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https://github.com/blakeblackshear/frigate.git
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LPR bugfix (#17384)
* ensure image is numpy array * clean up debugging * clean up postprocessor * process raw input as img
This commit is contained in:
Josh Hawkins
GitHub
parent
4ccf61a6d7
commit
4edf0d8cd3
@ -32,10 +32,6 @@ class LicensePlateProcessingMixin:
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def __init__(self, *args, **kwargs):
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super().__init__(*args, **kwargs)
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self.requires_license_plate_detection = (
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"license_plate" not in self.config.objects.all_objects
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)
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self.event_metadata_publisher = EventMetadataPublisher()
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self.ctc_decoder = CTCDecoder()
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@ -312,7 +308,6 @@ class LicensePlateProcessingMixin:
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# get minimum bounding box (rotated rectangle) around the contour and the smallest side length.
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points, min_side = self._get_min_boxes(contour)
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logger.debug(f"min side {index}, {min_side}")
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if min_side < self.min_size:
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continue
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@ -320,7 +315,6 @@ class LicensePlateProcessingMixin:
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points = np.array(points)
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score = self._box_score(output, contour)
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logger.debug(f"box score {index}, {score}")
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if self.box_thresh > score:
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continue
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@ -991,21 +985,21 @@ class LicensePlateProcessingMixin:
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license_plate = self._detect_license_plate(rgb)
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logger.debug(
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f"YOLOv9 LPD inference time: {(datetime.datetime.now().timestamp() - yolov9_start) * 1000:.2f} ms"
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f"{camera}: YOLOv9 LPD inference time: {(datetime.datetime.now().timestamp() - yolov9_start) * 1000:.2f} ms"
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)
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self.__update_yolov9_metrics(
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datetime.datetime.now().timestamp() - yolov9_start
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)
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if not license_plate:
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logger.debug("Detected no license plates in full frame.")
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logger.debug(f"{camera}: Detected no license plates in full frame.")
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return
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license_plate_area = (license_plate[2] - license_plate[0]) * (
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license_plate[3] - license_plate[1]
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)
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if license_plate_area < self.lpr_config.min_area:
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logger.debug("License plate area below minimum threshold.")
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logger.debug(f"{camera}: License plate area below minimum threshold.")
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return
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license_plate_frame = rgb[
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@ -1027,13 +1021,15 @@ class LicensePlateProcessingMixin:
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# don't run for non car objects
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if obj_data.get("label") != "car":
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logger.debug("Not a processing license plate for non car object.")
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logger.debug(
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f"{camera}: Not a processing license plate for non car object."
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)
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return
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# don't run for stationary car objects
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if obj_data.get("stationary") == True:
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logger.debug(
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"Not a processing license plate for a stationary car object."
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f"{camera}: Not a processing license plate for a stationary car object."
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)
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return
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@ -1041,14 +1037,14 @@ class LicensePlateProcessingMixin:
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# that is not a license plate
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if obj_data.get("sub_label") and id not in self.detected_license_plates:
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logger.debug(
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f"Not processing license plate due to existing sub label: {obj_data.get('sub_label')}."
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f"{camera}: Not processing license plate due to existing sub label: {obj_data.get('sub_label')}."
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)
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return
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license_plate: Optional[dict[str, any]] = None
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if self.requires_license_plate_detection:
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logger.debug("Running manual license_plate detection.")
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if "license_plate" not in self.config.cameras[camera].objects.track:
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logger.debug(f"{camera}: Running manual license_plate detection.")
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car_box = obj_data.get("box")
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@ -1071,14 +1067,16 @@ class LicensePlateProcessingMixin:
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yolov9_start = datetime.datetime.now().timestamp()
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license_plate = self._detect_license_plate(car)
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logger.debug(
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f"YOLOv9 LPD inference time: {(datetime.datetime.now().timestamp() - yolov9_start) * 1000:.2f} ms"
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f"{camera}: YOLOv9 LPD inference time: {(datetime.datetime.now().timestamp() - yolov9_start) * 1000:.2f} ms"
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)
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self.__update_yolov9_metrics(
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datetime.datetime.now().timestamp() - yolov9_start
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)
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if not license_plate:
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logger.debug("Detected no license plates for car object.")
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logger.debug(
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f"{camera}: Detected no license plates for car object."
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)
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return
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license_plate_area = max(
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@ -1093,7 +1091,7 @@ class LicensePlateProcessingMixin:
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license_plate_area
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< self.config.cameras[obj_data["camera"]].lpr.min_area * 2
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):
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logger.debug("License plate is less than min_area")
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logger.debug(f"{camera}: License plate is less than min_area")
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return
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license_plate_frame = car[
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@ -1103,7 +1101,7 @@ class LicensePlateProcessingMixin:
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else:
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# don't run for object without attributes
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if not obj_data.get("current_attributes"):
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logger.debug("No attributes to parse.")
