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1、【核心升级】升级DJL版本到0.34.0
2、【平台支持】新增对 Linux ARM64 架构的全面支持 3、【通用视觉】集成零样本目标检测模型 4、【活体检测】优化视频检测流程，实现 Predictor 视频会话级复用 5、【人脸识别】SQLite人脸查询改进线程池 6、【人脸识别】修复 Milvus 向量库下 listFaces 接口的调用异常
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‎README.md‎

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@@ -242,6 +242,19 @@ SmartJavaAI是专为JAVA 开发者打造的一个功能丰富、开箱即用的
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</div>
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</td>
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</tr>
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<tr>
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<td>
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<div align="left">
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<p>零样本目标检测<br>(ZeroShot Object Detection)</p>
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- YOLO-World 模型 <br>
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</div>
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</td>
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<td>
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<div align="center">
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<img src="https://cdn.jsdelivr.net/gh/geekwenjie/SmartJavaAI-Site/images/vision/yolo-world.png" height = "200px"/>
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</div>
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</td>
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</tr>
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<tr>
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<td>
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<div align="left">
@@ -483,7 +496,7 @@ SmartJavaAI是专为JAVA 开发者打造的一个功能丰富、开箱即用的
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<dependency>
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<groupId>cn.smartjavaai</groupId>
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<artifactId>all</artifactId>
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<version>1.0.27</version>
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<version>1.1.0</version>
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</dependency>
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```
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‎all/pom.xml‎

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@@ -6,11 +6,11 @@
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<parent>
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<groupId>cn.smartjavaai</groupId>
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<artifactId>smartjavaai-parent</artifactId>
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<version>1.0.27</version>
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<version>1.1.0</version>
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</parent>
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<artifactId>all</artifactId>
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<version>1.0.27</version>
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<version>1.1.0</version>
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<name>${project.artifactId}</name>
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<description>SmartJavaAI</description>
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<url>https://github.com/geekwenjie/SmartJavaAI</url>

‎bom/pom.xml‎

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@@ -6,10 +6,10 @@
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<parent>
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<groupId>cn.smartjavaai</groupId>
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<artifactId>smartjavaai-parent</artifactId>
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<version>1.0.27</version>
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<version>1.1.0</version>
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</parent>
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<version>1.0.27</version>
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<version>1.1.0</version>
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<artifactId>bom</artifactId>
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<name>bom</name>
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<description>统一版本管理的 BOM 包，同时支持 import 和全量依赖</description>

‎common/pom.xml‎

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@@ -6,7 +6,7 @@
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<parent>
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<groupId>cn.smartjavaai</groupId>
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<artifactId>smartjavaai-parent</artifactId>
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<version>1.0.27</version>
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<version>1.1.0</version>
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</parent>
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<name>common</name>

‎common/src/main/java/cn/smartjavaai/common/executor/GlobalExecutor.java‎

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@@ -0,0 +1,53 @@
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package cn.smartjavaai.common.executor;
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import java.util.concurrent.ExecutorService;
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import java.util.concurrent.SynchronousQueue;
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import java.util.concurrent.ThreadPoolExecutor;
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import java.util.concurrent.TimeUnit;
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/**
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* @author dwj
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* @date 2025/11/26
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*/
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public class GlobalExecutor {
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private static volatile ExecutorService executor;
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public static ExecutorService getExecutor() {
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if (executor == null) {
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synchronized (GlobalExecutor.class) {
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if (executor == null) {
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int cores = Runtime.getRuntime().availableProcessors();
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executor = new ThreadPoolExecutor(
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cores,
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cores * 2,
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60L, TimeUnit.SECONDS,
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new SynchronousQueue<>(),
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runnable -> {
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Thread t = new Thread(runnable);
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t.setDaemon(true); // 守护线程
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return t;
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},
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new ThreadPoolExecutor.DiscardOldestPolicy()
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);
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}
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}
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}
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return executor;
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}
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public static void shutdown() {
40+
if (executor != null) {
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executor.shutdown();
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try {
43+
if (!executor.awaitTermination(5, TimeUnit.SECONDS)) {
44+
executor.shutdownNow();
45+
}
46+
} catch (InterruptedException e) {
47+
executor.shutdownNow();
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Thread.currentThread().interrupt();
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}
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}
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}
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}

