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zoom in/out in search for lost objects

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This commit is contained in:
Josh Hawkins 2023-09-30 19:50:33 -05:00
parent 9a4f970337
commit b264b168f2
2 changed files with 120 additions and 51 deletions
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169
frigate/ptz/autotrack.py
View File

@ -402,14 +402,24 @@ class PtzAutoTracker:
if (
self.config.cameras[camera].onvif.autotracking.zooming
== ZoomingModeEnum.relative
and self.tracked_object[camera] is not None
):
self.onvif._move_relative(camera, pan, tilt, zoom, 1)
else:
if zoom > 0:
self.onvif._zoom_absolute(camera, zoom, 1)
else:
if pan != 0 or tilt != 0:
self.onvif._move_relative(camera, pan, tilt, 0, 1)
if (
zoom > 0
and self.ptz_metrics[camera]["ptz_zoom_level"].value != zoom
):
self.onvif._zoom_absolute(camera, zoom, 1)
# Wait until the camera finishes moving
while not self.ptz_metrics[camera]["ptz_stopped"].is_set():
# check if ptz is moving
self.onvif.get_camera_status(camera)
# Wait until the camera finishes moving
while not self.ptz_metrics[camera]["ptz_stopped"].is_set():
# check if ptz is moving
@ -427,6 +437,7 @@ class PtzAutoTracker:
if (
self.intercept[camera] is not None
and len(self.move_metrics[camera]) < 500
and (pan != 0 or tilt != 0)
):
logger.debug("Adding new values to move metrics")
self.move_metrics[camera].append(
@ -477,12 +488,21 @@ class PtzAutoTracker:
tilt = tilt_excess
zoom = zoom_excess
def _should_zoom_in(self, camera, box, area, average_velocity):
def _should_zoom_in(self, camera, obj, box):
camera_config = self.config.cameras[camera]
camera_width = camera_config.frame_shape[1]
camera_height = camera_config.frame_shape[0]
camera_area = camera_width * camera_height
obj.obj_data["area"]
x1, y1, x2, y2 = obj.obj_data["estimate_velocity"]
average_velocity = (
(x1 + x2) / 2,
(y1 + y2) / 2,
(x1 + x2) / 2,
(y1 + y2) / 2,
)
bb_left, bb_top, bb_right, bb_bottom = box
# If bounding box is not within 5% of an edge
@ -492,13 +512,22 @@ class PtzAutoTracker:
#
# TODO: Take into account the area changing when an object is moving out of frame
edge_threshold = 0.15
area_threshold = self.zoom_factor[camera]
velocity_threshold = 0.1
# if we have a big object, let's zoom out
# base the area threshold on 5 times the zoom_factor
above_area_threshold = (
min(
obj.obj_data["area"] / camera_area * 5 * self.zoom_factor[camera],
1,
)
== 1
)
# if we have a fast moving object, let's zoom out
# fast moving is defined as a velocity of more than 10% of the camera's width or height
# so an object with an x velocity of 15 pixels on a 1280x720 camera would trigger a zoom out
velocity_threshold = average_velocity[0] > (
above_velocity_threshold = average_velocity[0] > (
camera_width * velocity_threshold
) or average_velocity[1] > (camera_height * velocity_threshold)
@ -508,13 +537,14 @@ class PtzAutoTracker:
and bb_right < (1 - edge_threshold) * camera_width
and bb_top > edge_threshold * camera_height
and bb_bottom < (1 - edge_threshold) * camera_height
and area < area_threshold * camera_area
and not velocity_threshold
and not above_area_threshold
and not above_velocity_threshold
)
def _autotrack_move_ptz(self, camera, obj):
camera_config = self.config.cameras[camera]
average_velocity = (0,) * 4
predicted_box = []
# # frame width and height
camera_width = camera_config.frame_shape[1]
@ -543,30 +573,56 @@ class PtzAutoTracker:
)
# get euclidean distance of the two points, sometimes the estimate is way off
distance = np.linalg.norm([x2 - x1, y2 - y1])
# may not need this
# distance = np.linalg.norm([x2 - x1, y2 - y1])
if distance <= 5:
# make sure we're not dealing with a disappeared object
if not all(x == 0.0 for x in obj.score_history[-3:]):
# this box could exceed the frame boundaries if velocity is high
# but we'll handle that in _enqueue_move() as two separate moves
predicted_box = [
round(x + camera_fps * predicted_movement_time * v)
for x, v in zip(obj.obj_data["box"], average_velocity)
]
else:
# estimate was bad
predicted_box = obj.obj_data["box"]
centroid_x = round((predicted_box[0] + predicted_box[2]) / 2)
centroid_y = round((predicted_box[1] + predicted_box[3]) / 2)
centroid_x = round((predicted_box[0] + predicted_box[2]) / 2)
centroid_y = round((predicted_box[1] + 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
# 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'Original box: {obj.obj_data["box"]}')
logger.debug(f"Predicted box: {predicted_box}")
logger.debug(f'Velocity: {obj.obj_data["estimate_velocity"]}')
zoom = self._get_zoom_amount(camera, obj, predicted_box)
