修改为openvivn

ruoyi-video/src/main/java/com/ruoyi/video/thread/detector/OpenVinoYoloDetector.java

@@ -5,21 +5,14 @@ import org.bytedeco.javacpp.indexer.FloatRawIndexer;
 import org.bytedeco.opencv.opencv_core.*;
 import org.bytedeco.opencv.opencv_dnn.Net;
 
-import java.nio.file.Files;
-import java.nio.file.Path;
-import java.util.ArrayList;
-import java.util.Collections;
-import java.util.List;
+import java.nio.file.*;
+import java.util.*;
 
-import static org.bytedeco.opencv.global.opencv_core.*;
-import static org.bytedeco.opencv.global.opencv_dnn.*;
-import static org.bytedeco.opencv.global.opencv_imgproc.*;
+import static org.bytedeco.opencv.global.opencv_dnn.*;   // DNN API（readNetFromModelOptimizer / blobFromImage 等）
+import static org.bytedeco.opencv.global.opencv_core.*;  // Mat/Size/Scalar/transpose 等
+import static org.bytedeco.opencv.global.opencv_imgproc.*; // cvtColor 等
 
-/**
- * 纯 OpenCV CPU 后端的 YOLO IR 检测器（.xml/.bin）
- * 与原 OpenVinoYoloDetector 代码保持一致，只是固定：DNN_BACKEND_OPENCV + DNN_TARGET_CPU。
- */
-public final class OpenCvYoloDetector implements YoloDetector {
+public final class OpenVinoYoloDetector implements YoloDetector {
     private final String modelName;
     private final Net net;
     private final Size input;
@@ -27,15 +20,7 @@ public final class OpenCvYoloDetector implements YoloDetector {
     private final String[] classes;
     private final int colorBGR;
 
-    /**
-     * @param name    模型别名
-     * @param dir     模型目录（含 model.xml / model.bin / classes.txt）
-     * @param inW     推理输入宽
-     * @param inH     推理输入高
-     * @param backend 兼容参数，忽略（统一使用 OpenCV CPU）
-     * @param colorBGR 画框颜色（BGR packed int）
-     */
-    public OpenCvYoloDetector(String name, Path dir, int inW, int inH, String backend, int colorBGR) throws Exception {
+    public OpenVinoYoloDetector(String name, Path dir, int inW, int inH, String backend, int colorBGR) throws Exception {
         this.modelName = name;
         this.input = new Size(inW, inH);
         this.colorBGR = colorBGR;
@@ -45,18 +30,26 @@ public final class OpenCvYoloDetector implements YoloDetector {
 
         Path clsPath = dir.resolve("classes.txt");
         if (Files.exists(clsPath)) {
-            this.classes = Files.readAllLines(clsPath).stream()
-                    .map(String::trim).filter(s -> !s.isEmpty())
-                    .toArray(String[]::new);
+            this.classes = Files.readAllLines(clsPath).stream().map(String::trim)
+                    .filter(s -> !s.isEmpty()).toArray(String[]::new);
         } else {
             this.classes = new String[0];
         }
 
         this.net = readNetFromModelOptimizer(xml, bin);
 
-        // ✅ 固定使用 OpenCV CPU 后端（不再尝试 OpenVINO）
-        net.setPreferableBackend(DNN_BACKEND_OPENCV);
-        net.setPreferableTarget(DNN_TARGET_CPU);
+        boolean set = false;
+        if ("openvino".equalsIgnoreCase(backend)) {
+            try {
+                net.setPreferableBackend(DNN_BACKEND_INFERENCE_ENGINE);
+                net.setPreferableTarget(DNN_TARGET_CPU);
+                set = true;
+            } catch (Throwable ignore) { /* 回退 */ }
+        }
+        if (!set) {
+            net.setPreferableBackend(DNN_BACKEND_OPENCV);
+            net.setPreferableTarget(DNN_TARGET_CPU);
+        }
     }
 
     @Override public String name() { return modelName; }
@@ -65,7 +58,7 @@ public final class OpenCvYoloDetector implements YoloDetector {
     public List<Detection> detect(Mat bgr) {
         if (bgr == null || bgr.empty()) return Collections.emptyList();
 