‎examples/face-example/pom.xml‎

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@@ -12,7 +12,7 @@
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<maven.compiler.source>11</maven.compiler.source>
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<maven.compiler.target>11</maven.compiler.target>
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<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
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<smartjavaai.version>1.0.27</smartjavaai.version>
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<smartjavaai.version>1.1.0</smartjavaai.version>
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<!--如果打包运行，需要替换成你的main-->
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<exec.mainClass>smartai.examples.face.facedet.FaceDetDemo</exec.mainClass>
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<artifactId>face</artifactId>
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</dependency>
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<dependency>
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<groupId>ai.djl.pytorch</groupId>
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<artifactId>pytorch-jni</artifactId>
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<version>2.5.1-0.32.0</version>
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<version>2.7.1-0.34.0</version>
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<scope>runtime</scope>
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</dependency>
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<groupId>ai.djl.pytorch</groupId>
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<artifactId>pytorch-native-cpu</artifactId>
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<classifier>${djl.platform.windows-x86_64}</classifier>
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<version>2.5.1</version>
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<version>2.7.1</version>
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<scope>runtime</scope>
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</dependency>
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<groupId>ai.djl.pytorch</groupId>
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<artifactId>pytorch-native-cpu</artifactId>
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<classifier>${djl.platform.linux-x86_64}</classifier>
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<version>2.5.1</version>
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<version>2.7.1</version>
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<scope>runtime</scope>
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</dependency>
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<!-- linux aarch64 平台 (保留对应平台的配置，可以减小包大小)-->
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<dependency>
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<groupId>ai.djl.pytorch</groupId>
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<artifactId>pytorch-native-cpu-precxx11</artifactId>
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<classifier>${djl.platform.linux-x86_64}</classifier>
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<version>2.5.1</version>
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<scope>runtime</scope>
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<groupId>org.bytedeco</groupId>
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<artifactId>javacpp</artifactId>
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<version>${javacv.version}</version>
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<classifier>${javacv.platform.linux-arm64}</classifier>
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</dependency>
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<dependency>
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<groupId>org.bytedeco</groupId>
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<artifactId>ffmpeg</artifactId>
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<version>6.1.1-1.5.10</version>
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<classifier>${javacv.platform.linux-arm64}</classifier>
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</dependency>
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<dependency>
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<groupId>org.bytedeco</groupId>
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<artifactId>openblas</artifactId>
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<version>0.3.26-1.5.10</version>
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<classifier>${javacv.platform.linux-arm64}</classifier>
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</dependency>
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<dependency>
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<groupId>org.bytedeco</groupId>
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<artifactId>opencv</artifactId>
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<version>4.9.0-1.5.10</version>
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<classifier>${javacv.platform.linux-arm64}</classifier>
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</dependency>
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<dependency>
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<groupId>ai.djl.pytorch</groupId>
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<artifactId>pytorch-native-cpu</artifactId>
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<classifier>${djl.platform.linux-aarch64}</classifier>
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<version>2.7.1</version>
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<scope>runtime</scope>
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</dependency>
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184209
<!-- macOS M系列 平台 (保留对应平台的配置，可以减小包大小)-->
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<dependency>
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<groupId>ai.djl.pytorch</groupId>
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<artifactId>pytorch-native-cpu</artifactId>
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<classifier>${djl.platform.osx-aarch64}</classifier>
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<version>2.5.1</version>
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<version>2.7.1</version>
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<scope>runtime</scope>
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</dependency>
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‎examples/ocr-examples/pom.xml‎

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<maven.compiler.source>11</maven.compiler.source>
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<maven.compiler.target>11</maven.compiler.target>
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<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
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<smartjavaai.version>1.0.27</smartjavaai.version>
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<smartjavaai.version>1.1.0</smartjavaai.version>
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<!--如果打包运行，需要替换成你的main-->
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<exec.mainClass>smartai.examples.ocr.common.OcrRecognizeDemo</exec.mainClass>
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<dependency>
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<groupId>ai.djl.pytorch</groupId>
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<artifactId>pytorch-jni</artifactId>
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<version>2.5.1-0.32.0</version>
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<version>2.7.1-0.34.0</version>
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<scope>runtime</scope>
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</dependency>
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<groupId>ai.djl.pytorch</groupId>
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<artifactId>pytorch-native-cpu</artifactId>
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<classifier>${djl.platform.windows-x86_64}</classifier>
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<version>2.5.1</version>
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<version>2.7.1</version>
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<scope>runtime</scope>
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</dependency>
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<groupId>ai.djl.pytorch</groupId>
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<artifactId>pytorch-native-cpu</artifactId>
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<classifier>${djl.platform.linux-x86_64}</classifier>
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<version>2.5.1</version>
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<version>2.7.1</version>
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<scope>runtime</scope>
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</dependency>
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<!-- linux aarch64 平台 (保留对应平台的配置，可以减小包大小)-->
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<dependency>
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<groupId>org.bytedeco</groupId>
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<artifactId>javacpp</artifactId>
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<version>${javacv.version}</version>
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<classifier>${javacv.platform.linux-arm64}</classifier>
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</dependency>
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<dependency>
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<groupId>org.bytedeco</groupId>
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<artifactId>ffmpeg</artifactId>
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<version>6.1.1-1.5.10</version>
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<classifier>${javacv.platform.linux-arm64}</classifier>
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</dependency>
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<dependency>
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<groupId>org.bytedeco</groupId>
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<artifactId>openblas</artifactId>
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<version>0.3.26-1.5.10</version>
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<classifier>${javacv.platform.linux-arm64}</classifier>
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</dependency>
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<dependency>
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<groupId>org.bytedeco</groupId>
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<artifactId>opencv</artifactId>
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<version>4.9.0-1.5.10</version>
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<classifier>${javacv.platform.linux-arm64}</classifier>
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</dependency>
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<dependency>
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<groupId>ai.djl.pytorch</groupId>
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<artifactId>pytorch-native-cpu-precxx11</artifactId>
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<classifier>${djl.platform.linux-x86_64}</classifier>
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<version>2.5.1</version>
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<artifactId>pytorch-native-cpu</artifactId>
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<classifier>${djl.platform.linux-aarch64}</classifier>
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<version>2.7.1</version>
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<scope>runtime</scope>
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</dependency>
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@@ -214,7 +243,7 @@
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<groupId>ai.djl.pytorch</groupId>
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<artifactId>pytorch-native-cpu</artifactId>
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<classifier>${djl.platform.osx-aarch64}</classifier>
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<version>2.5.1</version>
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<version>2.7.1</version>
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<scope>runtime</scope>
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</dependency>
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‎examples/speech-examples/pom.xml‎

