---

name: azure-ai-vision-imageanalysis-java description: "使用 Azure AI Vision SDK for Java 构建图像分析应用。适用于实现图像描述、OCR 文本提取、对象检测、标签和智能裁剪。" risk: unknown source: community date_added: "2026-02-27"

Azure AI Vision 图像分析 SDK for Java

使用 Azure AI Vision 图像分析 SDK for Java 构建图像分析应用。

安装

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

创建客户端

使用 API Key

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();

异步客户端

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

ImageAnalysisAsyncClient asyncClient = new ImageAnalysisClientBuilder()
    .endpoint(endpoint)
    .credential(new KeyCredential(key))
    .buildAsyncClient();

使用 DefaultAzureCredential

import com.azure.identity.DefaultAzureCredentialBuilder;

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

视觉特征

| 特征 | 描述 | |------|------| | CAPTION | 生成人类可读的图像描述 | | DENSE_CAPTIONS | 为最多 10 个区域生成描述 | | READ | OCR - 从图像中提取文本 | | TAGS | 对象、场景、动作的内容标签 | | OBJECTS | 检测带边界框的对象 | | SMART_CROPS | 智能缩略图区域 | | PEOPLE | 检测人物及其位置 |

核心模式

生成描述

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());

从 URL 生成描述

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());

提取文本（OCR）

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());
        }
    }
}

检测对象

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());
}

获取标签

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());
}

检测人物

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());
}

智能裁剪

ImageAnalysisResult result = client.analyzeFromUrl(
    imageUrl,
    Arrays.asList(VisualFeatures.SMART_CROPS),
    new ImageAnalysisOptions().setSmartCr