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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Build image analysis applications using the Azure AI Vision Image Analysis SDK for Java.
<dependency>
<groupId>com.azure</groupId>
<artifactId>azure-ai-vision-imageanalysis</artifactId>
<version>1.1.0-beta.1</version>
</dependency>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().getValues()) {
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().getValues()) {
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().getValues()) {
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().getValues()) {
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().getValues()) {
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().getValues().size());
System.out.println("Objects: " + result.getObjects().getValues().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://<resource>.cognitiveservices.azure.com/
VISION_KEY=<your-api-key>Caption and Dense Captions require GPU-supported regions. Check supported regions before deployment.
This skill is applicable to execute the workflow or actions described in the overview.
Feature result wrappers may be absent when not requested; null-check each requested result and check a detected object has tags before indexing get(0). Verify model/feature availability and signatures for the pinned SDK. Scores/captions/OCR are uncertain model outputs, not identity or factual proof. Authorize cloud transfer of private images and protect output text. See ImageAnalysisResult API.
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