虹软SDK的简单使用
Java实现人脸识别,但是又不会自己实现算法,找SDK时发现了虹软。虹软SDK具有免费、识别率高等优点,然后到网上搜这个SDK的教程,没搜到,就自己探索,发现它自带的官方文档其实介绍的挺全面的,本文是由官方文档改编。
虹软SDK的激活
首先到官网注册账号,然后新建应用,然后获取到APP_ID和SDK_KEY
然后点击下载SDK,下好之后的项目结构:
|---doc
| |---ARCSOFT_ARC_FACE_JAVA_DEVELOPER'S_GUIDE.pdf 开发说明文档
|---lib
|---|---Win32/x64/linux64
| |---|---libarcsoft_face.dll 算法库
| |---|---libarcsoft_face_engine.dll 引擎库
| |---|---libarcsoft_face_engine_jni.dll 引擎库
| |---arcsoft-sdk-face-3.0.0.0.jar java依赖库
|---samplecode
| |---FaceEngineTest.java 示例代码
|---releasenotes.txt 说明文件
这里介绍的是windows版本,要将这三个.dll文件所在的文件夹添加到环境变量里面的Path里面去
再把下载的文件里面的jar包导入到项目里面去
然后就可以开始激活了
import com.arcsoft.face.FaceEngine;
import com.arcsoft.face.enums.ErrorInfo;
public class FaceTestMd {
public void engineTest() {
String appId = "你的APP_ID";
String sdkKey = "你的SDK_KEY";
FaceEngine faceEngine = new FaceEngine();
int errorCode = faceEngine.activeOnline(appId, sdkKey);
if (errorCode != ErrorInfo.MOK.getValue() &&
errorCode != ErrorInfo.MERR_ASF_ALREADY_ACTIVATED.getValue()) {
System.out.println("引擎激活失败:" + errorCode);
} else {
System.out.println("引擎激活成功");
}
}
public static void main(String[] args) {
new FaceTestMd().engineTest();
}
}
对引擎进行引擎配置和功能配置
package top.gostack.demo1;
import com.arcsoft.face.EngineConfiguration;
import com.arcsoft.face.FaceEngine;
import com.arcsoft.face.FunctionConfiguration;
import com.arcsoft.face.enums.DetectMode;
import com.arcsoft.face.enums.DetectOrient;
import com.arcsoft.face.enums.ErrorInfo;
public class FaceTestMd {
public void engineTest() {
String appId = "";
String sdkKey = "";
FaceEngine faceEngine = new FaceEngine();
int errorCode = faceEngine.activeOnline(appId, sdkKey);
if (errorCode != ErrorInfo.MOK.getValue() &&
errorCode != ErrorInfo.MERR_ASF_ALREADY_ACTIVATED.getValue()) {
System.out.println("引擎激活失败:" + errorCode);
} else {
System.out.println("引擎激活成功");
}
EngineConfiguration engineConfiguration = new EngineConfiguration();
engineConfiguration.setDetectMode(DetectMode.ASF_DETECT_MODE_IMAGE);
engineConfiguration.setDetectFaceOrientPriority(DetectOrient.ASF_OP_0_ONLY);
engineConfiguration.setDetectFaceScaleVal(16);
engineConfiguration.setDetectFaceMaxNum(10);
final FunctionConfiguration functionConfiguration = new FunctionConfiguration();
functionConfiguration.setSupportAge(true);
functionConfiguration.setSupportFaceDetect(true);
functionConfiguration.setSupportFaceRecognition(true);
functionConfiguration.setSupportGender(true);
functionConfiguration.setSupportFace3dAngle(true);
functionConfiguration.setSupportLiveness(true);
functionConfiguration.setSupportIRLiveness(false);
engineConfiguration.setFunctionConfiguration(functionConfiguration);
int errorCode2 = faceEngine.init(engineConfiguration);
if (errorCode2 != ErrorInfo.MOK.getValue()) {
System.out.println("初始化引擎失败");
} else {
System.out.println("初始化引擎成功");
}
}
public static void main(String[] args) {
new FaceTestMd().engineTest();
}
}
经过以上的操作引擎初始化算是成功了,然后下面可以进行功能测试
人脸相似度比对
package top.gostack.demo1;
import com.arcsoft.face.*;
import com.arcsoft.face.enums.DetectMode;
import com.arcsoft.face.enums.DetectOrient;
import com.arcsoft.face.enums.ErrorInfo;