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<maven.compiler.source>11</maven.compiler.source>
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<maven.compiler.target>11</maven.compiler.target>
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<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
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<smartjavaai.version>1.0.27</smartjavaai.version>
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<smartjavaai.version>1.1.0</smartjavaai.version>
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<!--如果打包运行，需要替换成你的main-->
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<exec.mainClass>smartai.examples.speech.asr.common.OcrRecognizeDemo</exec.mainClass>
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‎examples/translation-example/pom.xml‎

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<maven.compiler.source>11</maven.compiler.source>
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<maven.compiler.target>11</maven.compiler.target>
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<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
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<smartjavaai.version>1.0.27</smartjavaai.version>
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<smartjavaai.version>1.1.0</smartjavaai.version>
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<!--如果打包运行，需要替换成你的main-->
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<exec.mainClass>smartai.examples.nlp.translation.TranslationDemo</exec.mainClass>
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9393
<dependency>
9494
<groupId>ai.djl.pytorch</groupId>
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<artifactId>pytorch-jni</artifactId>
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<version>2.5.1-0.32.0</version>
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<version>2.7.1-0.34.0</version>
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<scope>runtime</scope>
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</dependency>
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<groupId>ai.djl.pytorch</groupId>
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<artifactId>pytorch-native-cpu</artifactId>
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<classifier>${djl.platform.windows-x86_64}</classifier>
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<version>2.5.1</version>
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<version>2.7.1</version>
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<scope>runtime</scope>
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</dependency>
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<groupId>ai.djl.pytorch</groupId>
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<artifactId>pytorch-native-cpu</artifactId>
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<classifier>${djl.platform.linux-x86_64}</classifier>
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<version>2.5.1</version>
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<version>2.7.1</version>
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<scope>runtime</scope>
121121
</dependency>
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<!-- linux aarch64 平台 (保留对应平台的配置，可以减小包大小)-->
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<dependency>
124125
<groupId>ai.djl.pytorch</groupId>
125-
<artifactId>pytorch-native-cpu-precxx11</artifactId>
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<classifier>${djl.platform.linux-x86_64}</classifier>
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<version>2.5.1</version>
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<artifactId>pytorch-native-cpu</artifactId>
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<classifier>${djl.platform.linux-aarch64}</classifier>
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<version>2.7.1</version>
128129
<scope>runtime</scope>
129130
</dependency>
130131

131-
132132
<!-- macOS M系列 平台 (保留对应平台的配置，可以减小包大小)-->
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<dependency>
134134
<groupId>ai.djl.pytorch</groupId>
135135
<artifactId>pytorch-native-cpu</artifactId>
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<classifier>${djl.platform.osx-aarch64}</classifier>
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<version>2.7.1</version>
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<scope>runtime</scope>
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</dependency>
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‎examples/translation-example/src/main/java/smartai/examples/nlp/translation/TranslationDemo.java‎

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@@ -44,7 +44,7 @@ public TranslationModel getNllbModel() {
4444
//指定翻译模型：NLLB,切换模型需同时修改modelEnum及modelPath
4545
config.setModelEnum(TranslationModeEnum.NLLB_MODEL);
4646
//指定模型路径，需将模型路径修改为本地的模型路径
47-
config.setModelPath("/Users/xxx/Documents/develop/model/trans/traced_translation_cpu.pt");
47+
config.setModelPath("/Users/wenjie/Documents/develop/model/translate/nllb/traced_translation_cpu.pt");
4848
config.setDevice(DeviceEnum.CPU);
4949
return TranslationModelFactory.getInstance().getModel(config);
5050
}

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