# SkillPatch skill: azure-ai-vision-imageanalysis-java

This skill provides guidance for building image analysis applications using the Azure AI Vision SDK for Java. It covers client creation (with API key, async, and DefaultAzureCredential), available visual features, and core usage patterns including image captioning, OCR text extraction, object detection, tagging, smart cropping, and people detection. Agents can follow the provided code snippets and workflows to implement image analysis capabilities end-to-end.

You (the agent) were given this URL and asked to use this skill. This is a **public** skill — no SkillPatch account, API key, or prior setup is required. Two ways to use it:

**1. Use it right now** — the skill's complete file tree (SKILL.md + all reference files) is inlined below; read `SKILL.md` first, then follow it, consulting the other files as it directs.

**2. Install the exact package onto disk** (recommended if you can run a shell — this reproduces the skill byte-for-byte, including any binary assets that can't be inlined):

```bash
mkdir -p .claude/skills/azure-ai-vision-imageanalysis-java
curl -sSL https://skillpatch.dev/install_skill/azure-ai-vision-imageanalysis-java | tar -xz -C .claude/skills/
```

(`.claude/skills/` is Claude Code's convention; use whatever directory your agent loads skills from.)


---

## Skill files (2)

- `SKILL.md`
- `references/examples.md`


### `SKILL.md`

````markdown
---
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.
license: MIT
metadata:
  author: Microsoft
  version: "1.0.0"
  package: com.azure:azure-ai-vision-imageanalysis
---

# 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.core.credential.TokenCredential;
import com.azure.identity.AzureIdentityEnvVars;
import com.azure.identity.DefaultAzureCredentialBuilder;
import com.azure.identity.ManagedIdentityCredentialBuilder;

TokenCredential credential = new DefaultAzureCredentialBuilder()
    .requireEnvVars(AzureIdentityEnvVars.AZURE_TOKEN_CREDENTIALS)
    .build();
// Or use a specific credential directly in production:
// See https://learn.microsoft.com/java/api/overview/azure/identity-readme?view=azure-java-stable#credential-classes
// TokenCredential credential = new ManagedIdentityCredentialBuilder().build();

ImageAnalysisClient client = new ImageAnalysisClientBuilder()
    .endpoint(endpoint)
    .credential(credential)
    .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/ # Required for all auth methods
VISION_KEY=<your-api-key> # Only required for AzureKeyCredential auth
AZURE_TOKEN_CREDENTIALS=prod  # Required only if DefaultAzureCredential is used in production
```

## 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"

````


### `references/examples.md`

````markdown
# Azure AI Vision Image Analysis Java SDK - Examples

Comprehensive code examples for the Azure AI Vision Image Analysis SDK for Java.

## Table of Contents

- [Maven Dependency](#maven-dependency)
- [Client Creation](#client-creation)
- [Visual Features](#visual-features)
- [Generate Caption](#generate-caption)
- [Extract Text (OCR)](#extract-text-ocr)
- [Detect Objects](#detect-objects)
- [Get Tags](#get-tags)
- [Detect People](#detect-people)
- [Smart Cropping](#smart-cropping)
- [Dense Captions](#dense-captions)
- [Multiple Features](#multiple-features)
- [Async Patterns](#async-patterns)
- [Error Handling](#error-handling)
- [Complete Application Example](#complete-application-example)

## Maven Dependency

```xml
<dependency>
    <groupId>com.azure</groupId>
    <artifactId>azure-ai-vision-imageanalysis</artifactId>
    <version>1.1.0-beta.1</version>
</dependency>

<!-- For DefaultAzureCredential -->
<dependency>
    <groupId>com.azure</groupId>
    <artifactId>azure-identity</artifactId>
    <version>1.14.2</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();
```

### With DefaultAzureCredential (Recommended)

```java
import com.azure.identity.DefaultAzureCredentialBuilder;

ImageAnalysisClient client = new ImageAnalysisClientBuilder()
    .endpoint(endpoint)
    .credential(new DefaultAzureCredentialBuilder().build())
    .buildClient();
```

### Async Client

```java
import com.azure.ai.vision.imageanalysis.ImageAnalysisAsyncClient;

ImageAnalysisAsyncClient asyncClient = new ImageAnalysisClientBuilder()
    .endpoint(endpoint)
    .credential(new DefaultAzureCredentialBuilder().build())
    .buildAsyncClient();
```

