Fix DataProcessor missing class error in pipeline deployment

- Add DataProcessor abstract base class with process method
- Add PostProcessor class for handling inference output data
- Fix PreProcessor inheritance from DataProcessor
- Resolves "name 'DataProcessor' is not defined" error during pipeline deployment

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

cluster4npu_ui/core/functions/Multidongle.py

@@ -13,7 +13,16 @@ from abc import ABC, abstractmethod
 from typing import Callable, Optional, Any, Dict
 
 
-class PreProcessor(DataProcessor): # type: ignore
+class DataProcessor(ABC):
+    """Abstract base class for data processors in the pipeline"""
+    
+    @abstractmethod
+    def process(self, data: Any, *args, **kwargs) -> Any:
+        """Process data and return result"""
+        pass
+
+
+class PreProcessor(DataProcessor):
     def __init__(self, resize_fn: Optional[Callable] = None, 
                  format_convert_fn: Optional[Callable] = None):
         self.resize_fn = resize_fn or self._default_resize
@@ -36,6 +45,22 @@ class PreProcessor(DataProcessor): # type: ignore
             return cv2.cvtColor(frame, cv2.COLOR_BGR2RGBA)
         return frame
 
+
+class PostProcessor(DataProcessor):
+    """Post-processor for handling output data from inference stages"""
+    
+    def __init__(self, process_fn: Optional[Callable] = None):
+        self.process_fn = process_fn or self._default_process
+    
+    def process(self, data: Any, *args, **kwargs) -> Any:
+        """Process inference output data"""
+        return self.process_fn(data, *args, **kwargs)
+    
+    def _default_process(self, data: Any, *args, **kwargs) -> Any:
+        """Default post-processing - returns data unchanged"""
+        return data
+
+
 class MultiDongle:
     # Curently, only BGR565, RGB8888, YUYV, and RAW8 formats are supported
     _FORMAT_MAPPING = {