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fixes

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This commit is contained in:
Weitheng Haw 2025-02-04 01:52:37 +00:00
parent c58d875a01
commit 7801ff44d2
3 changed files with 9 additions and 8 deletions
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7
frigate/embeddings/lpr/lpr.py
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@ -144,13 +144,14 @@ class LicensePlateRecognition:
return self.ctc_decoder(outputs) return self.ctc_decoder(outputs)
def process_license_plate( def process_license_plate(
self, image: np.ndarray self, image: np.ndarray, event_id: str = ""
) -> Tuple[List[str], List[float], List[int]]: ) -> Tuple[List[str], List[float], List[int]]:
""" """
Complete pipeline for detecting, classifying, and recognizing license plates in the input image. Complete pipeline for detecting, classifying, and recognizing license plates in the input image.
Args: Args:
image (np.ndarray): The input image in which to detect, classify, and recognize license plates. image (np.ndarray): The input image in which to detect, classify, and recognize license plates.
event_id (str): The ID of the event associated with this license plate detection.
Returns: Returns:
Tuple[List[str], List[float], List[int]]: Detected license plate texts, confidence scores, and areas of the plates. Tuple[List[str], List[float], List[int]]: Detected license plate texts, confidence scores, and areas of the plates.
@ -193,14 +194,14 @@ class LicensePlateRecognition:
area = height * width area = height * width
average_confidence = conf average_confidence = conf
avg_confidence = sum(average_confidence) / len(average_confidence) if average_confidence else 0
# Save debug image # Save debug image
try: try:
save_image = cv2.cvtColor( save_image = cv2.cvtColor(
rotated_images[original_idx], cv2.COLOR_RGB2BGR rotated_images[original_idx], cv2.COLOR_RGB2BGR
) )
confidence_value = average_confidence[0] if average_confidence and len(average_confidence) > 0 else 0 filename = f"{plate}_{int(avg_confidence * 100)}_{event_id}.jpg" if event_id else f"{plate}_{int(avg_confidence * 100)}.jpg"
filename = f"{plate}_{int(confidence_value * 100)}_{area}.jpg"
cv2.imwrite(os.path.join(self.debug_dir, filename), save_image) cv2.imwrite(os.path.join(self.debug_dir, filename), save_image)
except Exception as e: except Exception as e:
logger.warning(f"Failed to save debug image: {e}") logger.warning(f"Failed to save debug image: {e}")

2
frigate/embeddings/maintainer.py
View File

@ -443,7 +443,7 @@ class EmbeddingMaintainer(threading.Thread):
# run detection, returns results sorted by confidence, best first # run detection, returns results sorted by confidence, best first
license_plates, confidences, areas = ( license_plates, confidences, areas = (
self.license_plate_recognition.process_license_plate(license_plate_frame) self.license_plate_recognition.process_license_plate(license_plate_frame, id)
) )
logger.debug(f"Text boxes: {license_plates}") logger.debug(f"Text boxes: {license_plates}")

8
web/src/pages/LPRDebug.tsx
View File

@ -157,11 +157,11 @@ type LPRAttemptProps = {
function LPRAttempt({ attempt, config, onRefresh }: LPRAttemptProps) { function LPRAttempt({ attempt, config, onRefresh }: LPRAttemptProps) {
const [showDialog, setShowDialog] = useState(false); const [showDialog, setShowDialog] = useState(false);
const data = useMemo(() => { const data = useMemo(() => {
const parts = attempt.split("-"); const parts = attempt.split("_");
return { return {
eventId: `${parts[0]}-${parts[1]}`, plate: parts[0] || "Text not extracted",
plate: parts[2] || "Text not extracted", score: parts[1] || "0",
score: parts[3] || "0", eventId: parts[2]?.replace(".jpg", "") || null,
}; };
}, [attempt]); }, [attempt]);