Fixes (#18245)

* Only check if an object is stationary to avoid mqtt snapshot

* docs heading tweak

* Add more API descriptions

* Add missing lib for new rocm onnxruntime whl

* Update inference times to reflect better rocm performance

* Cleanup resetting tracked object activity

* remove print

---------

Co-authored-by: Josh Hawkins <32435876+hawkeye217@users.noreply.github.com>

docker/rocm/Dockerfile

@@ -22,7 +22,7 @@ RUN apt update && \
 
 RUN mkdir -p /opt/rocm-dist/opt/rocm-$ROCM/lib
 RUN cd /opt/rocm-$ROCM/lib && \
-    cp -dpr libMIOpen*.so* libamd*.so* libhip*.so* libhsa*.so* libmigraphx*.so* librocm*.so* librocblas*.so* libroctracer*.so* librocfft*.so* librocprofiler*.so* libroctx*.so* /opt/rocm-dist/opt/rocm-$ROCM/lib/ && \
+    cp -dpr libMIOpen*.so* libamd*.so* libhip*.so* libhsa*.so* libmigraphx*.so* librocm*.so* librocblas*.so* libroctracer*.so* librocsolver*.so* librocfft*.so* librocprofiler*.so* libroctx*.so* /opt/rocm-dist/opt/rocm-$ROCM/lib/ && \
     mkdir -p /opt/rocm-dist/opt/rocm-$ROCM/lib/migraphx/lib && \
     cp -dpr migraphx/lib/* /opt/rocm-dist/opt/rocm-$ROCM/lib/migraphx/lib
 RUN cd /opt/rocm-dist/opt/ && ln -s rocm-$ROCM rocm

docs/docs/configuration/face_recognition.md

@@ -172,6 +172,6 @@ Face recognition does not run on the recording stream, this would be suboptimal
 
 By default iOS devices will use HEIC (High Efficiency Image Container) for images, but this format is not supported for uploads. Choosing `large` as the format instead of `original` will use JPG which will work correctly.
 
-## How can I delete the face database and start over?
+### How can I delete the face database and start over?
 
 Frigate does not store anything in its database related to face recognition. You can simply delete all of your faces through the Frigate UI or remove the contents of the `/media/frigate/clips/faces` directory.

docs/docs/frigate/hardware.md

@@ -145,7 +145,7 @@ With the [rocm](../configuration/object_detectors.md#amdrocm-gpu-detector) detec
 
 | Name      | YOLOv9 Inference Time | YOLO-NAS Inference Time   |
 | --------- | --------------------- | ------------------------- |
-| AMD 780M  | ~ 14 ms               | 320: ~ 30 ms 640: ~ 60 ms |
+| AMD 780M  | ~ 14 ms               | 320: ~ 25 ms 640: ~ 50 ms |
 | AMD 8700G |                       | 320: ~ 20 ms 640: ~ 40 ms |
 
 ## Community Supported Detectors

frigate/api/media.py

@@ -640,7 +640,10 @@ def recording_clip(
     )
 
 
-@router.get("/vod/{camera_name}/start/{start_ts}/end/{end_ts}")
+@router.get(
+    "/vod/{camera_name}/start/{start_ts}/end/{end_ts}",
+    description="Returns an HLS playlist for the specified timestamp-range on the specified camera. Append /master.m3u8 or /index.m3u8 for HLS playback.",
+)
 def vod_ts(camera_name: str, start_ts: float, end_ts: float):
     recordings = (
         Recordings.select(
@@ -714,7 +717,10 @@ def vod_ts(camera_name: str, start_ts: float, end_ts: float):
     )
 
 
-@router.get("/vod/{year_month}/{day}/{hour}/{camera_name}")
+@router.get(
+    "/vod/{year_month}/{day}/{hour}/{camera_name}",
+    description="Returns an HLS playlist for the specified date-time on the specified camera. Append /master.m3u8 or /index.m3u8 for HLS playback.",
+)
 def vod_hour_no_timezone(year_month: str, day: int, hour: int, camera_name: str):
     """VOD for specific hour. Uses the default timezone (UTC)."""
     return vod_hour(
@@ -722,7 +728,10 @@ def vod_hour_no_timezone(year_month: str, day: int, hour: int, camera_name: str)
     )
 
 
-@router.get("/vod/{year_month}/{day}/{hour}/{camera_name}/{tz_name}")
+@router.get(
+    "/vod/{year_month}/{day}/{hour}/{camera_name}/{tz_name}",
+    description="Returns an HLS playlist for the specified date-time (with timezone) on the specified camera. Append /master.m3u8 or /index.m3u8 for HLS playback.",
+)
 def vod_hour(year_month: str, day: int, hour: int, camera_name: str, tz_name: str):
     parts = year_month.split("-")
     start_date = (
@@ -736,7 +745,10 @@ def vod_hour(year_month: str, day: int, hour: int, camera_name: str, tz_name: st
     return vod_ts(camera_name, start_ts, end_ts)
 
