update: 1024维的模型

face-search-core/src/main/java/com/visual/face/search/core/models/SeetaFaceOpenRecognition.java

@@ -8,8 +8,11 @@ import com.visual.face.search.core.domain.FaceInfo.Embedding;
 import com.visual.face.search.core.domain.ImageMat;
 import com.visual.face.search.core.utils.ArrayUtil;
 import org.opencv.core.Scalar;
+
+import java.util.Arrays;
 import java.util.Collections;
 import java.util.Map;
+import java.util.stream.Collectors;
 
 /**
  * 人脸识别-人脸特征提取
@@ -33,6 +36,19 @@ public class SeetaFaceOpenRecognition extends BaseOnnxInfer implements FaceRecog
      */
     @Override
     public Embedding inference(ImageMat image, Map<String, Object> params) {
+        if("light".equals(params.get("model"))){
+            return inferenceLight(image, params);
+        }else{
+            return inferenceLarge(image, params);
+        }
+    }
+
+    /**
+     * 人脸识别，人脸特征向量-512维
+     * @param image 图像信息
+     * @return
+     */
+    private Embedding inferenceLight(ImageMat image, Map<String, Object> params) {
         OnnxTensor tensor = null;
         OrtSession.Result output = null;
         try {
@@ -56,4 +72,38 @@ public class SeetaFaceOpenRecognition extends BaseOnnxInfer implements FaceRecog
         }
     }
 
+
+    /**
+     * 人脸识别，人脸特征向量-1024维
+     * @param image 图像信息
+     * @return
+     */
+    public Embedding inferenceLarge(ImageMat image, Map<String, Object> params) {
+        OnnxTensor tensor = null;
+        OrtSession.Result output = null;
+        try {
+            tensor = image.resizeAndNoReleaseMat(248,248)
+                    .blobFromImageAndDoReleaseMat(1.0, new Scalar(0, 0, 0), true)
+                    .to4dFloatOnnxTensorAndDoReleaseMat(true);
+            output = getSession().run(Collections.singletonMap(getInputName(), tensor));
+            float[][][] predictions = ((float[][][][]) output.get(0).getValue())[0];
+            float[] embeds = new float[predictions.length];
+            for(int i=0; i< embeds.length; i++){
+                embeds[i] = Double.valueOf(Math.sqrt(predictions[i][0][0])).floatValue();
+            }
+            double normValue = ArrayUtil.matrixNorm(embeds);
+            float[] embedding = ArrayUtil.division(embeds, Double.valueOf(normValue).floatValue());
+            return Embedding.build(image.toBase64AndNoReleaseMat(), embedding);
+        } catch (Exception e) {
+            throw new RuntimeException(e);
+        }finally {
+            if(null != tensor){
+                tensor.close();
+            }
+            if(null != output){
+                output.close();
+            }
+        }
+    }
+
 }

face-search-core/src/test/java/com/visual/face/search/core/test/models/SeetaFaceOpenRecognitionTest.java

@@ -20,33 +20,36 @@ import java.util.Map;
 
 public class SeetaFaceOpenRecognitionTest extends BaseTest {
     private static String modelCoordPath = "face-search-core/src/main/resources/model/onnx/keypoint_coordinate/coordinate_106_mobilenet_05.onnx";
-    private static String modelSeetaPath = "face-search-core/src/main/resources/model/onnx/recognition_fcae_seeta/face_recognizer_512.onnx";
+//    private static String modelSeetaPath = "face-search-core/src/main/resources/model/onnx/recognition_face_seeta/face_recognizer_512.onnx";
-//    private static String modelSeetaPath = "face-search-core/src/main/resources/model/onnx/recognition_fcae_seeta/face_recognizer_1024.onnx";
+    private static String modelSeetaPath = "face-search-core/src/main/resources/model/onnx/recognition_face_seeta/face_recognizer_1024.onnx";
 
     private static String imagePath = "face-search-core/src/test/resources/images/faces";
 //    private static String imagePath1 = "face-search-core/src/test/resources/images/faces/debug/debug_0001.jpg";
 //    private static String imagePath2 = "face-search-core/src/test/resources/images/faces/debug/debug_0004.jpeg";
     private static String imagePath1 = "face-search-core/src/test/resources/images/faces/compare/1682052661610.jpg";
-    private static String imagePath2 = "face-search-core/src/test/resources/images/faces/compare/1682052669004.jpg";
+//    private static String imagePath2 = "face-search-core/src/test/resources/images/faces/compare/1682052669004.jpg";
-//    private static String imagePath2 = "face-search-core/src/test/resources/images/faces/compare/1682053163961.jpg";
+    private static String imagePath2 = "face-search-core/src/test/resources/images/faces/compare/1682053163961.jpg";
 
     public static void main(String[] args) {
+        Map<String, Object> params = new HashMap<>();
+        params.put("model", "light1");
         FaceAlignment simple005pFaceAlignment = new Simple005pFaceAlignment();
         FaceKeyPoint insightCoordFaceKeyPoint = new InsightCoordFaceKeyPoint(modelCoordPath, 1);
         FaceRecognition insightSeetaFaceRecognition = new SeetaFaceOpenRecognition(modelSeetaPath, 1);
 
         Mat image1 = Imgcodecs.imread(imagePath1);
-        Mat image2 = Imgcodecs.imread(imagePath2);
+//        Mat image2 = Imgcodecs.imread(imagePath2);
 //        image1 = CropUtil.crop(image1, FaceInfo.FaceBox.build(54,27,310,380));
 //        image2 = CropUtil.crop(image2, FaceInfo.FaceBox.build(48,13,292,333));
 //        image2 = CropUtil.crop(image2, FaceInfo.FaceBox.build(52,9,235,263));
 
 //        simple005pFaceAlignment.inference()
 
-        FaceInfo.Embedding embedding1 = insightSeetaFaceRecognition.inference(ImageMat.fromCVMat(image1), null);
+        FaceInfo.Embedding embedding1 = insightSeetaFaceRecognition.inference(ImageMat.fromCVMat(image1), params);
-        FaceInfo.Embedding embedding2 = insightSeetaFaceRecognition.inference(ImageMat.fromCVMat(image2), null);
+        System.out.println(Arrays.toString(embedding1.embeds));
-        float similarity = Similarity.cosineSimilarity(embedding1.embeds, embedding2.embeds);
+//        FaceInfo.Embedding embedding2 = insightSeetaFaceRecognition.inference(ImageMat.fromCVMat(image2), params);
-        System.out.println(similarity);
+//        float similarity = Similarity.cosineSimilarity(embedding1.embeds, embedding2.embeds);
+//        System.out.println(similarity);
 //        System.out.println(Arrays.toString(embedding1.embeds));
 //        System.out.println(Arrays.toString(embedding2.embeds));
     }