().getX(), crop.getBoundingBox().getY(), crop.getBoundingBox().getWidth(), crop.getBoundingBox().getHeight()); } ``` ### Dense Captions ```java ImageAnalysisResult result = client.analyzeFromUrl( imageUrl, Arrays.asList(VisualFeatures.DENSE_CAPTIONS), new ImageAnalysisOptions().setGenderNeutralCaption(true)); for (DenseCaption caption : result.getDenseCaptions()) { System.out.printf("Caption: \"%s\" (confidence: %.4f)%n", caption.getText(), caption.getConfidence()); System.out.printf(" Region: x=%d, y=%d, w=%d, h=%d%n", caption.getBoundingBox().getX(), caption.getBoundingBox().getY(), caption.getBoundingBox().getWidth(), caption.getBoundingBox().getHeight()); } ``` ### Multiple Features ```java ImageAnalysisResult result = client.analyzeFromUrl( imageUrl, Arrays.asList( VisualFeatures.CAPTION, VisualFeatures.TAGS, VisualFeatures.OBJECTS, VisualFeatures.READ), new ImageAnalysisOptions() .setGenderNeutralCaption(true) .setLanguage("en")); // Access all results System.out.println("Caption: " + result.getCaption().getText()); System.out.println("Tags: " + result.getTags().size()); System.out.println("Objects: " + result.getObjects().size()); System.out.println("Text blocks: " + result.getRead().getBlocks().size()); ``` ### Async Analysis ```java asyncClient.analyzeFromUrl( imageUrl, Arrays.asList(VisualFeatures.CAPTION), null) .subscribe( result -> System.out.println("Caption: " + result.getCaption().getText()), error -> System.err.println("Error: " + error.getMessage()), () -> System.out.println("Complete") ); ``` ## Error Handling ```java import com.azure.core.exception.HttpResponseException; try { client.analyzeFromUrl(imageUrl, Arrays.asList(VisualFeatures.CAPTION), null); } catch (HttpResponseException e) { System.out.println("Status: " + e.getResponse().getStatusCode()); System.out.println("Error: " + e.getMessage()); } ``` ## Environment Variables ```bash VISION_ENDPOINT=https://<resource>.cognitiveservices.azure.com/ VISION_KEY=<your-api-key> ``` ## Image Requirements - Formats: JPEG, PNG, GIF, BMP, WEBP, ICO, TIFF, MPO - Size: < 20 MB - Dimensions: 50x50 to 16000x16000 pixels ## Regional Availability Caption and Dense Captions require GPU-supported regions. Check [supported regions](https://learn.microsoft.com/azure/ai-services/computer-vision/concept-describe-images-40) before deployment. ## Trigger Phrases - "image analysis Java" - "Azure Vision SDK" - "image captioning" - "OCR image text extraction" - "object detection image" - "smart crop thumbnail" - "detect people image" ## When to Use This skill is applicable to execute the workflow or actions described in the overview.
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