Tracker more sensitive and cv_renderer animates lines
This commit is contained in:
Ruben van de Ven
parent
888ef7ff93
commit
cebe102e74
10 changed files with 211 additions and 106 deletions
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@ -2,10 +2,10 @@
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# Default YOLO tracker settings for ByteTrack tracker https://github.com/ifzhang/ByteTrack
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tracker_type: bytetrack # tracker type, ['botsort', 'bytetrack']
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track_high_thresh: 0.05 # threshold for the first association
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track_low_thresh: 0.01 # threshold for the second association
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new_track_thresh: 0.1 # threshold for init new track if the detection does not match any tracks
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track_buffer: 35 # buffer to calculate the time when to remove tracks
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match_thresh: 0.9 # threshold for matching tracks
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track_high_thresh: 0.0001 # threshold for the first association
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track_low_thresh: 0.0001 # threshold for the second association
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new_track_thresh: 0.0001 # threshold for init new track if the detection does not match any tracks
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track_buffer: 50 # buffer to calculate the time when to remove tracks
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match_thresh: 0.95 # threshold for matching tracks
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fuse_score: True # Whether to fuse confidence scores with the iou distances before matching
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# min_box_area: 10 # threshold for min box areas(for tracker evaluation, not used for now)
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@ -54,10 +54,10 @@ class AnimationRenderer:
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self.tracker_sock.setsockopt(zmq.SUBSCRIBE, b'')
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self.tracker_sock.connect(config.zmq_trajectory_addr)
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self.frame_sock = context.socket(zmq.SUB)
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self.frame_sock.setsockopt(zmq.CONFLATE, 1) # only keep latest frame. NB. make sure this comes BEFORE connect, otherwise it's ignored!!
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self.frame_sock.setsockopt(zmq.SUBSCRIBE, b'')
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self.frame_sock.connect(config.zmq_frame_addr)
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self.frame_noimg_sock = context.socket(zmq.SUB)
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self.frame_noimg_sock.setsockopt(zmq.CONFLATE, 1) # only keep latest frame. NB. make sure this comes BEFORE connect, otherwise it's ignored!!
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self.frame_noimg_sock.setsockopt(zmq.SUBSCRIBE, b'')
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self.frame_noimg_sock.connect(config.zmq_frame_noimg_addr)
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self.H = self.config.H
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@ -324,26 +324,27 @@ class AnimationRenderer:
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new_tracks = False
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try:
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self.frame: Frame = self.frame_sock.recv_pyobj(zmq.NOBLOCK)
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self.frame: Frame = self.frame_noimg_sock.recv_pyobj(zmq.NOBLOCK)
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if not self.first_time:
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self.first_time = self.frame.time
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img = self.frame.img
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# newcameramtx, roi = cv2.getOptimalNewCameraMatrix(self.config.camera.mtx, self.config.camera.dist, (self.frame.img.shape[1], self.frame.img.shape[0]), 1, (self.frame.img.shape[1], self.frame.img.shape[0]))
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img = cv2.undistort(img, self.config.camera.mtx, self.config.camera.dist, None, self.config.camera.newcameramtx)
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img = cv2.warpPerspective(img, convert_world_space_to_img_space(self.config.camera.H), (self.config.camera.w, self.config.camera.h))
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# img = cv2.GaussianBlur(img, (15, 15), 0)
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img = cv2.flip(cv2.cvtColor(img, cv2.COLOR_BGR2RGB), 0)
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img = pyglet.image.ImageData(self.frame_size[0], self.frame_size[1], 'RGB', img.tobytes())
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# don't draw in batch, so that it is the background
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if hasattr(self, 'video_sprite') and self.video_sprite:
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self.video_sprite.delete()
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self.frame.img = None
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if self.frame.img:
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img = self.frame.img
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# newcameramtx, roi = cv2.getOptimalNewCameraMatrix(self.config.camera.mtx, self.config.camera.dist, (self.frame.img.shape[1], self.frame.img.shape[0]), 1, (self.frame.img.shape[1], self.frame.img.shape[0]))
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img = cv2.undistort(img, self.config.camera.mtx, self.config.camera.dist, None, self.config.camera.newcameramtx)
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img = cv2.warpPerspective(img, convert_world_space_to_img_space(self.config.camera.H), (self.config.camera.w, self.config.camera.h))
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# img = cv2.GaussianBlur(img, (15, 15), 0)
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img = cv2.flip(cv2.cvtColor(img, cv2.COLOR_BGR2RGB), 0)
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img = pyglet.image.ImageData(self.frame_size[0], self.frame_size[1], 'RGB', img.tobytes())
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# don't draw in batch, so that it is the background
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if hasattr(self, 'video_sprite') and self.video_sprite:
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self.video_sprite.delete()
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self.frame.img = None
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self.video_sprite = pyglet.sprite.Sprite(img=img, batch=self.batch_bg)
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# transform to flipped coordinate system for pyglet
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self.video_sprite.y = self.window.height - self.video_sprite.height
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# self.frame.img = np.array([]) # clearing memory?
