Update Model

Prj-Python/hyperlpr3/common/typedef.py

@@ -72,6 +72,9 @@ class Plate(object):
     def to_result(self):
         return [self.plate_code, self.rec_confidence, self.plate_type, self.det_bound_box.tolist(),]
 
+    def to_full_result(self):
+        return [self.plate_code, self.rec_confidence, self.plate_type, self.det_bound_box.tolist(), self.vertex.tolist()]
+
     def __dict__(self):
         return self.to_dict()
 

Prj-Python/hyperlpr3/hyperlpr3.py

@@ -14,7 +14,8 @@ class LicensePlateCatcher(object):
                  inference: int = INFER_ONNX_RUNTIME,
                  folder: str = _DEFAULT_FOLDER_,
                  detect_level: int = DETECT_LEVEL_LOW,
-                 logger_level: int = 3):
+                 logger_level: int = 3,
+                 full_result: bool = False):
         if inference == INFER_ONNX_RUNTIME:
             from hyperlpr3.inference.multitask_detect import MultiTaskDetectorORT
             from hyperlpr3.inference.recognition import PPRCNNRecognitionORT
@@ -31,7 +32,7 @@ class LicensePlateCatcher(object):
                 raise NotImplemented
             rec = PPRCNNRecognitionORT(join(folder, ort_cfg['rec_model_path']), input_size=(48, 160))
             cls = ClassificationORT(join(folder, ort_cfg['cls_model_path']), input_size=(96, 96))
-            self.pipeline = LPRMultiTaskPipeline(detector=det, recognizer=rec, classifier=cls)
+            self.pipeline = LPRMultiTaskPipeline(detector=det, recognizer=rec, classifier=cls, full_result=full_result)
         else:
             raise NotImplemented
 

Prj-Python/hyperlpr3/inference/pipeline.py

@@ -6,10 +6,11 @@ from hyperlpr3.common.tools_process import *
 
 class LPRMultiTaskPipeline(object):
 
-    def __init__(self, detector, recognizer, classifier):
+    def __init__(self, detector, recognizer, classifier, full_result=False):
         self.detector = detector
         self.recognizer = recognizer
         self.classifier = classifier
+        self.full_result = full_result
 
     def run(self, image: np.ndarray) -> list:
         result = list()
@@ -56,7 +57,10 @@ class LPRMultiTaskPipeline(object):
                         plate_type = GREEN
                 plate = Plate(vertex=land_marks, plate_code=plate_code, det_bound_box=np.asarray(rect),
                               rec_confidence=rec_confidence, dex_bound_confidence=score, plate_type=plate_type)
-                result.append(plate.to_result())
+                if self.full_result:
+                    result.append(plate.to_full_result())
+                else:
+                    result.append(plate.to_result())
 
         return result