✨ feat: 增加设备名称

- 在 Device 实体类中新增 deviceName 字段及其 getter/setter 方法
- 更新 DeviceMapper.xml，支持 device_name 字段的查询、插入和更新操作
- 修改 InspectionTask 实体类，增加 deviceIp 字段用于联查返回设备 IP
- 调整 InspectionTaskMapper.xml，通过左连接获取设备名称与 IP 信息- 移除冗余的 device_name 插入与更新逻辑
- 注释掉旧有的设备信息设置代码，避免重复赋值
- 更新 toString 方法以包含新的 deviceName 属性

python-inference-service/app/detector.py

@@ -12,7 +12,7 @@ from app.models import Detection
 class PythonModelDetector:
     """Object detector using native Python models"""
     
-    def __init__(self, model_name: str, model_path: str, input_width: int, input_height: int, color: int = 0x00FF00):
+    def __init__(self, model_name: str, model_path: str, input_width: int, input_height: int, color: int = 0x00FF00, model_config: dict = None):
         """
         Initialize detector with Python model
         
@@ -22,11 +22,13 @@ class PythonModelDetector:
             input_width: Input width for the model
             input_height: Input height for the model
             color: RGB color for detection boxes (default: green)
+            model_config: Additional configuration to pass to the model
         """
         self.model_name = model_name
         self.input_width = input_width
         self.input_height = input_height
         self.color = color
+        self.model_config = model_config or {}
         
         # Convert color from RGB to BGR (OpenCV uses BGR)
         self.color_bgr = ((color & 0xFF) << 16) | (color & 0xFF00) | ((color >> 16) & 0xFF)
@@ -72,8 +74,18 @@ class PythonModelDetector:
         if not hasattr(model_module, "Model"):
             raise AttributeError(f"Model module must define a 'Model' class: {model_path}")
         
-        # Create model instance
-        self.model = model_module.Model()
+        # Create model instance with config
+        # Try to pass config to model constructor if it accepts parameters
+        import inspect
+        model_class = model_module.Model
+        sig = inspect.signature(model_class.__init__)
+        
+        if len(sig.parameters) > 1:  # Has parameters beyond 'self'
+            # Pass all config as keyword arguments
+            self.model = model_class(**self.model_config)
+        else:
+            # No parameters, create without arguments
+            self.model = model_class()
         
         # Check if model has the required methods
         if not hasattr(self.model, "predict"):
@@ -113,18 +125,16 @@ class PythonModelDetector:
         # Original image dimensions
         img_height, img_width = img.shape[:2]
         
-        # Preprocess image
-        processed_img = self.preprocess(img)
-        
         # Measure inference time
         start_time = time.time()
         
         try:
             # Run inference using model's predict method
+            # Note: Pass original image to model, let it handle preprocessing
             # Expected return format from model's predict:
             # List of dicts with keys: 'bbox', 'class_id', 'confidence'
             # bbox: (x, y, w, h) normalized [0-1]
-            model_results = self.model.predict(processed_img)
+            model_results = self.model.predict(img)
             
             # Calculate inference time in milliseconds
             inference_time = (time.time() - start_time) * 1000
@@ -279,13 +289,22 @@ class ModelManager:
                 # Use color from palette
                 color = palette[i % len(palette)]
                 
+                # Extract model-specific config (model_file, model_name, etc.)
+                # These will be passed to the Model class __init__
+                model_init_config = {}
+                if "model_file" in model_config:
+                    model_init_config["model_file"] = model_config["model_file"]
+                if "display_name" in model_config:
+                    model_init_config["model_name"] = model_config["display_name"]
+                
                 # Create detector for Python model
                 detector = PythonModelDetector(
                     model_name=name,
                     model_path=path,
                     input_width=size[0],
                     input_height=size[1],
-                    color=color
+                    color=color,
+                    model_config=model_init_config
                 )
                 
                 self.models[name] = detector

python-inference-service/app/main.py

@@ -37,7 +37,7 @@ async def startup_event():
     model_manager = ModelManager()
     
     # Look for models.json configuration file
-    models_json_path = os.getenv("MODELS_JSON", os.path.join(os.path.dirname(__file__), "..", "models", "models.json"))
+    models_json_path = os.getenv("MODELS_JSON", os.path.join(os.path.dirname(__file__), "..", "models.json"))
     
     if os.path.exists(models_json_path):
         try:
@@ -130,8 +130,12 @@ async def detect_file(
     file: UploadFile = File(...)
 ):
     """Detect objects in an uploaded image file"""
-    global model_manager
+    print(f"接收到的 model_name: {model_name}")
+    print(f"文件名: {file.filename}")
+    print(f"文件内容类型: {file.content_type}")
     
+    global model_manager
+
     if not model_manager:
         raise HTTPException(status_code=500, detail="Model manager not initialized")
     
@@ -143,16 +147,39 @@ async def detect_file(
     # Read uploaded file
     try:
         contents = await file.read()
+        print(f"文件大小: {len(contents)} 字节")
+        
+        if len(contents) == 0:
+            raise HTTPException(status_code=400, detail="Empty file")
+        
         nparr = np.frombuffer(contents, np.uint8)
+        print(f"numpy数组形状: {nparr.shape}, dtype: {nparr.dtype}")
+        
         image = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
         
         if image is None:
-            raise HTTPException(status_code=400, detail="Invalid image data")
+            print("错误: cv2.imdecode 返回 None")
+            raise HTTPException(status_code=400, detail="Invalid image data - failed to decode")
+        
+        print(f"解码后图像形状: {image.shape}, dtype: {image.dtype}")
+        
+    except HTTPException:
+        raise
     except Exception as e:
+        print(f"处理图像时出错: {str(e)}")
+        import traceback
+        traceback.print_exc()
         raise HTTPException(status_code=400, detail=f"Failed to process image: {str(e)}")
     
     # Run detection
-    detections, inference_time = detector.detect(image)
+    try:
+        detections, inference_time = detector.detect(image)
+        print(f"检测完成: 找到 {len(detections)} 个目标, 耗时 {inference_time:.2f}ms")
+    except Exception as e:
+        print(f"推理过程中出错: {str(e)}")
+        import traceback
+        traceback.print_exc()
+        raise HTTPException(status_code=500, detail=f"Detection failed: {str(e)}")
     
     return DetectionResponse(
         model_name=model_name,

python-inference-service/models.json

@@ -0,0 +1,18 @@
+[
+  {
+    "name": "smoke",
+    "path": "models/universal_yolo_model.py",
+    "model_file": "smoke.pt",
+    "display_name": "吸烟检测",
+    "size": [640, 640],
+    "comment": "吸烟检测模型 - YOLOv11"
+  },
+  {
+    "name": "garbage",
+    "path": "models/universal_yolo_model.py",
+    "model_file": "garbage.pt",
+    "display_name": "垃圾识别",
+    "size": [640, 640],
+    "comment": "垃圾检测模型 - YOLOv8"
+  }
+] 

