improve motion detection during autotracking

frigate/motion/improved_motion.py

@@ -5,6 +5,7 @@ import imutils
 import numpy as np
 from scipy.ndimage import gaussian_filter
 
+from frigate.camera import PTZMetrics
 from frigate.comms.config_updater import ConfigSubscriber
 from frigate.config import MotionConfig
 from frigate.motion import MotionDetector
@@ -18,6 +19,7 @@ class ImprovedMotionDetector(MotionDetector):
         frame_shape,
         config: MotionConfig,
         fps: int,
+        ptz_metrics: PTZMetrics = None,
         name="improved",
         blur_radius=1,
         interpolation=cv2.INTER_NEAREST,
@@ -48,6 +50,8 @@ class ImprovedMotionDetector(MotionDetector):
         self.contrast_values[:, 1:2] = 255
         self.contrast_values_index = 0
         self.config_subscriber = ConfigSubscriber(f"config/motion/{name}")
+        self.ptz_metrics = ptz_metrics
+        self.last_stop_time = None
 
     def is_calibrating(self):
         return self.calibrating
@@ -64,6 +68,21 @@ class ImprovedMotionDetector(MotionDetector):
         if not self.config.enabled:
             return motion_boxes
 
+        # if ptz motor is moving from autotracking, quickly return
+        # a single box that is 80% of the frame
+        if (
+            self.ptz_metrics.autotracker_enabled.value
+            and not self.ptz_metrics.motor_stopped.is_set()
+        ):
+            return [
+                (
+                    int(self.frame_shape[1] * 0.1),
+                    int(self.frame_shape[0] * 0.1),
+                    int(self.frame_shape[1] * 0.9),
+                    int(self.frame_shape[0] * 0.9),
+                )
+            ]
+
         gray = frame[0 : self.frame_shape[0], 0 : self.frame_shape[1]]
 
         # resize frame
@@ -151,6 +170,25 @@ class ImprovedMotionDetector(MotionDetector):
             self.motion_frame_size[0] * self.motion_frame_size[1]
         )
 
+        # check if the motor has just stopped from autotracking
+        # if so, reassign the average to the current frame so we begin with a new baseline
+        if (
+            # ensure we only do this for cameras with autotracking enabled
+            self.ptz_metrics.autotracker_enabled.value
+            and self.ptz_metrics.motor_stopped.is_set()
+            and (
+                self.last_stop_time is None
+                or self.ptz_metrics.stop_time.value != self.last_stop_time
+            )
+            # value is 0 on startup or when motor is moving
+            and self.ptz_metrics.stop_time.value != 0
+        ):
+            self.last_stop_time = self.ptz_metrics.stop_time.value
+
+            self.avg_frame = resized_frame.astype(np.float32)
+            motion_boxes = []
+            pct_motion = 0
+
         # once the motion is less than 5% and the number of contours is < 4, assume its calibrated
         if pct_motion < 0.05 and len(motion_boxes) <= 4:
             self.calibrating = False

frigate/ptz/onvif.py

@@ -465,7 +465,6 @@ class OnvifController:
             return
 
         self.cams[camera_name]["active"] = True
-        self.ptz_metrics[camera_name].motor_stopped.clear()
         self.ptz_metrics[camera_name].start_time.value = 0
         self.ptz_metrics[camera_name].stop_time.value = 0
         move_request = self.cams[camera_name]["move_request"]

frigate/track/norfair_tracker.py

@@ -94,7 +94,6 @@ def histogram_distance(matched_not_init_trackers, unmatched_trackers):
         distance = 1 - cv2.compareHist(
             snd_embedding, detection_fst.embedding, cv2.HISTCMP_CORREL
         )
-        print("ReID distance", distance)
         if distance < 0.5:
             return distance
     return 1
@@ -220,7 +219,6 @@ class NorfairTracker(ObjectTracker):
                     )
                     is None
                 ):
-                    print("adding reid keys for ptz: ", obj_type)
                     reid_keys = [
                         "past_detections_length",
                         "reid_distance_function",
@@ -604,7 +602,9 @@ class NorfairTracker(ObjectTracker):
         # Collect all tracked objects from each tracker
         all_tracked_objects = []
 
-        self.print_objects_as_table(self.trackers["person"]["ptz"].tracked_objects)
+        # print a table to the console with norfair tracked object info
+        if False:
+            self.print_objects_as_table(self.trackers["person"]["ptz"].tracked_objects)
 
         # Get tracked objects from type-specific trackers
         for object_trackers in self.trackers.values():

frigate/video.py

@@ -436,7 +436,11 @@ def track_camera(
     object_filters = config.objects.filters
 
     motion_detector = ImprovedMotionDetector(
-        frame_shape, config.motion, config.detect.fps, name=config.name
+        frame_shape,
+        config.motion,
+        config.detect.fps,
+        name=config.name,
+        ptz_metrics=ptz_metrics,
     )
     object_detector = RemoteObjectDetector(
         name, labelmap, detection_queue, result_connection, model_config, stop_event