## 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 |

## Generate Caption

### From File

```java
import com.azure.ai.vision.imageanalysis.models.*;
import com.azure.core.util.BinaryData;
import java.io.File;
import java.util.Arrays;

// Load image from file
File imageFile = new File("photo.jpg");
BinaryData imageData = BinaryData.fromFile(imageFile.toPath());

// Analyze with caption
ImageAnalysisResult result = client.analyze(
    imageData,
    Arrays.asList(VisualFeatures.CAPTION),
    new ImageAnalysisOptions().setGenderNeutralCaption(true));

// Get caption
CaptionResult caption = result.getCaption();
System.out.printf("Caption: \"%s\" (confidence: %.4f)%n",
    caption.getText(),
    caption.getConfidence());
```

### From URL

```java
String imageUrl = "https://example.com/photo.jpg";

ImageAnalysisResult result = client.analyzeFromUrl(
    imageUrl,
    Arrays.asList(VisualFeatures.CAPTION),
    new ImageAnalysisOptions().setGenderNeutralCaption(true));

System.out.printf("Caption: \"%s\"%n", result.getCaption().getText());
```

### With Language

```java
ImageAnalysisResult result = client.analyzeFromUrl(
    imageUrl,
    Arrays.asList(VisualFeatures.CAPTION),
    new ImageAnalysisOptions()
        .setGenderNeutralCaption(true)
        .setLanguage("en"));  // Supported: en, es, fr, de, it, pt, ja, ko, zh
```

## Extract Text (OCR)

```java
File documentImage = new File("document.jpg");
BinaryData imageData = BinaryData.fromFile(documentImage.toPath());

ImageAnalysisResult result = client.analyze(
    imageData,
    Arrays.asList(VisualFeatures.READ),
    null);

ReadResult readResult = result.getRead();

System.out.println("=== Extracted Text ===");
for (DetectedTextBlock block : readResult.getBlocks()) {
    System.out.println("Block:");
    
    for (DetectedTextLine line : block.getLines()) {
        System.out.printf("  Line: '%s'%n", line.getText());
        
        // Get bounding polygon
        List<ImagePoint> polygon = line.getBoundingPolygon();
        System.out.printf("    Bounding polygon: [");
        for (ImagePoint point : polygon) {
            System.out.printf("(%d,%d) ", point.getX(), point.getY());
        }
        System.out.println("]");
        
        // Get individual words
        for (DetectedTextWord word : line.getWords()) {
            System.out.printf("    Word: '%s' (confidence: %.4f)%n",
                word.getText(),
                word.getConfidence());
        }
    }
}
```

### Extract Text from URL

```java
String documentUrl = "https://example.com/receipt.jpg";

ImageAnalysisResult result = client.analyzeFromUrl(
    documentUrl,
    Arrays.asList(VisualFeatures.READ),
    null);

// Collect all text
StringBuilder fullText = new StringBuilder();
for (DetectedTextBlock block : result.getRead().getBlocks()) {
    for (DetectedTextLine line : block.getLines()) {
        fullText.append(line.getText()).append("\n");
    }
}

System.out.println("Full extracted text:");
System.out.println(fullText.toString());
```

## Detect Objects

```java
String imageUrl = "https://example.com/street-scene.jpg";

ImageAnalysisResult result = client.analyzeFromUrl(
    imageUrl,
    Arrays.asList(VisualFeatures.OBJECTS),
    null);

System.out.println("=== Detected Objects ===");
for (DetectedObject obj : result.getObjects()) {
    // Get the primary tag (highest confidence)
    DetectedTag primaryTag = obj.getTags().get(0);
    
    System.out.printf("Object: %s (confidence: %.4f)%n",
        primaryTag.getName(),
        primaryTag.getConfidence());
    
    // Get bounding box
    ImageBoundingBox box = obj.getBoundingBox();
    System.out.printf("  Location: x=%d, y=%d, width=%d, height=%d%n",
        box.getX(), box.getY(), box.getWidth(), box.getHeight());
    
    // Additional tags for this object
    if (obj.getTags().size() > 1) {
        System.out.println("  Additional tags:");
        for (int i = 1; i < obj.getTags().size(); i++) {
            DetectedTag tag = obj.getTags().get(i);
            System.out.printf("    - %s (%.4f)%n", tag.getName(), tag.getConfidence());
        }
    }
}

System.out.printf("Total objects detected: %d%n", result.getObjects().size());
```