python-inference-service/models/garbage_model.py

@@ -1,207 +0,0 @@
-import os
-import numpy as np
-import cv2
-from typing import List, Dict, Any
-import torch
-
-class Model:
-    """
-    垃圾识别模型 - 直接加载 PyTorch 模型文件
-    """
-    
-    def __init__(self):
-        """初始化模型"""
-        # 获取当前文件所在目录路径
-        model_dir = os.path.dirname(os.path.abspath(__file__))
-        # 模型文件路径
-        model_path = os.path.join(model_dir, "best.pt")
-        
-        print(f"正在加载垃圾识别模型: {model_path}")
-        
-        # 加载 PyTorch 模型
-        self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-        print(f"使用设备: {self.device}")
-        
-        # 使用 YOLOv5 或通用方式加载模型
-        try:
-            # 尝试使用 YOLOv5 加载
-            import sys
-            sys.path.append(os.path.dirname(model_dir))  # 添加父目录到路径
-            
-            try:
-                # 方法1: 如果安装了 YOLOv5
-                import yolov5
-                self.model = yolov5.load(model_path, device=self.device)
-                self.yolov5_api = True
-                print("使用 YOLOv5 包加载模型")
-            except (ImportError, ModuleNotFoundError):
-                # 方法2: 直接加载 YOLO 代码
-                from models.yolov5_utils import attempt_load
-                self.model = attempt_load(model_path, device=self.device)
-                self.yolov5_api = False
-                print("使用内置 YOLOv5 工具加载模型")
-                
-        except Exception as e:
-            # 方法3: 通用 PyTorch 加载
-            print(f"YOLOv5 加载失败: {e}")
-            print("使用通用 PyTorch 加载")
-            self.model = torch.load(model_path, map_location=self.device)
-            if isinstance(self.model, dict) and 'model' in self.model:
-                self.model = self.model['model']
-            self.yolov5_api = False
-            
-            # 如果是 ScriptModule，设置为评估模式
-            if isinstance(self.model, torch.jit.ScriptModule):
-                self.model.eval()
-            elif hasattr(self.model, 'eval'):
-                self.model.eval()
-                
-        # 加载类别名称
-        self.classes = []
-        classes_path = os.path.join(model_dir, "classes.txt")
-        if os.path.exists(classes_path):
-            with open(classes_path, 'r', encoding='utf-8') as f:
-                self.classes = [line.strip() for line in f.readlines() if line.strip()]
-            print(f"已加载 {len(self.classes)} 个类别")
-        else:
-            # 如果模型自带类别信息
-            if hasattr(self.model, 'names') and self.model.names:
-                self.classes = self.model.names
-                print(f"使用模型自带类别，共 {len(self.classes)} 个类别")
-            else:
-                print("未找到类别文件，将使用数字索引作为类别名")
-        
-        # 设置识别参数
-        self.conf_threshold = 0.25  # 置信度阈值
-        self.img_size = 640        # 默认输入图像大小
-        
-        print("垃圾识别模型加载完成")
-    
-    def preprocess(self, image: np.ndarray) -> np.ndarray:
-        """预处理图像"""
-        # 如果是使用 YOLOv5 API，不需要预处理
-        if hasattr(self, 'yolov5_api') and self.yolov5_api:
-            return image
-            
-        # 默认预处理：调整大小并归一化
-        img = cv2.resize(image, (self.img_size, self.img_size))
-        
-        # BGR 转 RGB
-        img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
-        
-        # 归一化 [0, 255] -> [0, 1]
-        img = img / 255.0
-        
-        # HWC -> CHW (高度，宽度，通道 -> 通道，高度，宽度)
-        img = img.transpose(2, 0, 1)
-        
-        # 转为 torch tensor
-        img = torch.from_numpy(img).float()
-        
-        # 添加批次维度
-        img = img.unsqueeze(0)
-        
-        # 移至设备
-        img = img.to(self.device)
-        
-        return img
-    
-    def predict(self, image: np.ndarray) -> List[Dict[str, Any]]:
-        """模型推理"""
-        original_height, original_width = image.shape[:2]
-        
-        try:
-            # 如果使用 YOLOv5 API
-            if hasattr(self, 'yolov5_api') and self.yolov5_api:
-                # YOLOv5 API 直接处理图像
-                results = self.model(image)
-                
-                # 提取检测结果
-                predictions = results.pred[0]  # 第一批次的预测
-                
-                detections = []
-                for *xyxy, conf, cls_id in predictions.cpu().numpy():
-                    x1, y1, x2, y2 = xyxy
-                    
-                    # 转换为归一化坐标 (x, y, w, h)
-                    x = x1 / original_width
-                    y = y1 / original_height
-                    w = (x2 - x1) / original_width
-                    h = (y2 - y1) / original_height
-                    
-                    # 整数类别 ID
-                    cls_id = int(cls_id)
-                    
-                    # 获取类别名称
-                    class_name = f"cls{cls_id}"
-                    if 0 <= cls_id < len(self.classes):
-                        class_name = self.classes[cls_id]
-                    
-                    # 添加检测结果
-                    if conf >= self.conf_threshold:
-                        detections.append({
-                            'bbox': (x, y, w, h),
-                            'class_id': cls_id,
-                            'confidence': float(conf)
-                        })
-                        
-                return detections
-                
-            else:
-                # 通用 PyTorch 模型处理
-                # 预处理图像
-                img = self.preprocess(image)
-                
-                # 推理
-                with torch.no_grad():
-                    outputs = self.model(img)
-                
-                # 后处理结果（这里需要根据模型输出格式调整）
-                detections = []
-                
-                # 假设输出格式是 YOLO 风格：[batch_idx, x1, y1, x2, y2, conf, cls_id]
-                if isinstance(outputs, torch.Tensor) and outputs.dim() == 2 and outputs.size(1) >= 6:
-                    for *xyxy, conf, cls_id in outputs.cpu().numpy():
-                        if conf >= self.conf_threshold:
-                            x1, y1, x2, y2 = xyxy
-                            
-                            # 转换为归一化坐标 (x, y, w, h)
-                            x = x1 / original_width
-                            y = y1 / original_height
-                            w = (x2 - x1) / original_width
-                            h = (y2 - y1) / original_height
-                            
-                            # 整数类别 ID
-                            cls_id = int(cls_id)
-                            
-                            detections.append({
-                                'bbox': (x, y, w, h),
-                                'class_id': cls_id,
-                                'confidence': float(conf)
-                            })
-                # 处理其他可能的输出格式
-                else:
-                    # 这里需要根据模型的实际输出格式进行适配
-                    print("警告：无法识别的模型输出格式，请检查模型类型")
-                    
-                return detections
-                
-        except Exception as e:
-            print(f"推理过程中出错: {str(e)}")
-            # 出错时返回空结果
-            return []
-    
-    @property
-    def applies_nms(self) -> bool:
-        """模型是否内部应用了 NMS"""
-        # YOLOv5 会自动应用 NMS
-        return True
-    
-    def close(self):
-        """释放资源"""
-        if hasattr(self, 'model'):
-            # 删除模型以释放 GPU 内存
-            del self.model
-            if torch.cuda.is_available():
-                torch.cuda.empty_cache()
-        print("垃圾识别模型已关闭") 

python-inference-service/models/models.json

@@ -1,8 +0,0 @@
-[
-  {
-    "name": "yolov8_detector",
-    "path": "models/yolov8_model.py",
-    "size": [640, 640],
-    "comment": "YOLOv8检测模型，确保将训练好的best.pt文件放在models目录下"
-  }
-] 

python-inference-service/models/smoke.txt

@@ -0,0 +1 @@
+垃圾

python-inference-service/models/smoke_detector.py

@@ -1,126 +0,0 @@
-import numpy as np
-import cv2
-from typing import List, Dict, Any, Tuple
-
-class Model:
-    """
-    Smoke detection model implementation
-    
-    This is a simple example that could be replaced with an actual
-    TensorFlow, PyTorch, or other ML framework implementation.
-    """
-    
-    def __init__(self):
-        """Initialize smoke detection model"""
-        # In a real implementation, you would load your model here
-        print("Smoke detection model initialized")
-        
-        # Define smoke class IDs
-        self.smoke_classes = {
-            0: "smoke",
-            1: "fire"
-        }
-    
-    def preprocess(self, image: np.ndarray) -> np.ndarray:
-        """Preprocess image for model input"""
-        # Convert BGR to grayscale for smoke detection
-        gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
-        # Convert back to 3 channels to match model expected input shape
-        gray_3ch = cv2.cvtColor(gray, cv2.COLOR_GRAY2BGR)
-        
-        # In a real implementation, you would do normalization, etc.
-        return gray_3ch
-    
-    def predict(self, image: np.ndarray) -> List[Dict[str, Any]]:
-        """
-        Run smoke detection on the image
-        
-        This is a simplified example that uses basic image processing
-        In a real implementation, you would use your ML model
-        """
-        # Convert to grayscale for processing
-        gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
-        
-        # Apply Gaussian blur to reduce noise
-        blurred = cv2.GaussianBlur(gray, (15, 15), 0)
-        
-        # Simple thresholding to find potential smoke regions
-        # In a real implementation, you'd use a trained model
-        _, thresh = cv2.threshold(blurred, 100, 255, cv2.THRESH_BINARY)
-        
-        # Find contours in the thresholded image
-        contours, _ = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
-        
-        # Process contours to find potential smoke regions
-        detections = []
-        height, width = image.shape[:2]
-        
-        for contour in contours:
-            # Get bounding box
-            x, y, w, h = cv2.boundingRect(contour)
-            
-            # Filter small regions
-            if w > width * 0.05 and h > height * 0.05:
-                # Calculate area ratio
-                area = cv2.contourArea(contour)
-                rect_area = w * h
-                fill_ratio = area / rect_area if rect_area > 0 else 0
-                
-                # Smoke tends to have irregular shapes
-                # This is just for demonstration purposes
-                if fill_ratio > 0.2 and fill_ratio < 0.8:
-                    # Normalize coordinates
-                    x_norm = x / width
-                    y_norm = y / height
-                    w_norm = w / width
-                    h_norm = h / height
-                    
-                    # Determine if it's smoke or fire (just a simple heuristic for demo)
-                    # In a real model, this would be determined by the model prediction
-                    class_id = 0  # Default to smoke
-                    
-                    # Check if the region has high red values (fire)
-                    roi = image[y:y+h, x:x+w]
-                    if roi.size > 0:  # Make sure ROI is not empty
-                        avg_color = np.mean(roi, axis=(0, 1))
-                        if avg_color[2] > 150 and avg_color[2] > avg_color[0] * 1.5:  # High red, indicating fire
-                            class_id = 1  # Fire
-                    
-                    # Calculate confidence based on fill ratio
-                    # This is just for demonstration
-                    confidence = 0.5 + fill_ratio * 0.3
-                    
-                    # Add to detections
-                    detections.append({
-                        'bbox': (x_norm, y_norm, w_norm, h_norm),
-                        'class_id': class_id,
-                        'confidence': confidence
-                    })
-        
-        # For demo purposes, if no smoke detected by algorithm,
-        # add a small chance of random detection
-        if not detections and np.random.random() < 0.1:  # 10% chance
-            # Random smoke detection
-            x = np.random.random() * 0.7
-            y = np.random.random() * 0.7
-            w = 0.1 + np.random.random() * 0.2
-            h = 0.1 + np.random.random() * 0.2
-            confidence = 0.5 + np.random.random() * 0.3
-            
-            detections.append({
-                'bbox': (x, y, w, h),
-                'class_id': 0,  # Smoke
-                'confidence': confidence
-            })
-            
-        return detections
-    
-    @property
-    def applies_nms(self) -> bool:
-        """Model does not apply NMS internally"""
-        return False
-    
-    def close(self):
-        """Release resources"""
-        # In a real implementation, you would release model resources here
-        pass 

python-inference-service/models/universal_yolo_model.py

@@ -6,17 +6,39 @@ import torch
 
 class Model:
     """
-    YOLOv8 模型包装类 - 使用 Ultralytics YOLO
+    通用 YOLO 模型 - 支持 YOLOv8/YOLOv11 等基于 Ultralytics 的模型
     """
     
-    def __init__(self):
-        """初始化YOLOv8模型"""
+    def __init__(self, model_file: str = None, model_name: str = "YOLO"):
+        """
+        初始化模型
+        
+        Args:
+            model_file: 模型文件名（如 smoke.pt, best.pt）
+            model_name: 模型显示名称（用于日志）
+        """
         # 获取当前文件所在目录路径
         model_dir = os.path.dirname(os.path.abspath(__file__))
-        # 模型文件路径
-        model_path = os.path.join(model_dir, "best.pt")
         
-        print(f"正在加载YOLOv8模型: {model_path}")
+        # 如果没有指定模型文件，尝试常见的文件名
+        if model_file is None:
+            for possible_file in ['garbage.pt', 'smoke.pt', 'best.pt', 'yolov8.pt', 'model.pt']:
+                test_path = os.path.join(model_dir, possible_file)
+                if os.path.exists(test_path):
+                    model_file = possible_file
+                    break
+        
+        if model_file is None:
+            raise FileNotFoundError(f"未找到模型文件，请在初始化时指定 model_file 参数")
+        
+        # 模型文件路径
+        model_path = os.path.join(model_dir, model_file)
+        
+        if not os.path.exists(model_path):
+            raise FileNotFoundError(f"模型文件不存在: {model_path}")
+        
+        self.model_name = model_name
+        print(f"正在加载{model_name}模型: {model_path}")
         