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# self.video_sprite.opacity = 70
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self.video_sprite = pyglet.sprite.Sprite(img=img, batch=self.batch_bg)
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# transform to flipped coordinate system for pyglet
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self.video_sprite.y = self.window.height - self.video_sprite.height
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# self.frame.img = np.array([]) # clearing memory?
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# self.video_sprite.opacity = 70
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except zmq.ZMQError as e:
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# idx = frame.index if frame else "NONE"
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# logger.debug(f"reuse video frame {idx}")
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@ -253,6 +253,11 @@ connection_parser.add_argument('--zmq-frame-addr',
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type=str,
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default="ipc:///tmp/feeds_frame")
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connection_parser.add_argument('--zmq-frame-noimg-addr',
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help='Manually specity communication addr for the frame messages',
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type=str,
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default="ipc:///tmp/feeds_frame2")
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connection_parser.add_argument('--ws-port',
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help='Port to listen for incomming websocket connections. Also serves the testing html-page.',
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@ -334,7 +334,7 @@ class CvRenderer:
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def run(self):
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def run(self, timer_counter):
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frame = None
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prediction_frame = None
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tracker_frame = None
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@ -349,6 +349,8 @@ class CvRenderer:
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while self.is_running.is_set():
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i+=1
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with timer_counter.get_lock():
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timer_counter.value+=1
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# zmq_ev = self.frame_sock.poll(timeout=2000)
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@ -406,10 +408,10 @@ class CvRenderer:
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# clear out old tracks & predictions:
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for track_id, track in list(self.tracks.items()):
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if get_opacity(track, frame) == 0:
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if get_animation_position(track, frame) == 1:
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self.tracks.pop(track_id)
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for prediction_id, track in list(self.predictions.items()):
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if get_opacity(track, frame) == 0:
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if get_animation_position(track, frame) == 1:
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self.predictions.pop(prediction_id)
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logger.info('Stopping')
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@ -443,10 +445,10 @@ colorset = [
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# (0,0,0),
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# ]
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def get_opacity(track: Track, current_frame: Frame):
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fade_duration = current_frame.camera.fps * 1.5
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def get_animation_position(track: Track, current_frame: Frame):
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fade_duration = current_frame.camera.fps * 3
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diff = current_frame.index - track.history[-1].frame_nr
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return max(0, 1 - diff / fade_duration)
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return max(0, min(1, diff / fade_duration))
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# track.history[-1].frame_nr < (current_frame.index - current_frame.camera.fps * 3)
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# track.history[-1].frame_nr < (current_frame.index - current_frame.camera.fps * 3)
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@ -497,8 +499,8 @@ def decorate_frame(frame: Frame, tracker_frame: Frame, prediction_frame: Frame,
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inv_H = np.linalg.pinv(prediction_frame.H)
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# draw_track(img, track, int(track_id))
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draw_trackjectron_history(img, track, int(track.track_id), convert_world_points_to_img_points)
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opacity = get_opacity(track, frame)
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draw_track_predictions(img, track, int(track.track_id)+1, config.camera, convert_world_points_to_img_points, opacity=opacity)
