feat: TensorRT 固定 batch=4 重构

- tensorrt_engine.py 工业级 Buffer Pool
- preprocessor.py 添加 pad_to_batch4()
- postprocessor.py 支持批量输出
- settings.py 固定 batch_size=4

check_engine.py

@@ -0,0 +1,43 @@
+"""检查 TensorRT Engine 的实际 shape"""
+import sys
+import os
+sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+try:
+    import tensorrt as trt
+    
+    engine_path = "./models/yolo11n.engine"
+    
+    with open(engine_path, "rb") as f:
+        runtime = trt.Runtime(trt.Logger(trt.Logger.WARNING))
+        engine = runtime.deserialize_cuda_engine(f.read())
+    
+    print("=" * 60)
+    print("Engine Binding Information")
+    print("=" * 60)
+    
+    for i in range(engine.num_bindings):
+        name = engine.get_binding_name(i)
+        shape = engine.get_binding_shape(i)
+        dtype = trt.nptype(engine.get_binding_dtype(i))
+        is_input = engine.binding_is_input(i)
+        
+        size = trt.volume(shape)
+        
+        print(f"\nBinding {i}:")
+        print(f"  Name: {name}")
+        print(f"  Shape: {shape}")
+        print(f"  Dtype: {dtype}")
+        print(f"  Size: {size}")
+        print(f"  Is Input: {is_input}")
+        
+        if is_input:
+            print(f"  Total Elements: {size}")
+            print(f"  Expected Batch Size: {shape[0] if len(shape) > 0 else 'N/A'}")
+    
+    print("\n" + "=" * 60)
+    
+except Exception as e:
+    print(f"Error: {e}")
+    import traceback
+    traceback.print_exc()