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https://github.com/blakeblackshear/frigate.git
synced 2026-05-05 04:57:42 +03:00
only calculate zoom time of relative move
This commit is contained in:
Josh Hawkins
parent
25428e5741
commit
05b915b495
@ -364,9 +364,9 @@ class PtzAutoTracker:
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!= ZoomingModeEnum.disabled
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):
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logger.info(f"Calibration for {camera} in progress: 0% complete")
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self.zoom_time[camera] = 0
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for i in range(2):
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start_time = time.time()
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# absolute move to 0 - fully zoomed out
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self.onvif._zoom_absolute(
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camera,
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@ -389,9 +389,6 @@ class PtzAutoTracker:
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self.onvif.get_camera_status(camera)
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zoom_in_values.append(self.ptz_metrics[camera].zoom_level.value)
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stop_time = time.time()
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self.zoom_time[camera] = stop_time - start_time
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if (
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self.config.cameras[camera].onvif.autotracking.zooming
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@ -411,6 +408,7 @@ class PtzAutoTracker:
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zoom_out_values.append(self.ptz_metrics[camera].zoom_level.value)
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zoom_start_time = time.time()
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# relative move to 0.01
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self.onvif._move_relative(
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camera,
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@ -423,6 +421,38 @@ class PtzAutoTracker:
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while not self.ptz_metrics[camera].motor_stopped.is_set():
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self.onvif.get_camera_status(camera)
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zoom_stop_time = time.time()
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full_relative_start_time = time.time()
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self.onvif._move_relative(
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camera,
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-1,
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-1,
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-1e-2,
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1,
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)
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while not self.ptz_metrics[camera].motor_stopped.is_set():
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self.onvif.get_camera_status(camera)
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full_relative_stop_time = time.time()
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self.onvif._move_relative(
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camera,
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1,
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1,
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1e-2,
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1,
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)
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while not self.ptz_metrics[camera].motor_stopped.is_set():
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self.onvif.get_camera_status(camera)
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self.zoom_time[camera] = (
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full_relative_stop_time - full_relative_start_time
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) - (zoom_stop_time - zoom_start_time)
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zoom_in_values.append(self.ptz_metrics[camera].zoom_level.value)
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self.ptz_metrics[camera].max_zoom.value = max(zoom_in_values)
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@ -435,7 +465,6 @@ class PtzAutoTracker:
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else:
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self.ptz_metrics[camera].max_zoom.value = 1
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self.ptz_metrics[camera].min_zoom.value = 0
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self.zoom_time[camera] = 0
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self.onvif._move_to_preset(
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camera,
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@ -1071,6 +1100,7 @@ class PtzAutoTracker:
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average_velocity = np.zeros((4,))
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predicted_box = obj.obj_data["box"]
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zoom_predicted_box = obj.obj_data["box"]
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centroid_x = obj.obj_data["centroid"][0]
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centroid_y = obj.obj_data["centroid"][1]
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@ -1079,20 +1109,20 @@ class PtzAutoTracker:
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pan = ((centroid_x / camera_width) - 0.5) * 2
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tilt = (0.5 - (centroid_y / camera_height)) * 2
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_, average_velocity = (
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self._get_valid_velocity(camera, obj)
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if "velocity" not in self.tracked_object_metrics[camera]
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else (
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self.tracked_object_metrics[camera]["valid_velocity"],
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self.tracked_object_metrics[camera]["velocity"],
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)
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)
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if (
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camera_config.onvif.autotracking.movement_weights
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): # use estimates if we have available coefficients
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predicted_movement_time = self._predict_movement_time(camera, pan, tilt)
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_, average_velocity = (
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self._get_valid_velocity(camera, obj)
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if "velocity" not in self.tracked_object_metrics[camera]
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else (
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self.tracked_object_metrics[camera]["valid_velocity"],
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self.tracked_object_metrics[camera]["velocity"],
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)
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)
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if np.any(average_velocity):
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# this box could exceed the frame boundaries if velocity is high
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# but we'll handle that in _enqueue_move() as two separate moves
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@ -1126,21 +1156,24 @@ class PtzAutoTracker:
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and camera_config.onvif.autotracking.zooming == ZoomingModeEnum.relative
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and zoom != 0
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):
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zoom_predicted_movement_time = abs(zoom) * self.zoom_time[camera]
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zoom_predicted_movement_time = 0
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zoom_predicted_box = (
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predicted_box
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+ camera_fps * zoom_predicted_movement_time * average_velocity
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)
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if np.any(average_velocity):
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zoom_predicted_movement_time = abs(zoom) * self.zoom_time[camera]
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zoom_predicted_box = np.round(zoom_predicted_box).astype(int)
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zoom_predicted_box = (
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predicted_box
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+ camera_fps * zoom_predicted_movement_time * average_velocity
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)
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centroid_x = round((zoom_predicted_box[0] + zoom_predicted_box[2]) / 2)
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centroid_y = round((zoom_predicted_box[1] + zoom_predicted_box[3]) / 2)
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zoom_predicted_box = np.round(zoom_predicted_box).astype(int)
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# recalculate pan and tilt with new centroid
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pan = ((centroid_x / camera_width) - 0.5) * 2
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tilt = (0.5 - (centroid_y / camera_height)) * 2
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centroid_x = round((zoom_predicted_box[0] + zoom_predicted_box[2]) / 2)
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centroid_y = round((zoom_predicted_box[1] + zoom_predicted_box[3]) / 2)
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# recalculate pan and tilt with new centroid
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pan = ((centroid_x / camera_width) - 0.5) * 2
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tilt = (0.5 - (centroid_y / camera_height)) * 2
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logger.debug(
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f"{camera}: Zoom amount: {zoom}, zoom predicted time: {zoom_predicted_movement_time}, zoom predicted box: {tuple(zoom_predicted_box)}"
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