## Get Tags

```java
String imageUrl = "https://example.com/nature.jpg";

ImageAnalysisResult result = client.analyzeFromUrl(
    imageUrl,
    Arrays.asList(VisualFeatures.TAGS),
    null);

System.out.println("=== Image Tags ===");

// Sort by confidence
List<DetectedTag> sortedTags = new ArrayList<>(result.getTags());
sortedTags.sort((a, b) -> Double.compare(b.getConfidence(), a.getConfidence()));

for (DetectedTag tag : sortedTags) {
    System.out.printf("%-20s (confidence: %.4f)%n",
        tag.getName(),
        tag.getConfidence());
}

// Filter high-confidence tags (>80%)
System.out.println("\nHigh-confidence tags (>80%):");
for (DetectedTag tag : sortedTags) {
    if (tag.getConfidence() > 0.80) {
        System.out.println("  - " + tag.getName());
    }
}
```

## Detect People

```java
String imageUrl = "https://example.com/group-photo.jpg";

ImageAnalysisResult result = client.analyzeFromUrl(
    imageUrl,
    Arrays.asList(VisualFeatures.PEOPLE),
    null);

System.out.println("=== Detected People ===");
System.out.printf("Number of people: %d%n", result.getPeople().size());

int personIndex = 1;
for (DetectedPerson person : result.getPeople()) {
    ImageBoundingBox box = person.getBoundingBox();
    
    System.out.printf("Person %d:%n", personIndex++);
    System.out.printf("  Confidence: %.4f%n", person.getConfidence());
    System.out.printf("  Location: x=%d, y=%d, width=%d, height=%d%n",
        box.getX(), box.getY(), box.getWidth(), box.getHeight());
    
    // Calculate center point
    int centerX = box.getX() + box.getWidth() / 2;
    int centerY = box.getY() + box.getHeight() / 2;
    System.out.printf("  Center: (%d, %d)%n", centerX, centerY);
}
```

## Smart Cropping

```java
String imageUrl = "https://example.com/landscape.jpg";

// Request crops with specific aspect ratios
ImageAnalysisResult result = client.analyzeFromUrl(
    imageUrl,
    Arrays.asList(VisualFeatures.SMART_CROPS),
    new ImageAnalysisOptions()
        .setSmartCropsAspectRatios(Arrays.asList(1.0, 1.5, 0.75)));  // 1:1, 3:2, 3:4

System.out.println("=== Smart Crop Regions ===");
for (CropRegion crop : result.getSmartCrops()) {
    ImageBoundingBox box = crop.getBoundingBox();
    
    System.out.printf("Aspect ratio: %.2f%n", crop.getAspectRatio());
    System.out.printf("  Region: x=%d, y=%d, width=%d, height=%d%n",
        box.getX(), box.getY(), box.getWidth(), box.getHeight());
}
```

### Use Smart Crops for Thumbnails

```java
// Get square thumbnail region
ImageAnalysisResult result = client.analyzeFromUrl(
    imageUrl,
    Arrays.asList(VisualFeatures.SMART_CROPS),
    new ImageAnalysisOptions()
        .setSmartCropsAspectRatios(Arrays.asList(1.0)));  // Square

CropRegion squareCrop = result.getSmartCrops().get(0);
ImageBoundingBox box = squareCrop.getBoundingBox();

// Use these coordinates to crop your image
System.out.printf("Thumbnail region: x=%d, y=%d, size=%dx%d%n",
    box.getX(), box.getY(), box.getWidth(), box.getHeight());
```

## Dense Captions

```java
String imageUrl = "https://example.com/complex-scene.jpg";

ImageAnalysisResult result = client.analyzeFromUrl(
    imageUrl,
    Arrays.asList(VisualFeatures.DENSE_CAPTIONS),
    new ImageAnalysisOptions().setGenderNeutralCaption(true));

System.out.println("=== Dense Captions ===");
int regionIndex = 1;
for (DenseCaption caption : result.getDenseCaptions()) {
    ImageBoundingBox box = caption.getBoundingBox();
    
    System.out.printf("Region %d:%n", regionIndex++);
    System.out.printf("  Caption: \"%s\"%n", caption.getText());
    System.out.printf("  Confidence: %.4f%n", caption.getConfidence());
    System.out.printf("  Location: x=%d, y=%d, width=%d, height=%d%n",
        box.getX(), box.getY(), box.getWidth(), box.getHeight());
}
```

