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.
Add this skill
npx mdskills install sickn33/azure-ai-vision-imageanalysis-javaComprehensive SDK reference with clear code examples for all major image analysis features
Build image analysis applications using the Azure AI Vision Image Analysis SDK for Java.
com.azure
azure-ai-vision-imageanalysis
1.1.0-beta.1
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();
import com.azure.ai.vision.imageanalysis.ImageAnalysisAsyncClient;
ImageAnalysisAsyncClient asyncClient = new ImageAnalysisClientBuilder()
.endpoint(endpoint)
.credential(new KeyCredential(key))
.buildAsyncClient();
import com.azure.identity.DefaultAzureCredentialBuilder;
ImageAnalysisClient client = new ImageAnalysisClientBuilder()
.endpoint(endpoint)
.credential(new DefaultAzureCredentialBuilder().build())
.buildClient();
| 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 |
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());
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());
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());
}
}
}
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());
}
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());
}
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());
}
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());
}
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());
}
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());
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")
);
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());
}
VISION_ENDPOINT=https://.cognitiveservices.azure.com/
VISION_KEY=
Caption and Dense Captions require GPU-supported regions. Check supported regions before deployment.
Install via CLI
npx mdskills install sickn33/azure-ai-vision-imageanalysis-javaAzure AI Vision Imageanalysis Java is a free, open-source AI agent skill. 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.
Install Azure AI Vision Imageanalysis Java with a single command:
npx mdskills install sickn33/azure-ai-vision-imageanalysis-javaThis downloads the skill files into your project and your AI agent picks them up automatically.
Azure AI Vision Imageanalysis Java works with Claude Code, Claude Desktop, Cursor, Vscode Copilot, Windsurf, Continue Dev, Codex, Gemini Cli, Amp, Roo Code, Goose, Opencode, Trae, Qodo, Command Code. Skills use the open SKILL.md format which is compatible with any AI coding agent that reads markdown instructions.