         # 检查设备
         self.device = "cuda" if torch.cuda.is_available() else "cpu"
@@ -26,19 +48,30 @@ class Model:
         try:
             from ultralytics import YOLO
             self.model = YOLO(model_path)
-            print("使用 Ultralytics YOLO 加载模型成功")
+            print(f"使用 Ultralytics YOLO 加载模型成功")
         except ImportError:
             raise ImportError("请安装 ultralytics: pip install ultralytics>=8.0.0")
         except Exception as e:
-            raise Exception(f"加载YOLOv8模型失败: {str(e)}")
+            raise Exception(f"加载{model_name}模型失败: {str(e)}")
                 
         # 加载类别名称
         self.classes = []
-        classes_path = os.path.join(model_dir, "classes.txt")
-        if os.path.exists(classes_path):
-            with open(classes_path, 'r', encoding='utf-8') as f:
+        
+        # 1. 首先尝试加载与模型文件同名的类别文件（如 smoke.txt）
+        model_base_name = os.path.splitext(model_file)[0]
+        classes_path_specific = os.path.join(model_dir, f"{model_base_name}.txt")
+        
+        # 2. 然后尝试加载通用的 classes.txt
+        classes_path_generic = os.path.join(model_dir, "classes.txt")
+        
+        if os.path.exists(classes_path_specific):
+            with open(classes_path_specific, 'r', encoding='utf-8') as f:
                 self.classes = [line.strip() for line in f.readlines() if line.strip()]
-            print(f"已加载 {len(self.classes)} 个类别")
+            print(f"已加载类别文件: {model_base_name}.txt ({len(self.classes)} 个类别)")
+        elif os.path.exists(classes_path_generic):
+            with open(classes_path_generic, 'r', encoding='utf-8') as f:
+                self.classes = [line.strip() for line in f.readlines() if line.strip()]
+            print(f"已加载类别文件: classes.txt ({len(self.classes)} 个类别)")
         else:
             # 使用模型自带的类别信息
             if hasattr(self.model, 'names') and self.model.names:
@@ -51,10 +84,10 @@ class Model:
         self.conf_threshold = 0.25  # 置信度阈值
         self.img_size = 640        # 默认输入图像大小
         
-        print("YOLOv8模型加载完成")
+        print(f"{model_name}模型加载完成")
     
     def preprocess(self, image: np.ndarray) -> np.ndarray:
-        """预处理图像 - YOLOv8会自动处理，这里直接返回"""
+        """预处理图像 - Ultralytics YOLO 会自动处理，这里直接返回"""
         return image
     
     def predict(self, image: np.ndarray) -> List[Dict[str, Any]]:
@@ -62,7 +95,7 @@ class Model:
         original_height, original_width = image.shape[:2]
         
         try:
-            # YOLOv8推理
+            # YOLO 推理
             results = self.model(
                 image, 
                 conf=self.conf_threshold,
@@ -122,7 +155,7 @@ class Model:
     @property
     def applies_nms(self) -> bool:
         """模型是否内部应用了 NMS"""
-        # YOLOv8会自动应用 NMS
+        # Ultralytics YOLO 会自动应用 NMS
         return True
     
     def close(self):
@@ -132,4 +165,5 @@ class Model:
             del self.model
             if torch.cuda.is_available():
                 torch.cuda.empty_cache()
-        print("YOLOv8模型已关闭") 
+        print(f"{self.model_name}模型已关闭")
+

python-inference-service/models/yolov5_utils.py

@@ -1,56 +0,0 @@
-import torch
-import torch.nn as nn
-import sys
-import os
-
-def attempt_load(weights, device=''):
-    """尝试加载YOLOv5模型"""
-    # 加载模型
-    model = torch.load(weights, map_location=device)
-    
-    # 确定模型格式
-    if isinstance(model, dict):
-        if 'model' in model:  # state_dict格式
-            model = model['model']
-        elif 'state_dict' in model:  # state_dict格式
-            model = model['state_dict']
-    
-    # 如果是state_dict，则需要创建模型架构
-    if isinstance(model, dict):
-        print("警告：加载的是权重字典，尝试创建默认模型结构")
-        from models.yolov5_model import YOLOv5
-        model_arch = YOLOv5()
-        model_arch.load_state_dict(model)
-        model = model_arch
-    
-    # 设置为评估模式
-    if isinstance(model, nn.Module):
-        model.eval()
-    
-    # 检查是否有类别信息
-    if not hasattr(model, 'names') or not model.names:
-        print("模型没有类别信息，尝试加载默认类别")
-        # 设置通用类别
-        model.names = ['object']
-        
-    return model
-
-class YOLOv5:
-    """简化版YOLOv5模型结构，用于加载权重"""
-    def __init__(self):
-        super(YOLOv5, self).__init__()
-        self.names = []  # 类别名称
-        # 这里应该添加真实的网络结构
-        # 但为了简单起见，我们只提供一个占位符
-        # 在实际使用中，您应该实现完整的网络架构
-        
-    def forward(self, x):
-        # 这里应该是实际的前向传播逻辑
-        # 这只是一个占位符
-        raise NotImplementedError("这是一个占位符模型，请使用完整的YOLOv5模型实现")
-        
-    def load_state_dict(self, state_dict):
-        print("尝试加载模型权重")
-        # 实际的权重加载逻辑
-        # 这只是一个占位符
-        return self 

rtsp-vue/src/api/video/alarm.js

@@ -21,8 +21,8 @@ export function getAlarm(alarmId) {
 export function handleAlarm(data) {
   return request({
     url: '/video/alarm/handle',
-    method: 'put',
-    data: data
+    method: 'post',
+    params: data
   })
 }
 
@@ -30,7 +30,7 @@ export function handleAlarm(data) {
 export function batchHandleAlarm(data) {
   return request({
     url: '/video/alarm/batchHandle',
-    method: 'put',
+    method: 'post',
     data: data
   })
 }

rtsp-vue/src/layout/components/Navbar.vue

@@ -19,7 +19,6 @@
         <div @click="router.push('/tool/gen')" title="代码生成" class="right-menu-item hover-effect">
           <svg-icon icon-class="code" />
         </div>
-        
 
         <screenfull id="screenfull" class="right-menu-item hover-effect" />
 

rtsp-vue/src/views/index.vue

@@ -15,19 +15,26 @@
     </el-form>
 
 
-    <div style="display: flex;">
+    <div style="display: flex; gap: 20px">
       <div class="card" @click="handleVideoCameraFilled(item)" v-for="item in deviceList" :key="item.deviceId">
-        <div class="card-image">
-          <img :src="item.url" :alt="item.url" style="width: 100%; height: 100%;" />
-          <!-- <div style="width: 100%; height: 100%;">
-              {{ item.url }}
-            </div> -->
+        <el-row>
+          <el-col :span="16">
+            <h3 style="display: flex; align-items: center;"><img :src="DeviceImage" alt="" style="width: 20px; height: 20px; margin-right: 10px;"> {{ item.deviceName }}</h3>
+            <div class="li" style="display: flex; align-items: center;">设备分类：<dict-tag :options="device_type" :value="item.type" /></div>
+            <div class="li" style="display: flex; align-items: center;">设备IP：{{ item.ip }}</div>
+            <div class="li" style="display: flex; align-items: center;">用户名：{{ item.username ?? '-' }}</div>
+          </el-col>
+          <el-col :span="8">
+            <img :src="CameraImage" alt="设备图片" style="width: 100%;" />
+          </el-col>
+        </el-row>
+        <!-- <div class="card-image">
+          <img :src="DeviceImage" :alt="item.url" style="width: 100%; height: 100%;" />
         </div>
         <div class="category"><dict-tag :options="device_type" :value="item.type" /></div>
         <div class="heading">
           {{ item.ip }}
-          <!-- <div class="author"> By <span class="name">Abi</span> 4 days ago</div> -->
-        </div>
+        </div> -->
       </div>
     </div>
 
@@ -89,6 +96,8 @@ import { listDevice } from "@/api/video/device";
 import { listInspectionRecord } from "@/api/video/insRecord";
 import { listInspection } from "@/api/video/inspection";
 import { listAlarm } from "@/api/video/alarm";
+import DeviceImage from "@/assets/images/device.png";
+import CameraImage from "@/assets/images/camera.png";
 
 const { proxy } = getCurrentInstance();
 const { device_on_status, device_type, ins_record_status } = proxy.useDict('device_on_status', 'device_type', 'ins_record_status');
@@ -186,19 +195,17 @@ getList();
 <style scoped>
 /* From Uiverse.io by alexmaracinaru */
 .card {
-  width: 190px;
-  background: white;
+  width: 300px;
   padding: .4em;
-  border-radius: 6px;
+  border-radius: 0;
+  border: 1px solid #e0e0e0;
 }
 
 .card-image {
-  background-color: rgb(236, 236, 236);
   width: 100%;
   height: 130px;
   text-align: center;
   word-break: break-all;
-  border-radius: 6px 6px 0 0;
 }
 