import com.arcsoft.face.toolkit.ImageInfo;
import java.io.File;
import java.util.ArrayList;
import java.util.List;
import static com.arcsoft.face.toolkit.ImageFactory.getRGBData;
public class FaceTestMd {
public void engineTest() {
String appId = "";
String sdkKey = "";
FaceEngine faceEngine = new FaceEngine();
int errorCode = faceEngine.activeOnline(appId, sdkKey);
if (errorCode != ErrorInfo.MOK.getValue() &&
errorCode != ErrorInfo.MERR_ASF_ALREADY_ACTIVATED.getValue()) {
System.out.println("引擎激活失败:" + errorCode);
} else {
System.out.println("引擎激活成功");
}
EngineConfiguration engineConfiguration = new EngineConfiguration();
engineConfiguration.setDetectMode(DetectMode.ASF_DETECT_MODE_IMAGE);
engineConfiguration.setDetectFaceOrientPriority(DetectOrient.ASF_OP_0_ONLY);
engineConfiguration.setDetectFaceScaleVal(16);
engineConfiguration.setDetectFaceMaxNum(10);
final FunctionConfiguration functionConfiguration = new FunctionConfiguration();
functionConfiguration.setSupportAge(true);
functionConfiguration.setSupportFaceDetect(true);
functionConfiguration.setSupportFaceRecognition(true);
functionConfiguration.setSupportGender(true);
functionConfiguration.setSupportFace3dAngle(true);
functionConfiguration.setSupportLiveness(true);
functionConfiguration.setSupportIRLiveness(false);
engineConfiguration.setFunctionConfiguration(functionConfiguration);
int errorCode2 = faceEngine.init(engineConfiguration);
if (errorCode2 != ErrorInfo.MOK.getValue()) {
System.out.println("初始化引擎失败");
} else {
System.out.println("初始化引擎成功");
}
String imgPath1 = "F:/Spring/SpringMVC/workplace/Ace_Face/resources/wyy1.jpg";
String imgPath2 = "F:/Spring/SpringMVC/workplace/Ace_Face/resources/wyy4.jpg";
FaceFeature faceFeature1 = getFaceFeature(imgPath1, faceEngine);
FaceFeature faceFeature2 = getFaceFeature(imgPath2, faceEngine);
FaceSimilar faceSimilar = new FaceSimilar();
int errorCode5 = faceEngine.compareFaceFeature(faceFeature1, faceFeature2, faceSimilar);
if (errorCode5 != ErrorInfo.MOK.getValue()) {
System.out.println("人脸对比操作失败!");
} else {
System.out.println("人脸对比成功!");
System.out.println("人脸相似度:" + faceSimilar.getScore());
}
}
public FaceFeature getFaceFeature(String imgPath, FaceEngine faceEngine) {
ImageInfo imageInfo = getRGBData(new File(imgPath));
List<FaceInfo> faceInfoList = new ArrayList<>();
int errorCode3 = faceEngine.detectFaces(imageInfo.getImageData(), imageInfo.getWidth(), imageInfo.getHeight(),
imageInfo.getImageFormat(), faceInfoList);
if (errorCode3 != ErrorInfo.MOK.getValue()) {
System.out.println("数据传入失败");
} else {
System.out.println("数据传入成功");
System.out.println(faceInfoList);
}
FaceFeature faceFeature = new FaceFeature();
int errorCode4 = faceEngine.extractFaceFeature(imageInfo.getImageData(),
imageInfo.getWidth(), imageInfo.getHeight(), imageInfo.getImageFormat(),
faceInfoList.get(0), faceFeature);
if (errorCode4 != ErrorInfo.MOK.getValue()) {
System.out.println("人脸特征提取失败!");
} else {
System.out.println("人脸特征提取成功!");
System.out.println("特征值大小:" + faceFeature.getFeatureData().length);
}
return faceFeature;
}
public static void main(String[] args) {