 
-@router.get("/vod/event/{event_id}")
+@router.get(
+    "/vod/event/{event_id}",
+    description="Returns an HLS playlist for the specified object. Append /master.m3u8 or /index.m3u8 for HLS playback.",
+)
 def vod_event(event_id: str):
     try:
         event: Event = Event.get(Event.id == event_id)

frigate/data_processing/common/license_plate/mixin.py

@@ -1570,10 +1570,26 @@ class LicensePlateProcessingMixin:
     def handle_request(self, topic, request_data) -> dict[str, Any] | None:
         return
 
-    def expire_object(self, object_id: str, camera: str):
+    def lpr_expire(self, object_id: str, camera: str):
         if object_id in self.detected_license_plates:
             self.detected_license_plates.pop(object_id)
 
+            if object_id in self.camera_current_cars.get(camera, []):
+                self.camera_current_cars[camera].remove(object_id)
+
+                if len(self.camera_current_cars[camera]) == 0:
+                    self.requestor.send_data(
+                        "tracked_object_update",
+                        json.dumps(
+                            {
+                                "type": TrackedObjectUpdateTypesEnum.lpr,
+                                "name": None,
+                                "plate": None,
+                                "camera": camera,
+                            }
+                        ),
+                    )
+
 
 class CTCDecoder:
     """

frigate/data_processing/real_time/face.py

@@ -293,10 +293,11 @@ class FaceRealTimeProcessor(RealTimeProcessorApi):
             if camera not in self.camera_current_people:
                 self.camera_current_people[camera] = []
 
+            self.camera_current_people[camera].append(id)
+
         self.person_face_history[id].append(
             (sub_label, score, face_frame.shape[0] * face_frame.shape[1])
         )
-        self.camera_current_people[camera].append(id)
         (weighted_sub_label, weighted_score) = self.weighted_average(
             self.person_face_history[id]
         )

frigate/data_processing/real_time/license_plate.py

@@ -1,6 +1,5 @@
 """Handle processing images for face detection and recognition."""
 
-import json
 import logging
 from typing import Any
 
@@ -15,7 +14,6 @@ from frigate.data_processing.common.license_plate.mixin import (
 from frigate.data_processing.common.license_plate.model import (
     LicensePlateModelRunner,
 )
-from frigate.types import TrackedObjectUpdateTypesEnum
 
 from ..types import DataProcessorMetrics
 from .api import RealTimeProcessorApi
@@ -55,21 +53,5 @@ class LicensePlateRealTimeProcessor(LicensePlateProcessingMixin, RealTimeProcess
         return
 
     def expire_object(self, object_id: str, camera: str):
-        if object_id in self.detected_license_plates:
-            self.detected_license_plates.pop(object_id)
-
-            if object_id in self.camera_current_cars.get(camera, []):
-                self.camera_current_cars[camera].remove(object_id)
-
-                if len(self.camera_current_cars[camera]) == 0:
-                    self.requestor.send_data(
-                        "tracked_object_update",
-                        json.dumps(
-                            {
-                                "type": TrackedObjectUpdateTypesEnum.lpr,
-                                "name": None,
-                                "plate": None,
-                                "camera": camera,
-                            }
-                        ),
-                    )
+        """Expire lpr objects."""
+        self.lpr_expire(object_id, camera)

frigate/track/object_processing.py

@@ -249,7 +249,7 @@ class TrackedObjectProcessor(threading.Thread):
 
     def should_mqtt_snapshot(self, camera, obj: TrackedObject):
         # object never changed position
-        if obj.obj_data["position_changes"] == 0:
+        if obj.is_stationary():
             return False
 
         # if there are required zones and there is no overlap

frigate/track/tracked_object.py

@@ -384,16 +384,16 @@ class TrackedObject:
 
         return event
 
-    def is_active(self):
+    def is_active(self) -> bool:
         return not self.is_stationary()
 
-    def is_stationary(self):
+    def is_stationary(self) -> bool:
         return (
             self.obj_data["motionless_count"]
             > self.camera_config.detect.stationary.threshold
         )
 
-    def get_thumbnail(self, ext: str):
+    def get_thumbnail(self, ext: str) -> bytes | None:
         img_bytes = self.get_img_bytes(
             ext, timestamp=False, bounding_box=False, crop=True, height=175
         )
@@ -404,7 +404,7 @@ class TrackedObject:
             _, img = cv2.imencode(f".{ext}", np.zeros((175, 175, 3), np.uint8))
             return img.tobytes()
 
-    def get_clean_png(self):
+    def get_clean_png(self) -> bytes | None:
         if self.thumbnail_data is None:
             return None
 
@@ -433,7 +433,7 @@ class TrackedObject:
         crop=False,
         height: int | None = None,
         quality: int | None = None,
-    ):
+    ) -> bytes | None:
         if self.thumbnail_data is None:
             return None