Init license plate pipeline

open_image_models/detection/pipeline/license_plate.py

@@ -0,0 +1,50 @@
+"""
+License Plate object detection pipeline.
+"""
+
+import logging
+from collections.abc import Sequence
+
+import onnxruntime as ort
+
+from open_image_models.detection.core.hub import PlateDetectorModel, download_model
+from open_image_models.detection.core.yolo_v9.inference import YoloV9ObjectDetector
+
+# Setup logging
+LOGGER = logging.getLogger(__name__)
+LOGGER.setLevel(logging.INFO)
+
+
+class LicensePlateDetector(YoloV9ObjectDetector):
+    """
+    Specialized detector for license plates using YoloV9 model.
+    Inherits from YoloV9ObjectDetector and sets up license plate specific configuration.
+    """
+
+    def __init__(
+        self,
+        detection_model: PlateDetectorModel,
+        conf_thresh: float = 0.25,
+        providers: Sequence[str | tuple[str, dict]] | None = None,
+        sess_options: ort.SessionOptions = None,
+    ) -> None:
+        """
+        Initializes the LicensePlateDetector with the specified detection model and inference device.
+
+        Args:
+            detection_model: Detection model to use, see `PlateDetectorModel`.
+            conf_thresh: Confidence threshold for filtering predictions.
+            providers: Optional sequence of providers in order of decreasing precedence. If not specified, all available
+            providers are used.
+            sess_options: Advanced session options for ONNX Runtime.
+        """
+        # Download model if needed
+        detector_model_path = download_model(detection_model)
+        super().__init__(
+            model_path=detector_model_path,
+            conf_thresh=conf_thresh,
+            class_labels=["License Plate"],
+            providers=providers,
+            sess_options=sess_options,
+        )
+        LOGGER.info("Initialized LicensePlateDetector with model %s", detector_model_path)