new FaceTestMd().engineTest();
}
}
其余的还有年龄检测,活体检测,性别检测等等,其中在官方文档里面介绍的很清楚,我就不再一一赘述了,直接放上的测试代码和结果
我的测试代码
package top.gostack.demo1;
import com.arcsoft.face.*;
import com.arcsoft.face.enums.DetectMode;
import com.arcsoft.face.enums.DetectOrient;
import com.arcsoft.face.enums.ErrorInfo;
import com.arcsoft.face.toolkit.ImageInfo;
import java.io.File;
import java.util.ArrayList;
import java.util.List;
import static com.arcsoft.face.toolkit.ImageFactory.getRGBData;
public class FaceTest {
public void engineTest() {
String appId = "";
String sdkKey = "";
FaceEngine faceEngine = new FaceEngine();
int errorCode = faceEngine.activeOnline(appId, sdkKey);
if (errorCode != ErrorInfo.MOK.getValue() &&
errorCode != ErrorInfo.MERR_ASF_ALREADY_ACTIVATED.getValue())
{
System.out.println("引擎激活失败:"+errorCode);
} else {
System.out.println("引擎激活成功");
}
EngineConfiguration engineConfiguration = new EngineConfiguration();
engineConfiguration.setDetectMode(DetectMode.ASF_DETECT_MODE_IMAGE);
engineConfiguration.setDetectFaceOrientPriority(DetectOrient.ASF_OP_0_ONLY);
engineConfiguration.setDetectFaceScaleVal(16);
engineConfiguration.setDetectFaceMaxNum(10);
final FunctionConfiguration functionConfiguration = new FunctionConfiguration();
functionConfiguration.setSupportAge(true);
functionConfiguration.setSupportFaceDetect(true);
functionConfiguration.setSupportFaceRecognition(true);
functionConfiguration.setSupportGender(true);
functionConfiguration.setSupportFace3dAngle(true);
functionConfiguration.setSupportLiveness(true);
functionConfiguration.setSupportIRLiveness(false);
engineConfiguration.setFunctionConfiguration(functionConfiguration);
int errorCode2 = faceEngine.init(engineConfiguration);
if (errorCode2 != ErrorInfo.MOK.getValue()) {
System.out.println("初始化引擎失败");
} else {
System.out.println("初始化引擎成功");
}
String imgPath1 = "F:/Spring/SpringMVC/workplace/Ace_Face/resources/wyy1.jpg";
String imgPath2 = "F:/Spring/SpringMVC/workplace/Ace_Face/resources/wyy4.jpg";
FaceFeature faceFeature1 = getFaceFeature(imgPath1, faceEngine);
FaceFeature faceFeature2 = getFaceFeature(imgPath2, faceEngine);
FaceSimilar faceSimilar = new FaceSimilar();
int errorCode5 = faceEngine.compareFaceFeature(faceFeature1, faceFeature2, faceSimilar);
if (errorCode5 != ErrorInfo.MOK.getValue()) {
System.out.println("人脸对比操作失败!");
} else {
System.out.println("人脸对比成功!");
System.out.println("人脸相似度:" + faceSimilar.getScore());
}
int errorCode11 = faceEngine.unInit();
if (errorCode11 != ErrorInfo.MOK.getValue()) {
System.out.println("引擎卸载失败,错误码:");
System.out.println(errorCode);
} else {
System.out.println("引擎卸载成功!");
}
}
public FaceFeature getFaceFeature(String imgPath, FaceEngine faceEngine) {
ImageInfo imageInfo = getRGBData(new File(imgPath));
List<FaceInfo> faceInfoList = new ArrayList<>();
int errorCode3 = faceEngine.detectFaces(imageInfo.getImageData(), imageInfo.getWidth(), imageInfo.getHeight(),
imageInfo.getImageFormat(), faceInfoList);
if (errorCode3 != ErrorInfo.MOK.getValue()) {
System.out.println("数据传入失败");
} else {
System.out.println("数据传入成功");
System.out.println(faceInfoList);
}