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anim_position = get_animation_position(track, frame)
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draw_track_predictions(img, track, int(track.track_id)+1, config.camera, convert_world_points_to_img_points, anim_position=anim_position)
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cv2.putText(img, f"{len(track.predictor_history) if track.predictor_history else 'none'}", to_point(track.history[0].get_foot_coords()), cv2.FONT_HERSHEY_COMPLEX, 1, (255,255,255), 1)
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base_color = (255,)*3
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@ -532,6 +534,6 @@ def decorate_frame(frame: Frame, tracker_frame: Frame, prediction_frame: Frame,
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return img
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def run_cv_renderer(config: Namespace, is_running: BaseEvent):
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def run_cv_renderer(config: Namespace, is_running: BaseEvent, timer_counter):
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renderer = CvRenderer(config, is_running)
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renderer.run()
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renderer.run(timer_counter)
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@ -420,6 +420,9 @@ class Frame:
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} for t in self.tracks.values()
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}
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def without_img(self):
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return Frame(self.index, None, self.time, self.tracks, self.H, self.camera)
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def video_src_from_config(config) -> UrlOrPath:
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if config.video_loop:
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video_srcs: Iterable[UrlOrPath] = cycle(config.video_src)
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@ -442,12 +445,17 @@ class FrameEmitter:
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self.frame_sock.setsockopt(zmq.CONFLATE, 1) # only keep latest frame. make sure to set BEFORE connect/bind
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self.frame_sock.bind(config.zmq_frame_addr)
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self.frame_noimg_sock = context.socket(zmq.PUB)
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self.frame_noimg_sock.setsockopt(zmq.CONFLATE, 1) # only keep latest frame. make sure to set BEFORE connect/bind
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self.frame_noimg_sock.bind(config.zmq_frame_noimg_addr)
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logger.info(f"Connection socket {config.zmq_frame_addr}")
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logger.info(f"Connection socket {config.zmq_frame_noimg_addr}")
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self.video_srcs = video_src_from_config(self.config)
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def emit_video(self):
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def emit_video(self, timer_counter):
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i = 0
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delay_generation = False
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for video_path in self.video_srcs:
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@ -462,7 +470,7 @@ class FrameEmitter:
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video.set(cv2.CAP_PROP_FPS, 5)
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fps=5
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elif video_path.url.scheme == 'rtsp':
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gst = f"rtspsrc location={video_path} latency=0 buffer-mode=auto ! decodebin ! videoconvert ! appsink max-buffers=1 drop=true"
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gst = f"rtspsrc location={video_path} latency=0 buffer-mode=auto ! decodebin ! videoconvert ! appsink max-buffers=0 drop=true"
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logger.info(f"Capture gstreamer (gst-launch-1.0): {gst}")
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video = cv2.VideoCapture(gst, cv2.CAP_GSTREAMER)
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fps=12
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@ -496,7 +504,11 @@ class FrameEmitter:
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prev_time = time.time()
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while self.is_running.is_set():
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with timer_counter.get_lock():
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timer_counter.value += 1
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ret, img = video.read()
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# seek to 0 if video has finished. Infinite loop
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@ -515,6 +527,7 @@ class FrameEmitter:
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frame = Frame(index=i, img=img, H=self.config.H, camera=self.config.camera)
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# TODO: this is very dirty, need to find another way.
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# perhaps multiprocessing Array?
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self.frame_noimg_sock.send(pickle.dumps(frame.without_img()))
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self.frame_sock.send(pickle.dumps(frame))
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# only delay consuming the next frame when using a file.
