add zoom time to movement predictions

This commit is contained in:
Josh Hawkins 2025-04-27 14:06:35 -05:00
parent eb4433162c
commit 9eb87e2f44
2 changed files with 42 additions and 7 deletions

View File

@ -63,9 +63,9 @@ class PtzAutotrackConfig(FrigateBaseModel):
else:
raise ValueError("Invalid type for movement_weights")
if len(weights) != 5:
if len(weights) != 6:
raise ValueError(
"movement_weights must have exactly 5 floats, remove this line from your config and run autotracking calibration"
"movement_weights must have exactly 6 floats, remove this line from your config and run autotracking calibration"
)
return weights

View File

@ -206,6 +206,7 @@ class PtzAutoTracker:
self.calibrating: dict[str, object] = {}
self.intercept: dict[str, object] = {}
self.move_coefficients: dict[str, object] = {}
self.zoom_time: dict[str, float] = {}
self.zoom_factor: dict[str, object] = {}
# if cam is set to autotrack, onvif should be set up
@ -292,7 +293,7 @@ class PtzAutoTracker:
self.move_threads[camera].start()
if camera_config.onvif.autotracking.movement_weights:
if len(camera_config.onvif.autotracking.movement_weights) == 5:
if len(camera_config.onvif.autotracking.movement_weights) == 6:
camera_config.onvif.autotracking.movement_weights = [
float(val)
for val in camera_config.onvif.autotracking.movement_weights
@ -311,7 +312,10 @@ class PtzAutoTracker:
camera_config.onvif.autotracking.movement_weights[2]
)
self.move_coefficients[camera] = (
camera_config.onvif.autotracking.movement_weights[3:]
camera_config.onvif.autotracking.movement_weights[3:5]
)
self.zoom_time[camera] = (
camera_config.onvif.autotracking.movement_weights[5]
)
else:
camera_config.onvif.autotracking.enabled = False
@ -362,6 +366,7 @@ class PtzAutoTracker:
logger.info(f"Calibration for {camera} in progress: 0% complete")
for i in range(2):
start_time = time.time()
# absolute move to 0 - fully zoomed out
self.onvif._zoom_absolute(
camera,
@ -384,6 +389,9 @@ class PtzAutoTracker:
self.onvif.get_camera_status(camera)
zoom_in_values.append(self.ptz_metrics[camera].zoom_level.value)
stop_time = time.time()
self.zoom_time[camera] = stop_time - start_time
if (
self.config.cameras[camera].onvif.autotracking.zooming
@ -421,12 +429,13 @@ class PtzAutoTracker:
self.ptz_metrics[camera].min_zoom.value = min(zoom_out_values)
logger.debug(
f"{camera}: Calibration values: max zoom: {self.ptz_metrics[camera].max_zoom.value}, min zoom: {self.ptz_metrics[camera].min_zoom.value}"
f"{camera}: Calibration values: max zoom: {self.ptz_metrics[camera].max_zoom.value}, min zoom: {self.ptz_metrics[camera].min_zoom.value}, zoom time: {self.zoom_time[camera]}"
)
else:
self.ptz_metrics[camera].max_zoom.value = 1
self.ptz_metrics[camera].min_zoom.value = 0
self.zoom_time[camera] = 0
self.onvif._move_to_preset(
camera,
@ -537,6 +546,7 @@ class PtzAutoTracker:
self.ptz_metrics[camera].max_zoom.value,
self.intercept[camera],
*self.move_coefficients[camera],
self.zoom_time[camera],
]
)
@ -1111,6 +1121,31 @@ class PtzAutoTracker:
camera, obj, predicted_box, predicted_movement_time, debug_zoom=True
)
if (
camera_config.onvif.autotracking.movement_weights
and camera_config.onvif.autotracking.zooming == ZoomingModeEnum.relative
and zoom != 0
):
zoom_predicted_movement_time = abs(zoom) * self.zoom_time[camera]
zoom_predicted_box = (
predicted_box
+ camera_fps * zoom_predicted_movement_time * average_velocity
)
zoom_predicted_box = np.round(zoom_predicted_box).astype(int)
centroid_x = round((zoom_predicted_box[0] + zoom_predicted_box[2]) / 2)
centroid_y = round((zoom_predicted_box[1] + zoom_predicted_box[3]) / 2)
# recalculate pan and tilt with new centroid
pan = ((centroid_x / camera_width) - 0.5) * 2
tilt = (0.5 - (centroid_y / camera_height)) * 2
logger.debug(
f"{camera}: Zoom predicted time: {zoom_predicted_movement_time}, zoom predicted box: {tuple(zoom_predicted_box)}"
)
self._enqueue_move(camera, obj.obj_data["frame_time"], pan, tilt, zoom)
def _autotrack_move_zoom_only(self, camera, obj):
@ -1242,7 +1277,7 @@ class PtzAutoTracker:
return
# this is a brand new object that's on our camera, has our label, entered the zone,
# is not a false positive, and is not initially motionless
# is not a false positive, and is active
if (
# new object
self.tracked_object[camera] is None
@ -1252,7 +1287,7 @@ class PtzAutoTracker:
and not obj.previous["false_positive"]
and not obj.false_positive
and not self.tracked_object_history[camera]
and obj.obj_data["motionless_count"] == 0
and obj.active
):
logger.debug(
f"{camera}: New object: {obj.obj_data['id']} {obj.obj_data['box']} {obj.obj_data['frame_time']}"