 .card-image:hover {

rtsp-vue/src/views/video/alarm/index.vue

@@ -84,10 +84,9 @@
 
     <el-table v-loading="loading" :data="alarmList" @selection-change="handleSelectionChange">
       <el-table-column type="selection" width="55" align="center" />
-      <el-table-column label="报警ID" align="center" prop="alarmId" />
       <el-table-column label="任务名称" align="center" prop="taskName" />
       <el-table-column label="设备名称" align="center" prop="deviceName" />
-      <el-table-column label="报警类型" align="center" prop="alarmType" />
+      <!-- <el-table-column label="报警类型" align="center" prop="alarmType" /> -->
       <el-table-column label="报警级别" align="center" prop="alarmLevel">
         <template #default="scope">
           <el-tag v-if="scope.row.alarmLevel === '1'" type="info">低</el-tag>
@@ -109,20 +108,10 @@
             :src="scope.row.imagePath"
             :preview-src-list="[scope.row.imagePath]"
             fit="cover"
+            preview-teleported
           />
         </template>
       </el-table-column>
-      <el-table-column label="报警视频" align="center" prop="videoPath">
-        <template #default="scope">
-          <el-button
-            v-if="scope.row.videoPath"
-            link
-            type="primary"
-            icon="VideoPlay"
-            @click="handleView(scope.row)"
-          >播放</el-button>
-        </template>
-      </el-table-column>
       <el-table-column label="报警时间" align="center" prop="alarmTime" width="180">
         <template #default="scope">
           <span>{{ parseTime(scope.row.alarmTime, '{y}-{m}-{d} {h}:{i}:{s}') }}</span>
@@ -200,10 +189,9 @@
     <!-- 查看详情对话框 -->
     <el-dialog title="报警详情" v-model="viewOpen" width="800px" append-to-body>
       <el-descriptions :column="2" border>
-        <el-descriptions-item label="报警ID">{{ viewForm.alarmId }}</el-descriptions-item>
         <el-descriptions-item label="任务名称">{{ viewForm.taskName }}</el-descriptions-item>
         <el-descriptions-item label="设备名称">{{ viewForm.deviceName }}</el-descriptions-item>
-        <el-descriptions-item label="报警类型">{{ viewForm.alarmType }}</el-descriptions-item>
+        <!-- <el-descriptions-item label="报警类型">{{ viewForm.alarmType }}</el-descriptions-item> -->
         <el-descriptions-item label="报警级别">
           <el-tag v-if="viewForm.alarmLevel === '1'" type="info">低</el-tag>
           <el-tag v-else-if="viewForm.alarmLevel === '2'" type="warning">中</el-tag>
@@ -233,15 +221,7 @@
           :src="viewForm.imagePath"
           :preview-src-list="[viewForm.imagePath]"
           fit="contain"
-        />
-      </div>
-      <div v-if="viewForm.videoPath" style="margin-top: 20px;">
-        <h4>报警视频：</h4>
-        <video
-          :src="viewForm.videoPath"
-          style="width: 100%; max-height: 420px; background: #000"
-          controls
-          preload="metadata"
+          preview-teleported
         />
       </div>
     </el-dialog>

rtsp-vue/src/views/video/device/index.vue

@@ -63,6 +63,7 @@
       <el-table-column type="selection" width="55" align="center" />
 <!--      <el-table-column label="设备ID" align="center" prop="deviceId" />-->
       <el-table-column label="IP地址" align="center" prop="ip" width="150" fixed />
+      <el-table-column label="设备名称" align="center" prop="deviceName" width="150" />
       <el-table-column label="设备类型" align="center" prop="type" width="80">
         <template #default="scope">
           <dict-tag :options="device_type" :value="scope.row.type"/>
@@ -103,6 +104,9 @@
         <el-form-item label="IP地址" prop="ip">
           <el-input v-model="form.ip" placeholder="请输入IP地址" />
         </el-form-item>
+        <el-form-item label="设备名称">
+          <el-input v-model="form.deviceName" placeholder="请输入设备名称" />
+        </el-form-item>
         <el-form-item label="设备类型" prop="type">
           <el-select v-model="form.type" placeholder="请选择设备类型">
             <el-option
@@ -218,6 +222,7 @@ function reset() {
   form.value = {
     deviceId: null,
     ip: null,
+    deviceName: null,
     type: null,
     userName: null,
     password: null,

rtsp-vue/src/views/video/inspection/index.vue

@@ -12,6 +12,11 @@
           <el-option v-for="dict in task_status" :key="dict.value" :label="dict.label" :value="dict.value" />
         </el-select>
       </el-form-item>
+      <el-form-item label="模型" prop="modelName">
+        <el-select v-model="queryParams.modelName" placeholder="请选择模型" clearable>
+          <el-option v-for="dict in py_model_manager" :key="dict.value" :label="dict.label" :value="dict.value" />
+        </el-select>
+      </el-form-item>
       <el-form-item>
         <el-button type="primary" icon="Search" @click="handleQuery">搜索</el-button>
         <el-button icon="Refresh" @click="resetQuery">重置</el-button>
@@ -40,8 +45,14 @@
 
     <el-table v-loading="loading" :data="inspectionList" @selection-change="handleSelectionChange">
       <el-table-column type="selection" width="55" align="center" />
-      <el-table-column label="任务ID" align="center" prop="taskId" />
+      <!-- <el-table-column label="任务ID" align="center" prop="taskId" /> -->
+      <el-table-column label="模型" align="center" prop="modelName">
+        <template #default="scope">
+          <dict-tag :options="py_model_manager" :value="scope.row.modelName" />
+        </template>
+      </el-table-column>
       <el-table-column label="任务名称" align="center" prop="taskName" />
+      <el-table-column label="设备IP" align="center" prop="deviceIp" />
       <el-table-column label="设备名称" align="center" prop="deviceName" />
       <el-table-column label="Cron表达式" align="center" prop="cronExpression" />
       <el-table-column label="巡检时长(秒)" align="center" prop="duration" />
@@ -90,6 +101,11 @@
         <el-form-item label="任务名称" prop="taskName">
           <el-input v-model="form.taskName" placeholder="请输入任务名称" />
         </el-form-item>
+        <el-form-item label="模型" prop="modelName">
+          <el-select v-model="form.modelName" placeholder="请选择模型" style="width: 100%">
+            <el-option v-for="dict in py_model_manager" :key="dict.value" :label="dict.label" :value="dict.value" />
+          </el-select>
+        </el-form-item>
         <el-form-item label="设备" prop="deviceId">
           <el-select v-model="form.deviceId" placeholder="请选择设备" style="width: 100%">
             <el-option v-for="device in deviceList" :key="device.deviceId" :label="device.ip"
@@ -146,7 +162,7 @@ import Crontab from '@/components/Crontab'
 import router from '@/router'
 
 const { proxy } = getCurrentInstance();
-const { sys_normal_disable, task_status } = proxy.useDict('sys_normal_disable', 'task_status');
+const { sys_normal_disable, task_status, py_model_manager } = proxy.useDict('sys_normal_disable', 'task_status', 'py_model_manager');
 
 const inspectionList = ref([]);
 const deviceList = ref([]);