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@ -540,7 +553,7 @@ class FrameEmitter:
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def run_frame_emitter(config: Namespace, is_running: Event):
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def run_frame_emitter(config: Namespace, is_running: Event, timer_counter: int):
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router = FrameEmitter(config, is_running)
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router.emit_video()
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router.emit_video(timer_counter)
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is_running.clear()
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@ -13,6 +13,7 @@ from trap.prediction_server import run_prediction_server
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from trap.preview_renderer import run_preview_renderer
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from trap.animation_renderer import run_animation_renderer
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from trap.socket_forwarder import run_ws_forwarder
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from trap.timer import TimerCollection
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from trap.tracker import run_tracker
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from setproctitle import setproctitle, setthreadtitle
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@ -83,20 +84,23 @@ def start():
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# queue_listener.handlers.append(socket_handler)
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timers = TimerCollection()
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timer_fe = timers.new('frame_emitter')
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timer_tracker = timers.new('tracker')
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# instantiating process with arguments
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procs = [
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# ExceptionHandlingProcess(target=run_ws_forwarder, kwargs={'config': args, 'is_running': isRunning}, name='forwarder'),
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ExceptionHandlingProcess(target=run_frame_emitter, kwargs={'config': args, 'is_running': isRunning}, name='frame_emitter'),
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ExceptionHandlingProcess(target=run_tracker, kwargs={'config': args, 'is_running': isRunning}, name='tracker'),
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ExceptionHandlingProcess(target=run_frame_emitter, kwargs={'config': args, 'is_running': isRunning, 'timer_counter': timer_fe.iterations}, name='frame_emitter'),
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ExceptionHandlingProcess(target=run_tracker, kwargs={'config': args, 'is_running': isRunning, 'timer_counter': timer_tracker.iterations}, name='tracker'),
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]
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# if args.render_file or args.render_url or args.render_window:
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if args.render_window or args.render_file or args.render_url:
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timer_preview = timers.new('preview')
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procs.append(
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# ExceptionHandlingProcess(target=run_cv_renderer, kwargs={'config': args, 'is_running': isRunning}, name='preview')
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ExceptionHandlingProcess(target=run_cv_renderer, kwargs={'config': args, 'is_running': isRunning}, name='preview')
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ExceptionHandlingProcess(target=run_cv_renderer, kwargs={'config': args, 'is_running': isRunning, 'timer_counter': timer_preview.iterations}, name='preview')
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)
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if args.render_animation:
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procs.append(
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@ -104,8 +108,19 @@ def start():
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)
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if not args.bypass_prediction:
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timer_predict = timers.new('predict')
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procs.append(
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ExceptionHandlingProcess(target=run_prediction_server, kwargs={'config': args, 'is_running':isRunning}, name='inference'),
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ExceptionHandlingProcess(target=run_prediction_server, kwargs={'config': args, 'is_running':isRunning, 'timer_counter': timer_predict.iterations}, name='inference'),
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)
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def timer_process(timers: TimerCollection, is_running: Event):
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while is_running.is_set():
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time.sleep(1)
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timers.snapshot()
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print(timers.to_string())