## Multiple Features

Analyze with multiple features in a single request.

```java
String imageUrl = "https://example.com/photo.jpg";

ImageAnalysisResult result = client.analyzeFromUrl(
    imageUrl,
    Arrays.asList(
        VisualFeatures.CAPTION,
        VisualFeatures.TAGS,
        VisualFeatures.OBJECTS,
        VisualFeatures.PEOPLE,
        VisualFeatures.READ),
    new ImageAnalysisOptions()
        .setGenderNeutralCaption(true)
        .setLanguage("en"));

// Caption
System.out.println("=== Caption ===");
System.out.printf("\"%s\" (%.4f)%n",
    result.getCaption().getText(),
    result.getCaption().getConfidence());

// Tags
System.out.println("\n=== Tags ===");
for (DetectedTag tag : result.getTags()) {
    if (tag.getConfidence() > 0.7) {
        System.out.printf("  %s (%.2f)%n", tag.getName(), tag.getConfidence());
    }
}

// Objects
System.out.println("\n=== Objects ===");
System.out.printf("  Count: %d%n", result.getObjects().size());
for (DetectedObject obj : result.getObjects()) {
    System.out.printf("  - %s%n", obj.getTags().get(0).getName());
}

// People
System.out.println("\n=== People ===");
System.out.printf("  Count: %d%n", result.getPeople().size());

// Text
System.out.println("\n=== Text ===");
int lineCount = 0;
for (DetectedTextBlock block : result.getRead().getBlocks()) {
    lineCount += block.getLines().size();
}
System.out.printf("  Lines of text: %d%n", lineCount);

// Metadata
System.out.println("\n=== Image Metadata ===");
System.out.printf("  Dimensions: %d x %d%n",
    result.getMetadata().getWidth(),
    result.getMetadata().getHeight());
System.out.printf("  Model: %s%n", result.getModelVersion());
```

## Async Patterns

### Basic Async Analysis

```java
ImageAnalysisAsyncClient asyncClient = new ImageAnalysisClientBuilder()
    .endpoint(endpoint)
    .credential(new DefaultAzureCredentialBuilder().build())
    .buildAsyncClient();

String imageUrl = "https://example.com/photo.jpg";

asyncClient.analyzeFromUrl(
    imageUrl,
    Arrays.asList(VisualFeatures.CAPTION, VisualFeatures.TAGS),
    new ImageAnalysisOptions().setGenderNeutralCaption(true))
    .subscribe(
        result -> {
            System.out.println("Caption: " + result.getCaption().getText());
            System.out.println("Tags: " + result.getTags().size());
        },
        error -> System.err.println("Error: " + error.getMessage()),
        () -> System.out.println("Analysis complete")
    );

// Keep application running
Thread.sleep(10000);
```

### Parallel Analysis

```java
import reactor.core.publisher.Flux;
import reactor.core.publisher.Mono;

List<String> imageUrls = Arrays.asList(
    "https://example.com/image1.jpg",
    "https://example.com/image2.jpg",
    "https://example.com/image3.jpg"
);

Flux.fromIterable(imageUrls)
    .flatMap(url -> asyncClient.analyzeFromUrl(
        url,
        Arrays.asList(VisualFeatures.CAPTION),
        null)
        .map(result -> new ImageResult(url, result.getCaption().getText())))
    .subscribe(
        imageResult -> System.out.printf("%s: %s%n", 
            imageResult.url, imageResult.caption),
        error -> System.err.println("Error: " + error.getMessage())
    );

// Helper class
class ImageResult {
    String url;
    String caption;
    
    ImageResult(String url, String caption) {
        this.url = url;
        this.caption = caption;
    }
}
```

## Error Handling

```java
import com.azure.core.exception.HttpResponseException;

try {
    ImageAnalysisResult result = client.analyzeFromUrl(
        "invalid-url",
        Arrays.asList(VisualFeatures.CAPTION),
        null);
        
} catch (HttpResponseException e) {
    int statusCode = e.getResponse().getStatusCode();
    System.err.println("HTTP Status: " + statusCode);
    System.err.println("Error: " + e.getMessage());
    
    switch (statusCode) {
        case 400:
            System.err.println("Bad request - check image URL or format");
            break;
        case 401:
            System.err.println("Unauthorized - check API key");
            break;
        case 404:
            System.err.println("Resource not found");
            break;
        case 415:
            System.err.println("Unsupported media type - check image format");
            break;
        case 429:
            System.err.println("Rate limited - retry with backoff");
            break;
        default:
            System.err.println("Unexpected error");
    }
} catch (Exception e) {
    System.err.println("Unexpected error: " + e.getMessage());
}
```