rtsp-vue/src/views/video/model/dict.vue

@@ -0,0 +1,323 @@
+<template>
+  <div class="app-container">
+     <el-form :model="queryParams" ref="queryRef" :inline="true" v-show="showSearch">
+        <el-form-item label="模型简称" prop="dictLabel">
+           <el-input
+              v-model="queryParams.dictLabel"
+              placeholder="请输入模型简称"
+              clearable
+              style="width: 200px"
+              @keyup.enter="handleQuery"
+           />
+        </el-form-item>
+        <el-form-item label="状态" prop="status">
+           <el-select v-model="queryParams.status" placeholder="数据状态" clearable style="width: 200px">
+              <el-option
+                 v-for="dict in sys_normal_disable"
+                 :key="dict.value"
+                 :label="dict.label"
+                 :value="dict.value"
+              />
+           </el-select>
+        </el-form-item>
+        <el-form-item>
+           <el-button type="primary" icon="Search" @click="handleQuery">搜索</el-button>
+           <el-button icon="Refresh" @click="resetQuery">重置</el-button>
+        </el-form-item>
+     </el-form>
+
+     <el-row :gutter="10" class="mb8">
+        <el-col :span="1.5">
+           <el-button
+              type="primary"
+              plain
+              icon="Plus"
+              @click="handleAdd"
+              v-hasPermi="['system:dict:add']"
+           >新增</el-button>
+        </el-col>
+        <el-col :span="1.5">
+           <el-button
+              type="success"
+              plain
+              icon="Edit"
+              :disabled="single"
+              @click="handleUpdate"
+              v-hasPermi="['system:dict:edit']"
+           >修改</el-button>
+        </el-col>
+        <el-col :span="1.5">
+           <el-button
+              type="danger"
+              plain
+              icon="Delete"
+              :disabled="multiple"
+              @click="handleDelete"
+              v-hasPermi="['system:dict:remove']"
+           >删除</el-button>
+        </el-col>
+        <el-col :span="1.5">
+           <el-button
+              type="warning"
+              plain
+              icon="Download"
+              @click="handleExport"
+              v-hasPermi="['system:dict:export']"
+           >导出</el-button>
+        </el-col>
+        <right-toolbar v-model:showSearch="showSearch" @queryTable="getList"></right-toolbar>
+     </el-row>
+
+     <el-table v-loading="loading" :data="dataList" @selection-change="handleSelectionChange">
+        <el-table-column type="selection" width="55" align="center" />
+        <el-table-column label="模型简称" align="center" prop="dictLabel">
+           <template #default="scope">
+              <span v-if="(scope.row.listClass == '' || scope.row.listClass == 'default') && (scope.row.cssClass == '' || scope.row.cssClass == null)">{{ scope.row.dictLabel }}</span>
+              <el-tag v-else :type="scope.row.listClass == 'primary' ? '' : scope.row.listClass" :class="scope.row.cssClass">{{ scope.row.dictLabel }}</el-tag>
+           </template>
+        </el-table-column>
+        <el-table-column label="模型名称" align="center" prop="dictValue" />
+        <el-table-column label="状态" align="center" prop="status">
+           <template #default="scope">
+              <dict-tag :options="sys_normal_disable" :value="scope.row.status" />
+           </template>
+        </el-table-column>
+        <el-table-column label="备注" align="center" prop="remark" :show-overflow-tooltip="true" />
+        <el-table-column label="创建时间" align="center" prop="createTime" width="180">
+           <template #default="scope">
+              <span>{{ parseTime(scope.row.createTime) }}</span>
+           </template>
+        </el-table-column>
+        <el-table-column label="操作" align="center" width="160" class-name="small-padding fixed-width">
+           <template #default="scope">
+              <el-button link type="primary" icon="Edit" @click="handleUpdate(scope.row)" v-hasPermi="['system:dict:edit']">修改</el-button>
+              <el-button link type="primary" icon="Delete" @click="handleDelete(scope.row)" v-hasPermi="['system:dict:remove']">删除</el-button>
+           </template>
+        </el-table-column>
+     </el-table>
+
+     <pagination
+        v-show="total > 0"
+        :total="total"
+        v-model:page="queryParams.pageNum"
+        v-model:limit="queryParams.pageSize"
+        @pagination="getList"
+     />
+
+     <!-- 添加或修改参数配置对话框 -->
+     <el-dialog :title="title" v-model="open" width="500px" append-to-body>
+        <el-form ref="dataRef" :model="form" :rules="rules" label-width="80px">
+           <el-form-item label="模型简称" prop="dictLabel">
+              <el-input v-model="form.dictLabel" placeholder="请输入数据标签" />
+           </el-form-item>
+           <el-form-item label="模型名称" prop="dictValue">
+              <el-input v-model="form.dictValue" placeholder="请输入模型名称" />
+           </el-form-item>
+           <el-form-item label="状态" prop="status">
+              <el-radio-group v-model="form.status">
+                 <el-radio
+                    v-for="dict in sys_normal_disable"
+                    :key="dict.value"
+                    :value="dict.value"
+                 >{{ dict.label }}</el-radio>
+              </el-radio-group>
+           </el-form-item>
+           <el-form-item label="备注" prop="remark">
+              <el-input v-model="form.remark" type="textarea" placeholder="请输入内容"></el-input>
+           </el-form-item>
+        </el-form>
+        <template #footer>
+           <div class="dialog-footer">
+              <el-button type="primary" @click="submitForm">确 定</el-button>
+              <el-button @click="cancel">取 消</el-button>
+           </div>
+        </template>
+     </el-dialog>
+  </div>
+</template>
+
+<script setup name="Data">
+import useDictStore from '@/store/modules/dict'
+import { optionselect as getDictOptionselect, getType } from "@/api/system/dict/type";
+import { listData, getData, delData, addData, updateData } from "@/api/system/dict/data";
+
+const { proxy } = getCurrentInstance();
+const { sys_normal_disable } = proxy.useDict("sys_normal_disable");
+
+const dataList = ref([]);
+const open = ref(false);
+const loading = ref(true);
+const showSearch = ref(true);
+const ids = ref([]);
+const single = ref(true);
+const multiple = ref(true);
+const total = ref(0);
+const title = ref("");
+const defaultDictType = ref("");
+const typeOptions = ref([]);
+const route = useRoute();
+// 数据标签回显样式
+const listClassOptions = ref([
+ { value: "default", label: "默认" }, 
+ { value: "primary", label: "主要" }, 
+ { value: "success", label: "成功" },
+ { value: "info", label: "信息" },
+ { value: "warning", label: "警告" },
+ { value: "danger", label: "危险" }
+]);
+
+const data = reactive({
+ form: {},
+ queryParams: {
+   pageNum: 1,
+   pageSize: 20,
+   dictType: undefined,
+   dictLabel: undefined,
+   status: undefined
+ },
+ rules: {
+   dictLabel: [{ required: true, message: "数据标签不能为空", trigger: "blur" }],
+   dictValue: [{ required: true, message: "数据键值不能为空", trigger: "blur" }],
+   dictSort: [{ required: true, message: "数据顺序不能为空", trigger: "blur" }]
+ }
+});
+
+const { queryParams, form, rules } = toRefs(data);
+
+/** 查询字典类型详细 */
+function getTypes(dictId) {
+ getType(dictId).then(response => {
+   queryParams.value.dictType = response.data.dictType;
+   defaultDictType.value = response.data.dictType;
+   getList();
+ });
+}
+
+/** 查询字典类型列表 */
+function getTypeList() {
+ getDictOptionselect().then(response => {
+   typeOptions.value = response.data;
+ });
+}
+
+/** 查询字典数据列表 */
+function getList() {
+ loading.value = true;
+ listData(queryParams.value).then(response => {
+   dataList.value = response.rows;
+   total.value = response.total;
+   loading.value = false;
+ });
+}
+
+/** 取消按钮 */
+function cancel() {
+ open.value = false;
+ reset();
+}
+
+/** 表单重置 */
+function reset() {
+ form.value = {
+   dictCode: undefined,
+   dictLabel: undefined,
+   dictValue: undefined,
+   cssClass: undefined,
+   listClass: "default",
+   dictSort: 0,
+   status: "0",
+   remark: undefined
+ };
+ proxy.resetForm("dataRef");
+}
+
+/** 搜索按钮操作 */
+function handleQuery() {
+ queryParams.value.pageNum = 1;
+ getList();
+}
+
+/** 返回按钮操作 */
+function handleClose() {
+ const obj = { path: "/system/dict" };
+ proxy.$tab.closeOpenPage(obj);
+}
+
+/** 重置按钮操作 */
+function resetQuery() {
+ proxy.resetForm("queryRef");
+ queryParams.value.dictType = defaultDictType.value;
+ handleQuery();
+}
+
+/** 新增按钮操作 */
+function handleAdd() {
+ reset();
+ open.value = true;
+ title.value = "添加字典数据";
+ form.value.dictType = queryParams.value.dictType;
+}
+
+/** 多选框选中数据 */
+function handleSelectionChange(selection) {
+ ids.value = selection.map(item => item.dictCode);
+ single.value = selection.length != 1;
+ multiple.value = !selection.length;
+}
+
+/** 修改按钮操作 */
+function handleUpdate(row) {
+ reset();
+ const dictCode = row.dictCode || ids.value;
+ getData(dictCode).then(response => {
+   form.value = response.data;
+   open.value = true;
+   title.value = "修改字典数据";
+ });
+}
+
+/** 提交按钮 */
+function submitForm() {
+ proxy.$refs["dataRef"].validate(valid => {
+   if (valid) {
+     if (form.value.dictCode != undefined) {
+       updateData(form.value).then(response => {
+         useDictStore().removeDict(queryParams.value.dictType);
+         proxy.$modal.msgSuccess("修改成功");
+         open.value = false;
+         getList();
+       });
+     } else {
+       addData(form.value).then(response => {
+         useDictStore().removeDict(queryParams.value.dictType);
+         proxy.$modal.msgSuccess("新增成功");
+         open.value = false;
+         getList();
+       });
+     }
+   }
+ });
+}
+
+/** 删除按钮操作 */
+function handleDelete(row) {
+ const dictCodes = row.dictCode || ids.value;
+ proxy.$modal.confirm('是否确认删除字典编码为"' + dictCodes + '"的数据项？').then(function() {
+   return delData(dictCodes);
+ }).then(() => {
+   getList();
+   proxy.$modal.msgSuccess("删除成功");
+   useDictStore().removeDict(queryParams.value.dictType);
+ }).catch(() => {});
+}
+
+/** 导出按钮操作 */
+function handleExport() {
+ proxy.download("system/dict/data/export", {
+   ...queryParams.value
+ }, `dict_data_${new Date().getTime()}.xlsx`);
+}
+
+getTypes(105);
+getTypeList();
+</script>

ruoyi-video/pom.xml

@@ -109,6 +109,10 @@
             <groupId>com.ruoyi</groupId>
             <artifactId>ruoyi-framework</artifactId>
         </dependency>
+        <dependency>
+            <groupId>com.ruoyi</groupId>
+            <artifactId>ruoyi-quartz</artifactId>
+        </dependency>
 
     </dependencies>
 

ruoyi-video/src/main/java/com/ruoyi/video/controller/AlarmRecordController.java

@@ -8,6 +8,7 @@ import com.ruoyi.common.enums.BusinessType;
 import com.ruoyi.common.utils.SecurityUtils;
 import com.ruoyi.common.utils.poi.ExcelUtil;
 import com.ruoyi.video.domain.AlarmRecord;
+import com.ruoyi.video.domain.bo.alarmBatchBo;
 import com.ruoyi.video.service.InspectionTaskService;
 import org.springframework.beans.factory.annotation.Autowired;
 import org.springframework.security.access.prepost.PreAuthorize;
@@ -34,7 +35,6 @@ public class AlarmRecordController extends BaseController {
     /**
      * 查询报警记录列表
      */
-    @PreAuthorize("@ss.hasPermi('video:alarm:list')")
     @GetMapping("/list")
     public TableDataInfo list(AlarmRecord alarmRecord) {
         startPage();
@@ -45,7 +45,6 @@ public class AlarmRecordController extends BaseController {
     /**
      * 导出报警记录列表
      */
-    @PreAuthorize("@ss.hasPermi('video:alarm:export')")
     @Log(title = "报警记录", businessType = BusinessType.EXPORT)
     @PostMapping("/export")
     public void export(HttpServletResponse response, AlarmRecord alarmRecord) {
@@ -57,7 +56,6 @@ public class AlarmRecordController extends BaseController {
     /**
      * 处理报警记录
      */
-    @PreAuthorize("@ss.hasPermi('video:alarm:handle')")
     @Log(title = "处理报警记录", businessType = BusinessType.UPDATE)
     @PostMapping("/handle")
     public AjaxResult handle(@RequestParam Long alarmId, 
@@ -71,12 +69,12 @@ public class AlarmRecordController extends BaseController {
     /**
      * 批量处理报警记录
      */
-    @PreAuthorize("@ss.hasPermi('video:alarm:handle')")
     @Log(title = "批量处理报警记录", businessType = BusinessType.UPDATE)
     @PostMapping("/batchHandle")
-    public AjaxResult batchHandle(@RequestParam Long[] alarmIds, 
-                                @RequestParam String handleStatus, 
-                                @RequestParam(required = false) String handleRemark) {
+    public AjaxResult batchHandle(@RequestBody alarmBatchBo alarmBatchBo) {
+        Long[] alarmIds = alarmBatchBo.getAlarmIds();
+        String handleStatus = alarmBatchBo.getHandleStatus();
+        String handleRemark = alarmBatchBo.getHandleRemark();
         String handleBy = SecurityUtils.getUsername();
         int successCount = 0;
         for (Long alarmId : alarmIds) {

ruoyi-video/src/main/java/com/ruoyi/video/domain/Device.java

@@ -14,6 +14,8 @@ public class Device extends BaseEntity {
     private Long deviceId;
     @Excel(name = "IP地址")
     private String ip;
+    @Excel(name = "设备名称")
+    private String deviceName;
     @Excel(
             name = "设备类型(1=haikan,2=dahua)"
     )
@@ -51,7 +53,7 @@ public class Device extends BaseEntity {
     }
 
     public String toString() {
-        return "Device{deviceId=" + this.deviceId + ", ip='" + this.ip + "', type='" + this.type + "', mediaKey='" + this.mediaKey + "', userName='" + this.userName + "', password='" + this.password + "', url='" + this.url + "', enabledFlv='" + this.enabledFlv + "', enabledHls='" + this.enabledHls + "', mode='" + this.mode + "'}";
+        return "Device{deviceId=" + this.deviceId + ", deviceName='" + this.deviceName + "', ip='" + this.ip + "', type='" + this.type + "', mediaKey='" + this.mediaKey + "', userName='" + this.userName + "', password='" + this.password + "', url='" + this.url + "', enabledFlv='" + this.enabledFlv + "', enabledHls='" + this.enabledHls + "', mode='" + this.mode + "'}";
     }
 
     public Long getDeviceId() {
@@ -62,6 +64,14 @@ public class Device extends BaseEntity {
         this.deviceId = deviceId;
     }
 
