From d6880498f960fb17d4d3564713400969281d9f6b Mon Sep 17 00:00:00 2001
From: haotian <2421912570@qq.com>
Date: Sat, 28 Feb 2026 14:44:06 +0800
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---
 configs/sample_cam_ppe11.json              |   3 +-
 docs/models.md                             |  57 +++++++--------------
 models/{best-rk3588.rknn => best-768.rknn} | Bin
 plugins/ai_yolo/ai_yolo_node.cpp           |   7 +--
 4 files changed, 25 insertions(+), 42 deletions(-)
 rename models/{best-rk3588.rknn => best-768.rknn} (100%)

diff --git a/configs/sample_cam_ppe11.json b/configs/sample_cam_ppe11.json
index 82f6418..7237b74 100644
--- a/configs/sample_cam_ppe11.json
+++ b/configs/sample_cam_ppe11.json
@@ -52,7 +52,8 @@
             "stats": true,
             "stats_interval": 30,
             "detections": true
-          }
+          },
+          "class_filter": [3, 6]
         },
         {
           "id": "face_det_cam1",
diff --git a/docs/models.md b/docs/models.md
index eb4bda8..468d80f 100644
--- a/docs/models.md
+++ b/docs/models.md
@@ -6,8 +6,7 @@
 
 ```
 models/
-├── best-640.rknn                  # YOLO 通用检测模型 (3类)
-├── best-768.rknn                  # YOLO PPE检测模型 (11类)
+├── best-768.rknn                  # YOLO PPE检测模型 (11类，实际使用2类)
 ├── yolov5s-640-640.rknn           # YOLOv5 COCO预训练模型 (80类)
 ├── yolov8n-640.rknn               # YOLOv8n COCO预训练模型 (80类)
 ├── RetinaFace_mobile320.rknn      # 人脸检测模型
@@ -17,38 +16,12 @@ models/
 
 ## 模型详情
 
-### 1. best-640.rknn
-
-**类型**: YOLOv8 目标检测  
-**输入尺寸**: 640x640  
-**类别数**: 3  
-
-| 索引 | 类别名 | 说明 |
-|------|--------|------|
-| 0 | person | 人 |
-| 1 | vest | 反光背心 |
-| 2 | boots | 安全靴 |
-
-**配置示例**:
-```json
-{
-  "type": "ai_yolo",
-  "model_path": "./models/best-640.rknn",
-  "model_version": "v8",
-  "num_classes": 3,
-  "conf": 0.35,
-  "nms": 0.45
-}
-```
-
----
-
-### 2. best-768.rknn (PPE11)
+### 1. best-768.rknn (PPE11)
 
 **类型**: YOLOv8 PPE检测模型  
 **输入尺寸**: 768x768  
 **类别数**: 11  
-**模型名**: ppe11_person_boots_boost
+**实际使用类别**: 2 (boots + Person)
 
 | 索引 | 类别名 | 业务使用 | 说明 |
 |------|--------|----------|------|
@@ -75,7 +48,7 @@ models/
   "model_w": 768,
   "model_h": 768,
   "num_classes": 11,
-  "conf": 0.35,
+  "conf": 0.2,
   "nms": 0.45,
   "class_filter": [3, 6]
 }
@@ -89,9 +62,18 @@ models/
 }
 ```
 
+**Tracker配置**:
+```json
+{
+  "type": "tracker",
+  "track_classes": [3, 6],
+  "per_class": true
+}
+```
+
 ---
 
-### 3. yolov5s-640-640.rknn
+### 2. yolov5s-640-640.rknn
 
 **类型**: YOLOv5s COCO预训练模型  
 **输入尺寸**: 640x640  
@@ -113,7 +95,7 @@ models/
 
 ---
 
-### 4. yolov8n-640.rknn
+### 3. yolov8n-640.rknn
 
 **类型**: YOLOv8n COCO预训练模型  
 **输入尺寸**: 640x640  
@@ -135,7 +117,7 @@ models/
 
 ---
 
-### 5. RetinaFace_mobile320.rknn
+### 4. RetinaFace_mobile320.rknn
 
 **类型**: RetinaFace 人脸检测  
 **输入尺寸**: 320x320  
@@ -155,7 +137,7 @@ models/
 
 ---
 
-### 6. mobilefacenet_arcface.rknn
+### 5. mobilefacenet_arcface.rknn
 
 **类型**: MobileFaceNet + ArcFace 人脸识别  
 **输入尺寸**: 112x112  
@@ -186,8 +168,7 @@ models/
 | 场景 | 推荐模型 | 说明 |
 |------|----------|------|
 | 通用目标检测 | yolov8n-640.rknn | 80类COCO，通用性强 |
-| 工地安全检测 | best-640.rknn | 人/背心/安全靴 |
-| PPE完整检测 | best-768.rknn | 11类PPE，含正反例 |
+| 工地安全检测 (人+靴) | best-768.rknn | 11类PPE，只使用3(boots)+6(Person) |
 | 人脸检测+识别 | RetinaFace + MobileFaceNet | 人脸识别链路 |
 
 ## 注意事项
@@ -195,4 +176,4 @@ models/
 1. **模型尺寸匹配**: `preprocess` 节点的 `dst_w/dst_h` 必须与模型输入尺寸一致
 2. **num_classes**: 必须与模型实际类别数一致，否则后处理会出错
 3. **class_filter**: 用于过滤只关心的类别，减少后续处理负载
-4. **best-768.rknn**: 只消费类别 3(boots) 和 6(Person)，其他类别可忽略
+4. **best-768.rknn**: 只消费类别 3(boots) 和 6(Person)，其他类别在 class_filter 中已过滤
diff --git a/models/best-rk3588.rknn b/models/best-768.rknn
similarity index 100%
rename from models/best-rk3588.rknn
rename to models/best-768.rknn
diff --git a/plugins/ai_yolo/ai_yolo_node.cpp b/plugins/ai_yolo/ai_yolo_node.cpp
index 47c9e9c..e1fa69a 100644
--- a/plugins/ai_yolo/ai_yolo_node.cpp
+++ b/plugins/ai_yolo/ai_yolo_node.cpp
@@ -432,9 +432,10 @@ public:
         PushToDownstream(frame);
         ++processed_;
 
-        if (stats_log_ && stats_interval_ > 0 && (processed_ % stats_interval_) == 0) {
-            LogInfo("[ai_yolo] processed=" + std::to_string(processed_) + " id=" + id_);
-        }
+        // Stats log disabled to reduce log spam
+        // if (stats_log_ && stats_interval_ > 0 && (processed_ % stats_interval_) == 0) {
+        //     LogInfo("[ai_yolo] processed=" + std::to_string(processed_) + " id=" + id_);
+        // }
         return NodeStatus::OK;
     }