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logger.debug(f"{camera}: No attributes to parse.")
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return
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attributes: list[dict[str, any]] = obj_data.get(
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@ -1130,7 +1128,7 @@ class LicensePlateProcessingMixin:
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or area(license_plate_box)
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< self.config.cameras[obj_data["camera"]].lpr.min_area
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):
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logger.debug(f"Invalid license plate box {license_plate}")
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logger.debug(f"{camera}: Invalid license plate box {license_plate}")
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return
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license_plate_frame = cv2.cvtColor(frame, cv2.COLOR_YUV2BGR_I420)
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@ -1184,7 +1182,7 @@ class LicensePlateProcessingMixin:
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)
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logger.debug(
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f"Detected text: {plate} (average confidence: {avg_confidence:.2f}, area: {text_area} pixels)"
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f"{camera}: Detected text: {plate} (average confidence: {avg_confidence:.2f}, area: {text_area} pixels)"
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)
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else:
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logger.debug("No text detected")
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@ -1204,7 +1202,7 @@ class LicensePlateProcessingMixin:
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# Check against minimum confidence threshold
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if avg_confidence < self.lpr_config.recognition_threshold:
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logger.debug(
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f"Average confidence {avg_confidence} is less than threshold ({self.lpr_config.recognition_threshold})"
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f"{camera}: Average confidence {avg_confidence} is less than threshold ({self.lpr_config.recognition_threshold})"
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)
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return
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@ -1223,7 +1221,7 @@ class LicensePlateProcessingMixin:
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if similarity >= self.similarity_threshold:
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plate_id = existing_id
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logger.debug(
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f"Matched plate {top_plate} to {data['plate']} (similarity: {similarity:.3f})"
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f"{camera}: Matched plate {top_plate} to {data['plate']} (similarity: {similarity:.3f})"
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)
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break
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if plate_id is None:
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@ -1231,11 +1229,11 @@ class LicensePlateProcessingMixin:
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obj_data, top_plate, avg_confidence
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)
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logger.debug(
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f"New plate event for dedicated LPR camera {plate_id}: {top_plate}"
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f"{camera}: New plate event for dedicated LPR camera {plate_id}: {top_plate}"
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)
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else:
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logger.debug(
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f"Matched existing plate event for dedicated LPR camera {plate_id}: {top_plate}"
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f"{camera}: Matched existing plate event for dedicated LPR camera {plate_id}: {top_plate}"
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)
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self.detected_license_plates[plate_id]["last_seen"] = current_time
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@ -1246,7 +1244,7 @@ class LicensePlateProcessingMixin:
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if self._should_keep_previous_plate(
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id, top_plate, top_char_confidences, top_area, avg_confidence
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):
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logger.debug("Keeping previous plate")
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logger.debug(f"{camera}: Keeping previous plate")
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return
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# Determine subLabel based on known plates, use regex matching
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@ -1277,7 +1275,9 @@ class LicensePlateProcessingMixin:
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if dedicated_lpr:
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# save the best snapshot
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logger.debug(f"Writing snapshot for {id}, {top_plate}, {current_time}")
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logger.debug(
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f"{camera}: Writing snapshot for {id}, {top_plate}, {current_time}"
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)
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frame_bgr = cv2.cvtColor(frame, cv2.COLOR_YUV2BGR_I420)
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self.sub_label_publisher.publish(
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EventMetadataTypeEnum.save_lpr_snapshot,
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@ -139,7 +139,7 @@ class LicensePlatePostProcessor(LicensePlateProcessingMixin, PostProcessorApi):
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scale_y = image.shape[0] / detect_height
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# Determine which box to enlarge based on detection mode
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if self.requires_license_plate_detection:
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if "license_plate" not in self.config.cameras[camera_name].objects.track:
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# Scale and enlarge the car box
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box = obj_data.get("box")
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if not box:
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@ -189,7 +189,7 @@ class LicensePlatePostProcessor(LicensePlateProcessingMixin, PostProcessorApi):
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)
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keyframe_obj_data = obj_data.copy()
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if self.requires_license_plate_detection:
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if "license_plate" not in self.config.cameras[camera_name].objects.track:
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# car box
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keyframe_obj_data["box"] = [new_left, new_top, new_right, new_bottom]
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else:
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@ -261,8 +261,8 @@ class LicensePlateDetector(BaseEmbedding):
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def _preprocess_inputs(self, raw_inputs):
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if isinstance(raw_inputs, list):
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raise ValueError("License plate embedding does not support batch inputs.")
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# Get image as numpy array
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img = self._process_image(raw_inputs)
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img = raw_inputs
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height, width, channels = img.shape
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# Resize maintaining aspect ratio
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