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procs.append(
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ExceptionHandlingProcess(target=timer_process, kwargs={'is_running':isRunning, 'timers': timers}, name='timer'),
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)
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try:
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@ -166,11 +166,11 @@ class PredictionServer:
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def send_frame(self, frame: Frame):
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if self.external_predictions:
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# data = json.dumps(frame, cls=DataclassJSONEncoder)
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self.prediction_socket.send_json(frame, cls=DataclassJSONEncoder)
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self.prediction_socket.send_json(obj=frame, cls=DataclassJSONEncoder)
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else:
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self.prediction_socket.send_pyobj(frame)
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def run(self):
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def run(self, timer_counter):
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print(self.config)
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if self.config.seed is not None:
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random.seed(self.config.seed)
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@ -247,6 +247,8 @@ class PredictionServer:
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prev_run_time = 0
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while self.is_running.is_set():
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timestep += 1
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with timer_counter.get_lock():
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timer_counter.value+=1
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# this_run_time = time.time()
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# logger.debug(f'test {prev_run_time - this_run_time}')
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@ -477,7 +479,7 @@ class PredictionServer:
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def run_prediction_server(config: Namespace, is_running: Event):
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def run_prediction_server(config: Namespace, is_running: Event, timer_counter):
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# attempt to trace the warnings coming from pytorch
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# def warn_with_traceback(message, category, filename, lineno, file=None, line=None):
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@ -488,4 +490,4 @@ def run_prediction_server(config: Namespace, is_running: Event):
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# warnings.showwarning = warn_with_traceback
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s = PredictionServer(config, is_running)
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s.run()
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s.run(timer_counter)
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@ -1,6 +1,9 @@
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import collections
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from re import A
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import time
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from multiprocessing.sharedctypes import RawValue, Value, Array
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from ctypes import c_double
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from typing import MutableSequence
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class Timer():
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@ -8,47 +11,58 @@ class Timer():
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Measure 2 independent things: the freuency of tic, and the duration of tic->toc
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Note that indeed these don't need to be equal
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"""
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def __init__(self) -> None:
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self.last_tic = RawValue(c_double, -1)
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self.last_toc = RawValue(c_double, -1)
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self.fps = RawValue(c_double, -1)
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self.processing_duration = RawValue(c_double, -1)
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def __init__(self, name = 'timer') -> None:
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self.name = name
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self.tocs: MutableSequence[(float, int)] = collections.deque(maxlen=5)
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self.iterations = Value('i', 0)
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self.smoothing = .1
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# def tic(self):
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# now = time.time()
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# if self.last_tic is None:
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def tic(self):
