Improve ALPR_OCR peformance

modules/ANSOCR/ANSONNXOCR/PaddleOCRV5Engine.h

@@ -25,10 +25,13 @@ public:
 
     // Initialize the OCR pipeline
     // clsModelPath can be empty to skip classification
+    // preferTensorRT: try TensorRT EP first for the three sub-models
+    //                 (cuDNN-friendly cuDNN max-workspace mode either way)
     bool Initialize(const std::string& detModelPath,
                     const std::string& clsModelPath,
                     const std::string& recModelPath,
-                    const std::string& dictPath);
+                    const std::string& dictPath,
+                    bool preferTensorRT = false);
 
     // Run full OCR pipeline on an image
     // Returns results matching PaddleOCR::OCRPredictResult format
@@ -37,6 +40,14 @@ public:
     // Run recognizer only on a pre-cropped text image (no detection step)
     TextLine recognizeOnly(const cv::Mat& croppedImage);
 
+    // Run recognizer only on a batch of pre-cropped text images in a
+    // single batched ORT inference. Skips the detector entirely — the
+    // caller is expected to supply crops that are already roughly
+    // axis-aligned single-line text (e.g. ALPR plate ROIs, optionally
+    // pre-split into rows). Crops are grouped by bucket width, so a
+    // single call to this function typically issues 1–2 ORT Runs total.
+    std::vector<TextLine> recognizeMany(const std::vector<cv::Mat>& croppedImages);
+
     // Configuration setters (matching OCRModelConfig parameters)
     void SetDetMaxSideLen(int val)          { _maxSideLen = val; }
     void SetDetDbThresh(float val)          { _detDbThresh = val; }