-        // 保证 BGR 3通道
+        // 统一成 BGR 3 通道，避免 blobFromImage 断言失败
         if (bgr.channels() != 3) {
             Mat tmp = new Mat();
             if (bgr.channels() == 1) cvtColor(bgr, tmp, COLOR_GRAY2BGR);
@@ -76,19 +69,23 @@ public final class OpenCvYoloDetector implements YoloDetector {
 
         try (Mat blob = blobFromImage(bgr, 1.0/255.0, input, new Scalar(0.0), true, false, CV_32F)) {
             net.setInput(blob);
-
-            // 兼容单/多输出
+            // ===== 多输出兼容（Bytedeco 正确写法）=====
             org.bytedeco.opencv.opencv_core.StringVector outNames = net.getUnconnectedOutLayersNames();
             List<Mat> outs = new ArrayList<>();
 
             if (outNames == null || outNames.size() == 0) {
-                Mat out = net.forward();
+                // 只有一个默认输出
+                Mat out = net.forward();      // ← 直接返回 Mat
                 outs.add(out);
             } else {
+                // 多输出：用 MatVector 承接
                 org.bytedeco.opencv.opencv_core.MatVector outBlobs =
                         new org.bytedeco.opencv.opencv_core.MatVector(outNames.size());
-                net.forward(outBlobs, outNames);
-                for (long i = 0; i < outBlobs.size(); i++) outs.add(outBlobs.get(i));
+                net.forward(outBlobs, outNames);   // ← 正确的重载
+
+                for (long i = 0; i < outBlobs.size(); i++) {
+                    outs.add(outBlobs.get(i));
+                }
             }
 
             int fw = bgr.cols(), fh = bgr.rows();
@@ -101,6 +98,7 @@ public final class OpenCvYoloDetector implements YoloDetector {
             }
             if (boxes.isEmpty()) return Collections.emptyList();
 
+            // 纯 Java NMS，避免 MatOf* / Vector API 兼容问题
             List<Integer> keep = nmsIndices(boxes, scores, nmsTh);
 
             List<Detection> result = new ArrayList<>(keep.size());
@@ -113,6 +111,7 @@ public final class OpenCvYoloDetector implements YoloDetector {
             }
             return result;
         } catch (Throwable e) {
+            // 单帧失败不影响整体
             return Collections.emptyList();
         }
     }
@@ -124,6 +123,7 @@ public final class OpenCvYoloDetector implements YoloDetector {
         Mat m;
 
         if (dims == 2) {
+            // NxC 或 CxN
             if (out.cols() >= 6) {
                 m = out;
             } else {
@@ -132,6 +132,7 @@ public final class OpenCvYoloDetector implements YoloDetector {
                 m = tmp;
             }
         } else if (dims == 3) {
+            // [1,N,C] 或 [1,C,N]
             if (out.size(2) >= 6) {
                 m = out.reshape(1, out.size(1)); // -> N×C
             } else {
@@ -141,6 +142,7 @@ public final class OpenCvYoloDetector implements YoloDetector {
                 m = tmp;
             }
         } else if (dims == 4) {
+            // [1,1,N,C] 或 [1,1,C,N]
             int a = out.size(2), b = out.size(3);
             if (b >= 6) {
                 m = out.reshape(1, a).clone(); // -> N×C
@@ -151,7 +153,7 @@ public final class OpenCvYoloDetector implements YoloDetector {
                 m = tmp.clone();
             }
         } else {
-            return;
+            return; // 不支持的形状
         }
 
         int N = m.rows(), C = m.cols();
@@ -170,7 +172,7 @@ public final class OpenCvYoloDetector implements YoloDetector {
             float conf = obj * bestScore;
             if (conf < confTh) continue;
 
-            // 假定 (cx,cy,w,h) 为归一化中心点格式；如是 x1,y1,x2,y2，请按需改这里
+            // 默认假设归一化中心点格式 (cx,cy,w,h)；若你的 IR 是 x1,y1,x2,y2，请把这里换算改掉
             int bx = Math.max(0, Math.round(cx * fw - (w * fw) / 2f));
             int by = Math.max(0, Math.round(cy * fh - (h * fh) / 2f));
             int bw = Math.min(fw - bx, Math.round(w * fw));
@@ -187,6 +189,7 @@ public final class OpenCvYoloDetector implements YoloDetector {
     private List<Integer> nmsIndices(List<Rect2d> boxes, List<Float> scores, float nmsThreshold) {
         List<Integer> order = new ArrayList<>(boxes.size());
         for (int i = 0; i < boxes.size(); i++) order.add(i);
+        // 按分数降序
         order.sort((i, j) -> Float.compare(scores.get(j), scores.get(i)));
 
         List<Integer> keep = new ArrayList<>();
@@ -224,4 +227,4 @@ public final class OpenCvYoloDetector implements YoloDetector {
     }
 
     @Override public void close(){ net.close(); }
-}
+}