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now = time.time()
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if self.last_tic is None:
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# self.last_tic = now
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# return
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self.last_tic = now
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return
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# duration = now - self.last_tic
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# self.last_tic = now
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duration = now - self.last_tic
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self.last_tic = now
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current_fps = 1 / duration
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if not self.fps:
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self.fps = current_fps
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else:
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self.fps = self.fps * (1-self.smoothing) + current_fps * self.smoothing
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# current_fps = 1 / duration
|
||||
# if not self.fps:
|
||||
# self.fps = current_fps
|
||||
# else:
|
||||
# self.fps = self.fps * (1-self.smoothing) + current_fps * self.smoothing
|
||||
|
||||
def toc(self):
|
||||
self.last_toc = time.time()
|
||||
duration = self.last_toc - self.last_tic
|
||||
|
||||
self.processing_duration = self.processing_duration * (1-self.smoothing) + duration * self.smoothing
|
||||
self.iterations += 1
|
||||
|
||||
def snapshot(self):
|
||||
self.tocs.append((time.perf_counter(), self.iterations.value))
|
||||
|
||||
@property
|
||||
def fps(self):
|
||||
fpses = []
|
||||
if len(self.tocs) < 2:
|
||||
return 0
|
||||
dt = self.tocs[-1][0] - self.tocs[0][0]
|
||||
di = self.tocs[-1][1] - self.tocs[0][1]
|
||||
return di/dt
|
||||
|
||||
pass
|
||||
|
||||
class TimerCollection():
|
||||
def __init__(self) -> None:
|
||||
self._timers = set()
|
||||
|
||||
def print(self)->str:
|
||||
print('Update', end='\r')
|
||||
def snapshot(self):
|
||||
for timer in self._timers:
|
||||
timer.snapshot()
|
||||
|
||||
def to_string(self)->str:
|
||||
strs = [f"{t.name} {t.fps:.2f}" for t in self._timers]
|
||||
return " ".join(strs)
|
||||
|
||||
def new(self, name='timer'):
|
||||
t = Timer(name)
|
||||
self._timers.add(t)
|
||||
return t
|
||||
|
||||
|
||||
|
|
@ -22,7 +22,7 @@ from ultralytics import YOLO
|
|||
from ultralytics.engine.results import Results as YOLOResult
|
||||
import tqdm
|
||||
|
||||
from trap.utils import lerp
|
||||
from trap.utils import inv_lerp, lerp
|
||||
|
||||
|
||||
|
||||
|
|
@ -185,40 +185,82 @@ def tracker_compare():
|
|||
|
||||
bar.set_description(f"[{frames.video_nr}/{len(frames.video_srcs)}] [{frames.frame_idx}/{frames.frame_count}] {str(frames.video_path)}")
|
||||
|
||||
def draw_track_predictions(img: cv2.Mat, track: Track, color_index: int, camera:Camera, convert_points: Optional[Callable], opacity=1):
|
||||
def transition_path_points(path: np.array, t: float):
|
||||
"""
|
||||
Opacity: 0-1
|
||||
"""
|
||||
|
||||
if t >= 1:
|
||||
return path
|
||||
if t <= 0:
|
||||
return np.array([path[0]])
|
||||
|
||||
# new_path = np.array([])
|
||||
lengths = np.sqrt(np.sum(np.diff(path, axis=0)**2, axis=1))
|
||||
cum_lenghts = np.cumsum(lengths)
|
||||
# distance = cum_lenghts[-1] * t
|
||||
ts = np.concatenate((np.array([0.]), cum_lenghts / cum_lenghts[-1]))
|
||||
new_path = [path[0]]
|
||||
|
||||
for a, b, t_a, t_b in zip(path[:-1], path[1:], ts[:-1], ts[1:]):
|
||||
if t_b < t:
|
||||
new_path.append(b)
|
||||
continue
|
||||
# interpolate
|
||||
relative_t = inv_lerp(t_a, t_b, t)
|
||||
x = lerp(a[0], b[0], relative_t)
|
||||
y = lerp(a[1], b[1], relative_t)
|
||||
print(relative_t, a , b, x, y)
|
||||
new_path.append([x,y])
|
||||
break
|
||||
return np.array(new_path)
|
||||
|
||||
|
||||
|
||||
|
||||
def draw_track_predictions(img: cv2.Mat, track: Track, color_index: int, camera:Camera, convert_points: Optional[Callable], anim_position=.8):
|
||||
"""
|
||||
anim_position: 0-1
|
||||
"""
|
||||
if not track.predictions:
|
||||
return
|
||||
|
||||
current_point = track.get_projected_history(camera=camera)[-1]
|
||||
|
||||
if convert_points:
|
||||
current_point = convert_points([current_point])[0]
|
||||
opacity = 1-min(1, max(0, inv_lerp(0.8, 1, anim_position))) # fade out
|
||||
slide_t = min(1, max(0, inv_lerp(0, 0.8, anim_position))) # slide_position
|
||||
|
||||
|
||||
# if convert_points:
|
||||
# current_point = convert_points([current_point])[0]
|
||||
|
||||
for pred_i, pred in enumerate(track.predictions):
|
||||
pred_coords = pred #cv2.perspectiveTransform(np.array([pred]), inv_H)[0].tolist()
|
||||
# line_points = np.concatenate(([current_point], pred_coords)) # 'current point' is amoving target
|
||||
line_points = pred_coords
|
||||
# print(pred_coords, current_point, line_points)
|
||||
line_points = transition_path_points(line_points, slide_t)
|
||||
if convert_points:
|
||||
pred_coords = convert_points(pred_coords)
|
||||
line_points = convert_points(line_points)
|
||||
# color = (128,0,128) if pred_i else (128,128,0)
|
||||
|
||||
color = bgr_colors[color_index % len(bgr_colors)]
|
||||
color = tuple([int(c*opacity) for c in color])
|
||||
|
||||
|
||||