## Complete Application Example

```java
import com.azure.ai.vision.imageanalysis.ImageAnalysisClient;
import com.azure.ai.vision.imageanalysis.ImageAnalysisClientBuilder;
import com.azure.ai.vision.imageanalysis.models.*;
import com.azure.core.util.BinaryData;
import com.azure.identity.DefaultAzureCredentialBuilder;

import java.io.File;
import java.util.*;

public class ImageAnalyzer {
    
    private final ImageAnalysisClient client;
    
    public ImageAnalyzer() {
        this.client = new ImageAnalysisClientBuilder()
            .endpoint(System.getenv("VISION_ENDPOINT"))
            .credential(new DefaultAzureCredentialBuilder().build())
            .buildClient();
    }
    
    public ImageAnalysisReport analyzeImage(String imagePath) {
        File imageFile = new File(imagePath);
        BinaryData imageData = BinaryData.fromFile(imageFile.toPath());
        
        ImageAnalysisResult result = client.analyze(
            imageData,
            Arrays.asList(
                VisualFeatures.CAPTION,
                VisualFeatures.TAGS,
                VisualFeatures.OBJECTS,
                VisualFeatures.PEOPLE,
                VisualFeatures.READ),
            new ImageAnalysisOptions()
                .setGenderNeutralCaption(true)
                .setLanguage("en"));
        
        return buildReport(imagePath, result);
    }
    
    public ImageAnalysisReport analyzeImageUrl(String imageUrl) {
        ImageAnalysisResult result = client.analyzeFromUrl(
            imageUrl,
            Arrays.asList(
                VisualFeatures.CAPTION,
                VisualFeatures.TAGS,
                VisualFeatures.OBJECTS,
                VisualFeatures.PEOPLE,
                VisualFeatures.READ),
            new ImageAnalysisOptions()
                .setGenderNeutralCaption(true)
                .setLanguage("en"));
        
        return buildReport(imageUrl, result);
    }
    
    private ImageAnalysisReport buildReport(String source, ImageAnalysisResult result) {
        // Extract caption
        String caption = result.getCaption().getText();
        double captionConfidence = result.getCaption().getConfidence();
        
        // Extract high-confidence tags
        List<String> tags = new ArrayList<>();
        for (DetectedTag tag : result.getTags()) {
            if (tag.getConfidence() > 0.7) {
                tags.add(tag.getName());
            }
        }
        
        // Extract objects
        List<String> objects = new ArrayList<>();
        for (DetectedObject obj : result.getObjects()) {
            objects.add(obj.getTags().get(0).getName());
        }
        
        // Count people
        int peopleCount = result.getPeople().size();
        
        // Extract text
        StringBuilder extractedText = new StringBuilder();
        for (DetectedTextBlock block : result.getRead().getBlocks()) {
            for (DetectedTextLine line : block.getLines()) {
                extractedText.append(line.getText()).append("\n");
            }
        }
        
        return new ImageAnalysisReport(
            source,
            caption,
            captionConfidence,
            tags,
            objects,
            peopleCount,
            extractedText.toString().trim(),
            result.getMetadata().getWidth(),
            result.getMetadata().getHeight()
        );
    }
    
    // Report class
    public static class ImageAnalysisReport {
        public final String source;
        public final String caption;
        public final double captionConfidence;
        public final List<String> tags;
        public final List<String> objects;
        public final int peopleCount;
        public final String extractedText;
        public final int width;
        public final int height;
        
        public ImageAnalysisReport(String source, String caption, double captionConfidence,
                                   List<String> tags, List<String> objects, int peopleCount,
                                   String extractedText, int width, int height) {
            this.source = source;
            this.caption = caption;
            this.captionConfidence = captionConfidence;
            this.tags = tags;
            this.objects = objects;
            this.peopleCount = peopleCount;
            this.extractedText = extractedText;
            this.width = width;
            this.height = height;
        }
        
        @Override
        public String toString() {
            StringBuilder sb = new StringBuilder();
            sb.append("=== Image Analysis Report ===\n");
            sb.append(String.format("Source: %s\n", source));
            sb.append(String.format("Dimensions: %dx%d\n", width, height));
            sb.append(String.format("Caption: \"%s\" (%.2f%%)\n", caption, captionConfidence * 100));
            sb.append(String.format("Tags: %s\n", String.join(", ", tags)));
            sb.append(String.format("Objects: %s\n", String.join(", ",
...<truncated>
````