+    public String getDeviceName() {
+        return deviceName;
+    }
+
+    public void setDeviceName(String deviceName) {
+        this.deviceName = deviceName;
+    }
+
     public String getIp() {
         return this.ip;
     }

ruoyi-video/src/main/java/com/ruoyi/video/domain/InspectionTask.java

@@ -6,7 +6,7 @@ import java.util.Date;
 
 /**
  * 巡检任务对象 v_inspection_task
- * 
+ *
  * @author ruoyi
  * @date 2025-09-27
  */
@@ -22,9 +22,12 @@ public class InspectionTask extends BaseEntity {
     /** 设备ID */
     private Long deviceId;
 
-    /** 设备名称 */
+    /** 设备名称（联查返回） */
     private String deviceName;
 
+    /** 设备IP（联查返回） */
+    private String deviceIp;
+
     /** Cron表达式 */
     private String cronExpression;
 
@@ -52,6 +55,16 @@ public class InspectionTask extends BaseEntity {
     /** 报警次数 */
     private Long alarmCount;
 
+    private String modelName;
+
+    public void setModelName(String modelName) {
+        this.modelName = modelName;
+    }
+
+    public String getModelName() {
+        return modelName;
+    }
+
     public void setTaskId(Long taskId) {
         this.taskId = taskId;
     }
@@ -84,6 +97,14 @@ public class InspectionTask extends BaseEntity {
         return deviceName;
     }
 
+    public String getDeviceIp() {
+        return deviceIp;
+    }
+
+    public void setDeviceIp(String deviceIp) {
+        this.deviceIp = deviceIp;
+    }
+
     public void setCronExpression(String cronExpression) {
         this.cronExpression = cronExpression;
     }

ruoyi-video/src/main/java/com/ruoyi/video/domain/bo/alarmBatchBo.java

@@ -0,0 +1,10 @@
+package com.ruoyi.video.domain.bo;
+
+import lombok.Data;
+
+@Data
+public class alarmBatchBo {
+    private Long[] alarmIds;
+    private String handleStatus;
+    private String handleRemark;
+}

ruoyi-video/src/main/java/com/ruoyi/video/scheduler/InspectionCronScheduler.java

@@ -24,9 +24,10 @@ import java.util.concurrent.TimeUnit;
 
 /**
  * 内部巡检任务调度器（不依赖若依Quartz）
- * - 周期性轮询 v_inspection_task 中启用(status='0')的任务
+ * - 周期性轮询 v_inspection_task 中任务，按状态 0=启用、1=停用 控制是否触发
  * - 使用 Spring CronExpression 计算下一次执行
  * - 到点调用 InspectionTaskService.executeInspectionTask(taskId)
+ * - 不修改任务的状态字段（状态仅由外部手动启停控制）
  */
 @Slf4j
 @Component
@@ -119,21 +120,6 @@ public class InspectionCronScheduler {
                 } catch (Exception e) {
                     log.debug("更新nextExecuteTime失败: taskId={}, err={}", taskId, e.getMessage());
                 }
-
-                // 若发现状态为“2”（服务执行完成后置状态），将其规范化回“0”以维持启用
-                if ("2".equals(status)) {
-                    try {
-                        InspectionTask patch = new InspectionTask();
-                        patch.setTaskId(taskId);
-                        patch.setStatus("0");
-                        patch.setUpdateTime(DateUtils.getNowDate());
-                        inspectionTaskMapper.updateInspectionTask(patch);
-                        task.setStatus("0");
-                    } catch (Exception e) {
-                        log.debug("规范化任务状态失败: taskId={}, err={}", taskId, e.getMessage());
-                    }
-                }
-
                 // 到点触发判定：如果 next <= now + 10s 窗口内，就触发一次
                 long nowMs = System.currentTimeMillis();
                 long nextMs = nextDate.getTime();
@@ -164,19 +150,6 @@ public class InspectionCronScheduler {
                     } catch (Exception e) {
                         log.error("执行巡检任务触发失败: taskId={}, err={}", taskId, e.getMessage(), e);
                     }
-
-                    // 延迟规范化状态为启用（服务执行期间可能将其改为1或2）
-                    try {
-                        poller.schedule(() -> {
-                            try {
-                                InspectionTask patch2 = new InspectionTask();
-                                patch2.setTaskId(taskId);
-                                patch2.setStatus("0");
-                                patch2.setUpdateTime(DateUtils.getNowDate());
-                                inspectionTaskMapper.updateInspectionTask(patch2);
-                            } catch (Exception ignored) {}
-                        }, 3, TimeUnit.SECONDS);
-                    } catch (Exception ignore) {}
                 }
             }
         } catch (Exception e) {

ruoyi-video/src/main/java/com/ruoyi/video/service/VideoAnalysisService.java

@@ -64,15 +64,16 @@ public class VideoAnalysisService {
 
     @Autowired
     private com.ruoyi.video.mapper.InspectionTaskRecordMapper inspectionTaskRecordMapper;
+    @Autowired
+    private InspectionTaskMapper inspectionTaskMapper;
 
-    // 检测器配置 - 使用容器名而不是localhost
-    private static final String PYTHON_API_URL = "http://rtsp-python-service:10083/api/detect/file";
-    private static final String MODEL_NAME = "yolov8_detector";
+    // 检测器配置 - 支持环境变量配置
+    private static final String PYTHON_API_URL = System.getenv().getOrDefault("PYTHON_API_URL", "http://localhost:8000") + "/api/detect/file";
+    private static final String MODEL_NAME = "smoke"; // 默认使用吸烟检测模型
 
     /**
      * 分析视频并更新记录（同步调用）
      * @param task 巡检任务
-     * @param record 巡检记录
      * @param videoFile 视频文件
      */
     public void analyzeVideoWithRecord(InspectionTask task, com.ruoyi.video.domain.InspectionTaskRecord record, File videoFile) {
@@ -83,7 +84,11 @@ public class VideoAnalysisService {
             File outputVideoFile = File.createTempFile("analysis_output_", ".mp4");
             
             // 创建检测器
-            HttpYoloDetector detector = new HttpYoloDetector("yolov8", PYTHON_API_URL, MODEL_NAME, 0x00FF00);
+            String chosenModel = (task.getModelName() != null && !task.getModelName().trim().isEmpty())
+                    ? task.getModelName().trim()
+                    : MODEL_NAME;
+            log.info("使用模型进行分析: {} (taskId={})", chosenModel, task.getTaskId());
+            HttpYoloDetector detector = new HttpYoloDetector("yolov8", PYTHON_API_URL, chosenModel, 0x00FF00);
             
             // 处理视频并记录检测结果
             String detectionResult = processVideoWithRecord(videoFile, outputVideoFile, detector, task, record);
@@ -222,6 +227,9 @@ public class VideoAnalysisService {
      */
     private void createAlarmRecordForRecord(InspectionTask task, com.ruoyi.video.domain.InspectionTaskRecord record, 
                                             Detection detection, Mat frame, long frameCount) throws Exception {
+        //创建记录之前应该给task加上报警次数
+        task.setAlarmCount(task.getAlarmCount() + 1);
+        inspectionTaskMapper.updateInspectionTask(task);
         // 创建告警图像临时文件
         File alarmImageFile = File.createTempFile("alarm_", ".jpg");
         

ruoyi-video/src/main/java/com/ruoyi/video/service/impl/InspectionTaskServiceImpl.java

@@ -2,6 +2,7 @@ package com.ruoyi.video.service.impl;
 
 import com.ruoyi.common.utils.DateUtils;
 import com.ruoyi.common.utils.SecurityUtils;
+import com.ruoyi.quartz.util.CronUtils;
 import com.ruoyi.video.domain.*;
 import com.ruoyi.video.domain.dto.CameraDto;
 import com.ruoyi.video.mapper.InspectionTaskMapper;
@@ -64,7 +65,7 @@ public class InspectionTaskServiceImpl implements InspectionTaskService {
     private IVMinioObjectService vMinioObjectService;
 
     // 运行状态缓存（避免重复执行）
-    private final Map<Long, Boolean> runningTasks = new ConcurrentHashMap<>();
+//    private final Map<Long, Boolean> runningTasks = new ConcurrentHashMap<>();
 
     private ModelManager modelManager;
     // 延迟初始化，避免启动时的依赖问题
@@ -83,16 +84,15 @@ public class InspectionTaskServiceImpl implements InspectionTaskService {
     @Override
     public int insertInspectionTask(InspectionTask inspectionTask) {
         inspectionTask.setCreateTime(DateUtils.getNowDate());
-        // 这些字段在新版实体类中可能不存在，需要进行调整
-        // inspectionTask.setExecuteCount(0L);
-        // inspectionTask.setAlarmCount(0L);
+         inspectionTask.setExecuteCount(0L);
+         inspectionTask.setAlarmCount(0L);
         