for ci in range(0, len(pred_coords)):
|
||||
if ci == 0:
|
||||
# TODO)) prev point
|
||||
# continue
|
||||
start = [int(p) for p in current_point]
|
||||
# start = [int(p) for p in coords[-1]]
|
||||
# start = [0,0]?
|
||||
# print(start)
|
||||
else:
|
||||
start = [int(p) for p in pred_coords[ci-1]]
|
||||
end = [int(p) for p in pred_coords[ci]]
|
||||
cv2.line(img, start, end, color, 1, lineType=cv2.LINE_AA)
|
||||
for start, end in zip(line_points[:-1], line_points[1:]):
|
||||
# for ci in range(0, len(pred_coords)):
|
||||
# if ci == 0:
|
||||
# # TODO)) prev point
|
||||
# # continue
|
||||
# start = [int(p) for p in current_point]
|
||||
# # start = [int(p) for p in coords[-1]]
|
||||
# # start = [0,0]?
|
||||
# # print(start)
|
||||
# else:
|
||||
# start = [int(p) for p in pred_coords[ci-1]]
|
||||
# end = [int(p) for p in pred_coords[ci]]
|
||||
# print(np.rint(start),np.rint(end).tolist())
|
||||
cv2.line(img, np.rint(start).astype(int), np.rint(end).astype(int), color, 1, lineType=cv2.LINE_AA)
|
||||
# cv2.circle(img, end, 2, color, 1, lineType=cv2.LINE_AA)
|
||||
|
||||
def draw_trackjectron_history(img: cv2.Mat, track: Track, color_index: int, convert_points: Optional[Callable]):
|
||||
|
|
|
|||
|
|
@ -9,7 +9,7 @@ from multiprocessing import Event
|
|||
from pathlib import Path
|
||||
import pickle
|
||||
import time
|
||||
from typing import Optional, List
|
||||
from typing import Dict, Optional, List
|
||||
import jsonlines
|
||||
import numpy as np
|
||||
import torch
|
||||
|
|
@ -61,7 +61,7 @@ RCNN_SCALE = .4 # seems to have no impact on detections in the corners
|
|||
|
||||
def _yolov8_track(frame: Frame, model: YOLO, **kwargs) -> List[Detection]:
|
||||
|
||||
results: List[YOLOResult] = list(model.track(frame.img, persist=True, tracker="custom_bytetrack.yaml", verbose=False, **kwargs))
|
||||
results: List[YOLOResult] = list(model.track(frame.img, persist=True, tracker="custom_bytetrack.yaml", verbose=False, conf=0.00001, **kwargs))
|
||||
if results[0].boxes is None or results[0].boxes.id is None:
|
||||
# work around https://github.com/ultralytics/ultralytics/issues/5968
|
||||
return []
|
||||
|
|
@ -99,6 +99,10 @@ class TrackFilter:
|
|||
def apply(self, tracks: List[Track], camera: Camera):
|
||||
return [t for t in tracks if self.filter(t, camera)]
|
||||
|
||||
def apply_to_dict(self, tracks: Dict[str, Track], camera: Camera):
|
||||
tracks = self.apply(tracks.values(), camera)
|
||||
return {t.track_id: t for t in tracks}
|
||||
|
||||
class FinalDisplacementFilter(TrackFilter):
|
||||
def __init__(self, min_displacement):
|
||||
self.min_displacement = min_displacement
|
||||
|
|
@ -444,7 +448,7 @@ class Tracker:
|
|||
|
||||
def track_frame(self, frame: Frame):
|
||||
if self.config.detector == DETECTOR_YOLOv8:
|
||||
detections: List[Detection] = _yolov8_track(frame, self.model, classes=[0], imgsz=[1152, 640])
|
||||
detections: List[Detection] = _yolov8_track(frame, self.model, classes=[0, 15, 16], imgsz=[1152, 640])
|
||||
else :
|
||||
detections: List[Detection] = self._resnet_track(frame, scale = RCNN_SCALE)
|
||||
|
||||
|
|
@ -458,7 +462,7 @@ class Tracker:
|
|||
return detections
|
||||
|
||||
|
||||
def track(self, is_running: Event):
|
||||
def track(self, is_running: Event, timer_counter: int = 0):
|
||||
"""
|
||||
Live tracking of frames coming in over zmq
|
||||
"""
|
||||
|
|
@ -500,7 +504,11 @@ class Tracker:
|
|||
end_time = None
|
||||
tracker_dt = None
|
||||
w_time = None
|
||||
displacement_filter = FinalDisplacementFilter(.2)
|
||||
while self.is_running.is_set():
|
||||
|
||||
with timer_counter.get_lock():
|
||||
timer_counter.value += 1
|
||||
# this waiting for target_dt causes frame loss. E.g. with target_dt at .1, it
|
||||
# skips exactly 1 frame on a 10 fps video (which, it obviously should not do)
|
||||
# so for now, timing should move to emitter
|
||||
|
|
@ -566,6 +574,9 @@ class Tracker:
|
|||
# }
|
||||
active_track_ids = [d.track_id for d in detections]
|
||||
active_tracks = {t.track_id: t.get_with_interpolated_history() for t in self.tracks.values() if t.track_id in active_track_ids}
|
||||
active_tracks = displacement_filter.apply_to_dict(active_tracks, frame.camera)# a filter to remove just detecting static objects
|
||||
|
||||
|
||||
# active_tracks = {t.track_id: t for t in self.tracks.values() if t.track_id in active_track_ids}
|
||||
# active_tracks = {t.track_id: t for t in self.tracks.values() if t.track_id in active_track_ids}
|
||||
# logger.info(f"{trajectories}")
|
||||
|
|
@ -579,7 +590,7 @@ class Tracker:
|
|||
frame = self.smoother.smooth_frame_tracks(frame)
|
||||
|
||||
# print(f"send to {self.trajectory_socket}, {self.config.zmq_trajectory_addr}")
|
||||
self.trajectory_socket.send_pyobj(frame)
|
||||
self.trajectory_socket.send_pyobj(frame.without_img()) # ditch image for faster passthrough
|
||||
|
||||
end_time = time.time()
|
||||
tracker_dt = end_time - start_time
|
||||
|
|
@ -665,9 +676,9 @@ class Tracker:
|
|||
return [([d[0], d[1], d[2]-d[0], d[3]-d[1]], d[4], d[5]) for d in detections]
|
||||
|
||||
|
||||
def run_tracker(config: Namespace, is_running: Event):
|
||||
def run_tracker(config: Namespace, is_running: Event, timer_counter):
|
||||
router = Tracker(config)
|
||||
router.track(is_running)
|
||||
router.track(is_running, timer_counter)
|
||||
|
||||
|
||||
|
||||
|
|
|
|||
Loading…
Reference in a new issue