FunctionConfiguration functionConfiguration = new FunctionConfiguration();
functionConfiguration.setSupportAge(true);
functionConfiguration.setSupportFace3dAngle(true);
functionConfiguration.setSupportGender(true);
functionConfiguration.setSupportLiveness(true);
faceEngine.process(imageInfo.getImageData(), imageInfo.getWidth(),
imageInfo.getHeight(), imageInfo.getImageFormat(), faceInfoList, functionConfiguration);
int errorCode6 = faceEngine.process(imageInfo.getImageData(), imageInfo.getWidth(),
imageInfo.getHeight(), imageInfo.getImageFormat(), faceInfoList, functionConfiguration);
if (errorCode6 != ErrorInfo.MOK.getValue()) {
System.out.println("process接口调用失败,错误码:"+errorCode6);
} else {
System.out.println("process接口调用成功!");
}
List<AgeInfo> ageInfoList = new ArrayList<>();
int errorCode7 = faceEngine.getAge(ageInfoList);
if (errorCode7 != ErrorInfo.MOK.getValue()) {
System.out.print("获取年龄失败,错误码:");
System.out.println(errorCode7);
} else {
System.out.println("年龄获取成功!");
System.out.println("年龄:" + ageInfoList.get(0).getAge());
}
List<GenderInfo> genderInfoList = new ArrayList<GenderInfo>();
int errorCode8 = faceEngine.getGender(genderInfoList);
if (errorCode8 != ErrorInfo.MOK.getValue()) {
System.out.print("获取性别失败,错误码:");
System.out.println(errorCode8);
} else {
System.out.println("性别获取成功!");
System.out.println("性别:" + genderInfoList.get(0).getGender());
}
List<Face3DAngle> face3DAngleList = new ArrayList<Face3DAngle>();
int errorCode9 = faceEngine.getFace3DAngle(face3DAngleList);
if (errorCode9 != ErrorInfo.MOK.getValue()) {
System.out.println("3D信息检测失败,错误码:"+errorCode9);
} else {
System.out.println("3D信息获取成功!");
System.out.println("3D角度:" + face3DAngleList.get(0).getPitch() + "," +
face3DAngleList.get(0).getRoll() + "," + face3DAngleList.get(0).getYaw());
}
List<LivenessInfo> livenessInfoList = new ArrayList<LivenessInfo>();
int errorCode10 = faceEngine.getLiveness(livenessInfoList);
if (errorCode10 != ErrorInfo.MOK.getValue()) {
System.out.println("活体检测失败,错误码:"+errorCode10);
} else {
System.out.println("活体检测成功");
System.out.println("活体:" + livenessInfoList.get(0).getLiveness());
}
FaceFeature faceFeature = new FaceFeature();
int errorCode4 = faceEngine.extractFaceFeature(imageInfo.getImageData(),
imageInfo.getWidth(), imageInfo.getHeight(), imageInfo.getImageFormat(),
faceInfoList.get(0), faceFeature);
if (errorCode4 != ErrorInfo.MOK.getValue()) {
System.out.println("人脸特征提取失败!");
} else {
System.out.println("人脸特征提取成功!");
System.out.println("特征值大小:" + faceFeature.getFeatureData().length);
}
return faceFeature;
}
public static void main(String[] args) {
new FaceTest().engineTest();
}
}
运行结果:
引擎激活成功
初始化引擎成功
数据传入成功
[com.arcsoft.face.Rect(332, 152 - 924, 744),1]
process接口调用成功!
年龄获取成功!
年龄:21
性别获取成功!
性别:1
3D信息获取成功!
3D角度:-15.243982,21.721786,16.343493
活体检测成功
活体:1
人脸特征提取成功!
特征值大小:1032
数据传入成功
[com.arcsoft.face.Rect(345, 163 - 942, 760),1]
process接口调用成功!
年龄获取成功!
年龄:20
性别获取成功!
性别:1
3D信息获取成功!
3D角度:-11.13369,0.69471675,17.24398
活体检测成功
活体:1
人脸特征提取成功!
特征值大小:1032
人脸对比成功!
人脸相似度:0.9812902
引擎卸载成功!
最后注意,要学习这个SDK一定去看官方文档,写的很详细!
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