         // 获取设备信息
-        Device device = deviceService.selectDeviceByDeviceId(inspectionTask.getDeviceId());
-        // 新版实体类可能不需要设备名称
-        // if (device != null) {
-        //     inspectionTask.setDeviceName(device.getIp());
-        // }
+//        Device device = deviceService.selectDeviceByDeviceId(inspectionTask.getDeviceId());
+//
+//         if (device != null) {
+//             inspectionTask.setDeviceName(device.getIp());
+//         }
         
         return inspectionTaskMapper.insertInspectionTask(inspectionTask);
     }
@@ -117,14 +117,14 @@ public class InspectionTaskServiceImpl implements InspectionTaskService {
         if (task == null) {
             return false;
         }
-        
+
         // 启用任务，使用新版实体类的方法
         task.setStatus("0"); // 0表示启用
         task.setUpdateTime(DateUtils.getNowDate());
         inspectionTaskMapper.updateInspectionTask(task);
-        
-        runningTasks.put(taskId, true);
-        
+
+//        runningTasks.put(taskId, true);
+
         // 这里应该集成到Quartz定时任务中
         log.info("启动巡检任务: {}", taskId);
         return true;
@@ -142,7 +142,7 @@ public class InspectionTaskServiceImpl implements InspectionTaskService {
         task.setUpdateTime(DateUtils.getNowDate());
         inspectionTaskMapper.updateInspectionTask(task);
         
-        runningTasks.remove(taskId);
+//        runningTasks.remove(taskId);
         
         log.info("停止巡检任务: {}", taskId);
         return true;
@@ -170,7 +170,12 @@ public class InspectionTaskServiceImpl implements InspectionTaskService {
         
         try {
             // 更新任务状态为执行中
-            task.setStatus("1");
+//            task.setStatus("1");
+            // 更新最后执行时间和下次执行时间
+            task.setLastExecuteTime(new Date());
+            task.setNextExecuteTime(CronUtils.getNextExecution(task.getCronExpression()));
+            //更新执行次数
+            task.setExecuteCount(task.getExecuteCount() + 1);
             inspectionTaskMapper.updateInspectionTask(task);
             
             // 获取设备信息
@@ -191,16 +196,16 @@ public class InspectionTaskServiceImpl implements InspectionTaskService {
             inspectionTaskRecordMapper.updateInspectionTaskRecord(record);
             
             // 更新任务状态为已完成
-            task.setStatus("2");
-            inspectionTaskMapper.updateInspectionTask(task);
+//            task.setStatus("0");
+//            inspectionTaskMapper.updateInspectionTask(task);
             
         } catch (Exception e) {
             log.error("巡检任务执行失败: taskId={}", taskId, e);
             updateRecordFailed(record, e.getMessage());
             
             // 更新任务状态为已完成（虽然失败）
-            task.setStatus("2");
-            inspectionTaskMapper.updateInspectionTask(task);
+//            task.setStatus("0");
+//            inspectionTaskMapper.updateInspectionTask(task);
         }
     }
     
@@ -208,7 +213,7 @@ public class InspectionTaskServiceImpl implements InspectionTaskService {
      * 更新记录为失败状态
      */
     private void updateRecordFailed(InspectionTaskRecord record, String errorMsg) {
-        record.setStatus(1); // 失败
+        record.setStatus(2); // 失败
         record.setResult("执行失败: " + errorMsg);
         inspectionTaskRecordMapper.updateInspectionTaskRecord(record);
     }
@@ -452,7 +457,7 @@ public class InspectionTaskServiceImpl implements InspectionTaskService {
                                             alarm.setTaskId(task.getTaskId());
                                             alarm.setTaskName(task.getTaskName());
                                             alarm.setDeviceId(task.getDeviceId());
-                                            alarm.setDeviceName(task.getDeviceName());
+//                                            alarm.setDeviceName(task.getDeviceName());
                                             alarm.setAlarmType(best.getLabel());
                                             // 这里需要转换double为float
                                             alarm.setAlarmLevel(getAlarmLevel((float)best.getConfidence()));

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

@@ -27,14 +27,14 @@ import static org.bytedeco.opencv.global.opencv_imgcodecs.imencode;
  */
 public class HttpYoloDetector implements YoloDetector {
     private static final Logger log = LoggerFactory.getLogger(HttpYoloDetector.class);
-    
+
     private final String name;
     private final String apiUrl;
     private final String modelName;
     private final int colorBGR;
     private final RestTemplate restTemplate;
     private final ObjectMapper objectMapper;
-    
+
     /**
      * 创建HTTP检测器
      * @param name 检测器名称
@@ -49,48 +49,60 @@ public class HttpYoloDetector implements YoloDetector {
         this.colorBGR = colorBGR;
         this.restTemplate = new RestTemplate();
         this.objectMapper = new ObjectMapper();
-        
+
         log.info("创建HTTP YOLOv8检测器: {}, 服务地址: {}, 模型: {}", name, apiUrl, modelName);
     }
-    
+
     @Override
     public String name() {
         return name;
     }
-    
+
     @Override
     public List<Detection> detect(Mat bgr) {
         if (bgr == null || bgr.empty()) {
             return Collections.emptyList();
         }
-        
+
         try {
-            // 将OpenCV的Mat转换为JPEG字节数组
             BytePointer buffer = new BytePointer();
             imencode(".jpg", bgr, buffer);
             byte[] jpgBytes = new byte[(int)(buffer.capacity())];
             buffer.get(jpgBytes);
             buffer.deallocate();
-            
+
             // 准备HTTP请求参数
             HttpHeaders headers = new HttpHeaders();
             headers.setContentType(MediaType.MULTIPART_FORM_DATA);
-            
+
             MultiValueMap<String, Object> body = new LinkedMultiValueMap<>();
-            body.add("model_name", modelName);
+            // 仅发送文件，model_name 放到查询参数
             body.add("file", new CustomByteArrayResource(jpgBytes, "image.jpg"));
-            
+
             HttpEntity<MultiValueMap<String, Object>> requestEntity = new HttpEntity<>(body, headers);
-            
+
+            // 将 model_name 作为查询参数
+            String urlWithQuery;
+            try {
+                String encoded = java.net.URLEncoder.encode(modelName, java.nio.charset.StandardCharsets.UTF_8.toString());
+                urlWithQuery = apiUrl + (apiUrl.contains("?") ? "&" : "?") + "model_name=" + encoded;
+            } catch (Exception ex) {
+                urlWithQuery = apiUrl + (apiUrl.contains("?") ? "&" : "?") + "model_name=" + modelName;
+            }
+
             // 发送请求到Python服务
-            ResponseEntity<String> response = restTemplate.postForEntity(apiUrl, requestEntity, String.class);
+            ResponseEntity<String> response = restTemplate.postForEntity(urlWithQuery, requestEntity, String.class);
             String responseBody = response.getBody();
-            
+            if (!response.getStatusCode().is2xxSuccessful()) {
+                log.error("HTTP检测失败: status={}, body={}", response.getStatusCodeValue(), responseBody);
+                return Collections.emptyList();
+            }
+
             if (responseBody != null) {
                 // 解析响应JSON
                 Map<String, Object> result = objectMapper.readValue(responseBody, Map.class);
                 List<Map<String, Object>> detectionsJson = (List<Map<String, Object>>) result.get("detections");
-                
+
                 List<Detection> detections = new ArrayList<>();
                 for (Map<String, Object> det : detectionsJson) {
                     String label = (String) det.get("label");
@@ -99,16 +111,16 @@ public class HttpYoloDetector implements YoloDetector {
                     int y = ((Number) det.get("y")).intValue();
                     int width = ((Number) det.get("width")).intValue();
                     int height = ((Number) det.get("height")).intValue();
-                    
+
                     detections.add(new Detection(label, confidence, new Rect(x, y, width, height), colorBGR));
                 }
-                
+
                 return detections;
             }
         } catch (Exception e) {
             log.error("HTTP检测请求失败: {}", e.getMessage());
         }
-        
+
         return Collections.emptyList();
     }
 
@@ -116,57 +128,57 @@ public class HttpYoloDetector implements YoloDetector {
     private static class CustomByteArrayResource implements org.springframework.core.io.Resource {
         private final byte[] byteArray;
         private final String filename;
-        
+
         public CustomByteArrayResource(byte[] byteArray, String filename) {
             this.byteArray = byteArray;
             this.filename = filename;
         }
-        
+
         @Override
         public String getFilename() {
             return this.filename;
         }
-        
+
         @Override
         public java.io.InputStream getInputStream() throws IOException {
             return new java.io.ByteArrayInputStream(this.byteArray);
         }
-        
+
         @Override
         public boolean exists() {
             return true;
         }
-        
+
         @Override
         public java.net.URL getURL() throws IOException {
             throw new IOException("Not supported");
         }
-        
+
         @Override
         public java.net.URI getURI() throws IOException {
             throw new IOException("Not supported");
         }
-        
+
         @Override
         public java.io.File getFile() throws IOException {
             throw new IOException("Not supported");
         }
-        
+
         @Override
         public long contentLength() {
             return this.byteArray.length;
         }
-        
+
         @Override
         public long lastModified() {
             return System.currentTimeMillis();
         }
-        
+
         @Override
         public org.springframework.core.io.Resource createRelative(String relativePath) throws IOException {
             throw new IOException("Not supported");
         }
-        
+
         @Override
         public String getDescription() {
             return "Byte array resource [" + this.filename + "]";

ruoyi-video/src/main/resources/libs/models/models.json

@@ -1,4 +1,16 @@
 [
-  {"name":"smoke","path":"libs/models/smoke","size":[640,640],"backend":"opencv"},
-  {"name":"garbage","path":"libs/models/garbage","size":[640,640],"backend":"opencv"}
+  {
+    "name": "smoke",
+    "pythonModelName": "smoke",
+    "pythonApiUrl": "http://localhost:8000/api/detect/file",
+    "size": [640, 640],
+    "backend": "python"
+  },
+  {
+    "name": "garbage",
+    "pythonModelName": "garbage",
+    "pythonApiUrl": "http://localhost:8000/api/detect/file",
+    "size": [640, 640],
+    "backend": "python"
+  }
 ]

ruoyi-video/src/main/resources/mapper/video/DeviceMapper.xml

@@ -6,6 +6,7 @@
 
     <resultMap type="Device" id="DeviceResult">
         <result property="deviceId"    column="device_id"    />
+        <result property="deviceName"    column="device_name"    />
         <result property="ip"    column="ip"    />
         <result property="type"    column="type"    />
         <result property="userName"    column="user_name"    />
@@ -23,12 +24,13 @@
     </resultMap>
 