self._enqueue_move(camera, obj.obj_data["frame_time"], pan, tilt, zoom)
def _autotrack_move_zoom_only(self, camera, obj):
zoom = self._get_zoom_amount(camera, obj, obj.obj_data["box"])
self._enqueue_move(camera, obj.obj_data["frame_time"], 0, 0, zoom)
def _get_zoom_amount(self, camera, obj, predicted_box):
camera_config = self.config.cameras[camera]
# frame width and height
camera_width = camera_config.frame_shape[1]
camera_height = camera_config.frame_shape[0]
# absolute zooming separately from pan/tilt
if camera_config.onvif.autotracking.zooming == ZoomingModeEnum.absolute:
zoom_level = self.ptz_metrics[camera]["ptz_zoom_level"].value
if 0 < zoom_level <= 1:
if self._should_zoom_in(camera, obj, obj.obj_data["box"]):
zoom = min(1.0, zoom_level + 0.1)
else:
zoom = max(0.0, zoom_level - 0.1)
return zoom
if camera_config.onvif.autotracking.zooming == ZoomingModeEnum.relative:
# relative zooming concurrently with pan/tilt
zoom = min(
@ -577,18 +633,15 @@ class PtzAutoTracker:
1,
)
logger.debug(f"Zoom value: {zoom}")
# test if we need to zoom out
if not self._should_zoom_in(
camera,
obj,
predicted_box
if camera_config.onvif.autotracking.movement_weights
else obj.obj_data["box"],
obj.obj_data["area"],
average_velocity,
):
zoom = -(1 - zoom)
zoom = -zoom
# don't make small movements to zoom in if area hasn't changed significantly
# but always zoom out if necessary
@ -600,28 +653,30 @@ class PtzAutoTracker:
and zoom > 0
):
zoom = 0
return zoom
def _lost_object_zoom(self, camera, obj):
if not self._should_zoom_in(
camera,
obj,
obj.obj_data["box"],
):
self._enqueue_move(
camera,
self.ptz_metrics[camera]["ptz_frame_time"].value,
0,
0,
self.ptz_metrics[camera]["ptz_zoom_level"].value - 0.1,
)
else:
zoom = 0
self._enqueue_move(camera, obj.obj_data["frame_time"], pan, tilt, zoom)
def _autotrack_zoom_only(self, camera, obj):
camera_config = self.config.cameras[camera]
# absolute zooming separately from pan/tilt
if camera_config.onvif.autotracking.zooming == ZoomingModeEnum.absolute:
zoom_level = self.ptz_metrics[camera]["ptz_zoom_level"].value
if 0 < zoom_level <= 1:
if self._should_zoom_in(
camera, obj.obj_data["box"], obj.obj_data["area"], (0, 0, 0, 0)
):
zoom = min(1.0, zoom_level + 0.1)
else:
zoom = max(0.0, zoom_level - 0.1)
if zoom != zoom_level:
self._enqueue_move(camera, obj.obj_data["frame_time"], 0, 0, zoom)
self._enqueue_move(
camera,
self.ptz_metrics[camera]["ptz_frame_time"].value,
0,
0,
self.ptz_metrics[camera]["ptz_zoom_level"].value + 0.1,
)
def autotrack_object(self, camera, obj):
camera_config = self.config.cameras[camera]
@ -704,8 +759,8 @@ class PtzAutoTracker:
f"Autotrack: Existing object (do NOT move ptz): {obj.obj_data['id']} {obj.obj_data['box']} {obj.obj_data['frame_time']}"
)
# no need to move, but try absolute zooming
self._autotrack_zoom_only(camera, obj)
# no need to move, but try zooming
self._autotrack_move_zoom_only(camera, obj)
return
@ -715,8 +770,10 @@ class PtzAutoTracker:
self.tracked_object_previous[camera] = copy.deepcopy(obj)
self._autotrack_move_ptz(camera, obj)
# try absolute zooming too
self._autotrack_zoom_only(camera, obj)
# if our score history shows the last 5 detections are 0, zoom to see if we can find our lost object
if all(x == 0.0 for x in obj.score_history[-5:]):
logger.debug(f"Object {obj.obj_data['id']} is lost")
self._lost_object_zoom(camera, obj)
return
@ -776,6 +833,18 @@ class PtzAutoTracker:
if not self.ptz_metrics[camera]["ptz_stopped"].is_set():
self.onvif.get_camera_status(camera)
if (
self.tracked_object[camera] is None
and self.tracked_object_previous[camera] is not None
and (
# might want to use a different timestamp here?
self.ptz_metrics[camera]["ptz_frame_time"].value
- self.tracked_object_previous[camera].obj_data["frame_time"]
< autotracker_config.timeout
)
):
self._lost_object_zoom(camera, self.tracked_object_previous[camera])
# return to preset if tracking is over
if (
self.tracked_object[camera] is None
@ -784,7 +853,7 @@ class PtzAutoTracker:
# might want to use a different timestamp here?
self.ptz_metrics[camera]["ptz_frame_time"].value
- self.tracked_object_previous[camera].obj_data["frame_time"]
> autotracker_config.timeout
>= autotracker_config.timeout
)
and autotracker_config.return_preset
):

2
frigate/ptz/onvif.py
View File

@ -537,7 +537,7 @@ class OnvifController:
if (
self.config.cameras[camera_name].onvif.autotracking.zooming
== ZoomingModeEnum.absolute
!= ZoomingModeEnum.disabled
):
# store absolute zoom level as 0 to 1 interpolated from the values of the camera
self.ptz_metrics[camera_name]["ptz_zoom_level"].value = numpy.interp(