azure-ai-vision-imageanalysis-java

# 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>1.1.0-beta.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" ## Diff History - **v00.33.0**: Ingested from skills-main --- ## Why This Skill Exists Build image analysis applications with Azure AI Vision SDK for Java. <!-- SR_40: auto-generated from frontmatter `purpose`/`description` (OPP-Phase3). Expand with domain-specific rationale. --> ## When to Use Use this skill when implementing image captioning, <!-- SR_40: auto-generated from frontmatter `when`/`description` (OPP-Phase3). --> ## What If Fails - condition: Código não disponível para análise <!-- SR_40: auto-generated from frontmatter `what_if_fails` (OPP-Phase3). -->