     <sql id="selectDeviceVo">
-        select device_id, ip, type, user_name, password, url, mediaKey, enabledFlv, enabledHls, mode, create_by, create_time, update_by, update_time, remark from v_device
+        select device_id, device_name, ip, type, user_name, password, url, mediaKey, enabledFlv, enabledHls, mode, create_by, create_time, update_by, update_time, remark from v_device
     </sql>
 
     <select id="selectDeviceList" parameterType="Device" resultMap="DeviceResult">
         <include refid="selectDeviceVo"/>
         <where>
+            <if test="deviceName != null  and deviceName != ''"> and device_name like concat('%', #{deviceName}, '%')</if>
             <if test="ip != null  and ip != ''"> and ip = #{ip}</if>
             <if test="type != null  and type != ''"> and type = #{type}</if>
             <if test="userName != null  and userName != ''"> and user_name like concat('%', #{userName}, '%')</if>
@@ -49,6 +51,7 @@
     <insert id="insertDevice" parameterType="Device" useGeneratedKeys="true" keyProperty="deviceId">
         insert into v_device
         <trim prefix="(" suffix=")" suffixOverrides=",">
+            <if test="deviceName != null and deviceName != ''">device_name,</if>
             <if test="ip != null and ip != ''">ip,</if>
             <if test="type != null and type != ''">type,</if>
             <if test="userName != null and userName != ''">user_name,</if>
@@ -65,6 +68,7 @@
             <if test="remark != null">remark,</if>
         </trim>
         <trim prefix="values (" suffix=")" suffixOverrides=",">
+            <if test="deviceName != null and deviceName != ''">#{deviceName},</if>
             <if test="ip != null and ip != ''">#{ip},</if>
             <if test="type != null and type != ''">#{type},</if>
             <if test="userName != null and userName != ''">#{userName},</if>
@@ -85,6 +89,7 @@
     <update id="updateDevice" parameterType="Device">
         update v_device
         <trim prefix="SET" suffixOverrides=",">
+            <if test="deviceName != null and deviceName != ''">device_name = #{deviceName},</if>
             <if test="ip != null and ip != ''">ip = #{ip},</if>
             <if test="type != null and type != ''">type = #{type},</if>
             <if test="userName != null and userName != ''">user_name = #{userName},</if>

ruoyi-video/src/main/resources/mapper/video/InspectionTaskMapper.xml

@@ -1,14 +1,15 @@
 <?xml version="1.0" encoding="UTF-8" ?>
 <!DOCTYPE mapper
-PUBLIC "-//mybatis.org//DTD Mapper 3.0//EN"
-"http://mybatis.org/dtd/mybatis-3-mapper.dtd">
+        PUBLIC "-//mybatis.org//DTD Mapper 3.0//EN"
+        "http://mybatis.org/dtd/mybatis-3-mapper.dtd">
 <mapper namespace="com.ruoyi.video.mapper.InspectionTaskMapper">
-    
+
     <resultMap type="InspectionTask" id="InspectionTaskResult">
         <result property="taskId"           column="task_id"            />
         <result property="taskName"         column="task_name"          />
         <result property="deviceId"         column="device_id"          />
         <result property="deviceName"       column="device_name"        />
+        <result property="deviceIp"         column="device_ip"          />
         <result property="cronExpression"   column="cron_expression"    />
         <result property="duration"         column="duration"           />
         <result property="threshold"        column="threshold"          />
@@ -17,6 +18,7 @@ PUBLIC "-//mybatis.org//DTD Mapper 3.0//EN"
         <result property="executeCount"     column="execute_count"      />
         <result property="alarmCount"       column="alarm_count"        />
         <result property="lastExecuteTime"  column="last_execute_time"  />
+        <result property="modelName"        column="model_name"         />
         <result property="remark"           column="remark"             />
         <result property="createBy"         column="create_by"          />
         <result property="createTime"       column="create_time"        />
@@ -25,24 +27,30 @@ PUBLIC "-//mybatis.org//DTD Mapper 3.0//EN"
     </resultMap>
 
     <sql id="selectInspectionTaskVo">
-        select task_id, task_name, device_id, device_name, cron_expression, duration,
-               threshold, enable_detection, status, execute_count, alarm_count, 
-               last_execute_time, remark, create_by, create_time, update_by, update_time 
-        from v_inspection_task
+        select
+            t.task_id, t.task_name, t.device_id,
+            t.cron_expression, t.duration,
+            t.threshold, t.enable_detection, t.status, t.execute_count, t.alarm_count,
+            t.last_execute_time, t.model_name, t.remark, t.create_by, t.create_time, t.update_by, t.update_time,
+            d.device_name as device_name,
+            d.ip as device_ip
+        from v_inspection_task t
+                 left join v_device d on t.device_id = d.device_id
     </sql>
 
     <select id="selectInspectionTaskList" parameterType="InspectionTask" resultMap="InspectionTaskResult">
         <include refid="selectInspectionTaskVo"/>
-        <where>  
+        <where>
             <if test="taskName != null  and taskName != ''"> and task_name like concat('%', #{taskName}, '%')</if>
             <if test="deviceId != null"> and device_id = #{deviceId}</if>
-            <if test="deviceName != null  and deviceName != ''"> and device_name like concat('%', #{deviceName}, '%')</if>
+            <if test="deviceName != null  and deviceName != ''"> and d.device_name like concat('%', #{deviceName}, '%')</if>
             <if test="status != null  and status != ''"> and status = #{status}</if>
             <if test="enableDetection != null  and enableDetection != ''"> and enable_detection = #{enableDetection}</if>
+            <if test="modelName != null and modelName != ''"> and model_name = #{modelName}</if>
         </where>
         order by create_time desc
     </select>
-        
+
     <select id="selectEnabledInspectionTaskList" resultMap="InspectionTaskResult">
         <include refid="selectInspectionTaskVo"/>
         where status = '0'
@@ -59,7 +67,6 @@ PUBLIC "-//mybatis.org//DTD Mapper 3.0//EN"
         <trim prefix="(" suffix=")" suffixOverrides=",">
             <if test="taskName != null and taskName != ''">task_name,</if>
             <if test="deviceId != null">device_id,</if>
-            <if test="deviceName != null">device_name,</if>
             <if test="cronExpression != null and cronExpression != ''">cron_expression,</if>
             <if test="duration != null">duration,</if>
             <if test="threshold != null">threshold,</if>
@@ -68,6 +75,7 @@ PUBLIC "-//mybatis.org//DTD Mapper 3.0//EN"
             <if test="executeCount != null">execute_count,</if>
             <if test="alarmCount != null">alarm_count,</if>
             <if test="lastExecuteTime != null">last_execute_time,</if>
+            <if test="modelName != null and modelName != ''">model_name,</if>
             <if test="remark != null">remark,</if>
             <if test="createBy != null">create_by,</if>
             create_time
@@ -75,7 +83,6 @@ PUBLIC "-//mybatis.org//DTD Mapper 3.0//EN"
         <trim prefix="values (" suffix=")" suffixOverrides=",">
             <if test="taskName != null and taskName != ''">#{taskName},</if>
             <if test="deviceId != null">#{deviceId},</if>
-            <if test="deviceName != null">#{deviceName},</if>
             <if test="cronExpression != null and cronExpression != ''">#{cronExpression},</if>
             <if test="duration != null">#{duration},</if>
             <if test="threshold != null">#{threshold},</if>
@@ -84,6 +91,7 @@ PUBLIC "-//mybatis.org//DTD Mapper 3.0//EN"
             <if test="executeCount != null">#{executeCount},</if>
             <if test="alarmCount != null">#{alarmCount},</if>
             <if test="lastExecuteTime != null">#{lastExecuteTime},</if>
+            <if test="modelName != null and modelName != ''">#{modelName},</if>
             <if test="remark != null">#{remark},</if>
             <if test="createBy != null">#{createBy},</if>
             sysdate()
@@ -95,7 +103,6 @@ PUBLIC "-//mybatis.org//DTD Mapper 3.0//EN"
         <trim prefix="SET" suffixOverrides=",">
             <if test="taskName != null and taskName != ''">task_name = #{taskName},</if>
             <if test="deviceId != null">device_id = #{deviceId},</if>
-            <if test="deviceName != null">device_name = #{deviceName},</if>
             <if test="cronExpression != null and cronExpression != ''">cron_expression = #{cronExpression},</if>
             <if test="duration != null">duration = #{duration},</if>
             <if test="threshold != null">threshold = #{threshold},</if>
@@ -104,6 +111,7 @@ PUBLIC "-//mybatis.org//DTD Mapper 3.0//EN"
             <if test="executeCount != null">execute_count = #{executeCount},</if>
             <if test="alarmCount != null">alarm_count = #{alarmCount},</if>
             <if test="lastExecuteTime != null">last_execute_time = #{lastExecuteTime},</if>
+            <if test="modelName != null and modelName != ''">model_name = #{modelName},</if>
             <if test="remark != null">remark = #{remark},</if>
             <if test="updateBy != null">update_by = #{updateBy},</if>
             update_time = sysdate()
@@ -112,7 +120,7 @@ PUBLIC "-//mybatis.org//DTD Mapper 3.0//EN"
     </update>
 
     <update id="updateTaskExecuteInfo">
-        update v_inspection_task 
+        update v_inspection_task
         set execute_count = #{executeCount},
             alarm_count = #{alarmCount},
             last_execute_time = sysdate(),
@@ -125,7 +133,7 @@ PUBLIC "-//mybatis.org//DTD Mapper 3.0//EN"
     </delete>
 
     <delete id="deleteInspectionTaskByIds" parameterType="String">
-        delete from v_inspection_task where task_id in 
+        delete from v_inspection_task where task_id in
         <foreach item="taskId" collection="array" open="(" separator="," close=")">
             #{taskId}
         </foreach>