LPR tweaks (#17783)

* clarify docs

* improve debugging messages

* don't run any lpr postprocessing

* wording
This commit is contained in:
Josh Hawkins 2025-04-18 08:45:37 -05:00 committed by GitHub
parent 19aaa64fe9
commit 14a32a6472
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
5 changed files with 37 additions and 14 deletions

View File

@ -184,7 +184,7 @@ cameras:
ffmpeg: ... # add your streams
detect:
enabled: True
fps: 5 # increase to 10 if vehicles move quickly across your frame. Higher than 10 is unnecessary and is not recommended.
fps: 5 # increase to 10 if vehicles move quickly across your frame. Higher than 15 is unnecessary and is not recommended.
min_initialized: 2
width: 1920
height: 1080
@ -267,7 +267,7 @@ With this setup:
- Review items will always be classified as a `detection`.
- Snapshots will always be saved.
- Zones and object masks are **not** used.
- The `frigate/events` MQTT topic will **not** publish tracked object updates, though `frigate/reviews` will if recordings are enabled.
- The `frigate/events` MQTT topic will **not** publish tracked object updates with the license plate bounding box and score, though `frigate/reviews` will publish if recordings are enabled. If a plate is recognized as a known plate, publishing will occur with an updated `sub_label` field. If characters are recognized, publishing will occur with an updated `recognized_license_plate` field.
- License plate snapshots are saved at the highest-scoring moment and appear in Explore.
- Debug view will not show `license_plate` bounding boxes.
@ -280,7 +280,7 @@ With this setup:
| Object Detection | Standard Frigate+ detection applies | Bypasses standard object detection |
| Zones & Object Masks | Supported | Not supported |
| Debug View | May show `license_plate` bounding boxes | May **not** show `license_plate` bounding boxes |
| MQTT `frigate/events` | Publishes tracked object updates | Does **not** publish tracked object updates |
| MQTT `frigate/events` | Publishes tracked object updates | Publishes limited updates |
| Explore | Recognized plates available in More Filters | Recognized plates available in More Filters |
By selecting the appropriate configuration, users can optimize their dedicated LPR cameras based on whether they are using a Frigate+ model or the secondary LPR pipeline.

View File

@ -513,10 +513,14 @@ class FrigateConfig(FrigateBaseModel):
)
# Warn if detect fps > 10
if camera_config.detect.fps > 10:
if camera_config.detect.fps > 10 and camera_config.type != "lpr":
logger.warning(
f"{camera_config.name} detect fps is set to {camera_config.detect.fps}. This does NOT need to match your camera's frame rate. High values could lead to reduced performance. Recommended value is 5."
)
if camera_config.detect.fps > 15 and camera_config.type == "lpr":
logger.warning(
f"{camera_config.name} detect fps is set to {camera_config.detect.fps}. This does NOT need to match your camera's frame rate. High values could lead to reduced performance. Recommended value for LPR cameras are between 5-15."
)
# Default min_initialized configuration
min_initialized = int(camera_config.detect.fps / 2)

View File

@ -490,10 +490,6 @@ class LicensePlateProcessingMixin:
merged_boxes.append(current_box)
current_box = next_box
logger.debug(
f"Provided plate_width: {plate_width}, max_gap: {max_gap}, horizontal_gap: {horizontal_gap}"
)
# Add the last box
merged_boxes.append(current_box)
@ -1133,7 +1129,7 @@ class LicensePlateProcessingMixin:
# 4. Log the comparison
logger.debug(
f"Plate comparison - Current: {top_plate} (score: {curr_score:.3f}, min_conf: {curr_min_conf:.2f}) vs "
f"Previous: {prev_plate} (score: {prev_score:.3f}, min_conf: {prev_min_conf:.2f})\n"
f"Previous: {prev_plate} (score: {prev_score:.3f}, min_conf: {prev_min_conf:.2f}) "
f"Metrics - Length: {len(top_plate)} vs {len(prev_plate)} (scores: {curr_length_score:.2f} vs {prev_length_score:.2f}), "
f"Area: {top_area} vs {prev_area}, "
f"Avg Conf: {avg_confidence:.2f} vs {prev_avg_confidence:.2f}, "
@ -1263,6 +1259,15 @@ class LicensePlateProcessingMixin:
)
return
# don't run for objects with no position changes
# this is the initial state after registering a new tracked object
# LPR will run 2 frames after detect.min_initialized is reached
if obj_data.get("position_changes", 0) == 0:
logger.debug(
f"{camera}: Plate detected in {self.config.cameras[camera].detect.min_initialized + 1} concurrent frames, LPR frame threshold ({self.config.cameras[camera].detect.min_initialized + 2})"
)
return
license_plate: Optional[dict[str, any]] = None
if "license_plate" not in self.config.cameras[camera].objects.track:
@ -1401,6 +1406,8 @@ class LicensePlateProcessingMixin:
license_plate_frame,
)
logger.debug(f"{camera}: Running plate recognition.")
# run detection, returns results sorted by confidence, best first
start = datetime.datetime.now().timestamp()
license_plates, confidences, areas = self._process_license_plate(

View File

@ -54,6 +54,9 @@ class LicensePlatePostProcessor(LicensePlateProcessingMixin, PostProcessorApi):
Returns:
None.
"""
# don't run LPR post processing for now
return
event_id = data["event_id"]
camera_name = data["camera"]

View File

@ -138,11 +138,13 @@ class TrackedObject:
if not self.false_positive and has_valid_frame:
# determine if this frame is a better thumbnail
if self.thumbnail_data is None or is_better_thumbnail(
self.obj_data["label"],
self.thumbnail_data,
obj_data,
self.camera_config.frame_shape,
if self.thumbnail_data is None or (
better_thumb := is_better_thumbnail(
self.obj_data["label"],
self.thumbnail_data,
obj_data,
self.camera_config.frame_shape,
)
):
# use the current frame time if the object's frame time isn't in the frame cache
selected_frame_time = (
@ -150,6 +152,13 @@ class TrackedObject:
if obj_data["frame_time"] not in self.frame_cache.keys()
else obj_data["frame_time"]
)
if (
obj_data["frame_time"] not in self.frame_cache.keys()
and not better_thumb
):
logger.warning(
f"Frame time {obj_data['frame_time']} not in frame cache, using current frame time {selected_frame_time}"
)
self.thumbnail_data = {
"frame_time": selected_frame_time,
"box": obj_data["box"],