Tracker more sensitive and cv_renderer animates lines

custom_bytetrack.yaml

@@ -2,10 +2,10 @@
 # Default YOLO tracker settings for ByteTrack tracker https://github.com/ifzhang/ByteTrack
 
 tracker_type: bytetrack # tracker type, ['botsort', 'bytetrack']
-track_high_thresh: 0.05 # threshold for the first association
+track_high_thresh: 0.0001 # threshold for the first association
-track_low_thresh: 0.01 # threshold for the second association
+track_low_thresh: 0.0001 # threshold for the second association
-new_track_thresh: 0.1 # threshold for init new track if the detection does not match any tracks
+new_track_thresh: 0.0001 # threshold for init new track if the detection does not match any tracks
-track_buffer: 35 # buffer to calculate the time when to remove tracks
+track_buffer: 50 # buffer to calculate the time when to remove tracks
-match_thresh: 0.9 # threshold for matching tracks
+match_thresh: 0.95 # threshold for matching tracks
 fuse_score: True # Whether to fuse confidence scores with the iou distances before matching
 # min_box_area: 10  # threshold for min box areas(for tracker evaluation, not used for now)

trap/animation_renderer.py

@@ -54,10 +54,10 @@ class AnimationRenderer:
         self.tracker_sock.setsockopt(zmq.SUBSCRIBE, b'')
         self.tracker_sock.connect(config.zmq_trajectory_addr)
         
-        self.frame_sock = context.socket(zmq.SUB)
+        self.frame_noimg_sock = context.socket(zmq.SUB)
-        self.frame_sock.setsockopt(zmq.CONFLATE, 1) # only keep latest frame. NB. make sure this comes BEFORE connect, otherwise it's ignored!!
+        self.frame_noimg_sock.setsockopt(zmq.CONFLATE, 1) # only keep latest frame. NB. make sure this comes BEFORE connect, otherwise it's ignored!!
-        self.frame_sock.setsockopt(zmq.SUBSCRIBE, b'')
+        self.frame_noimg_sock.setsockopt(zmq.SUBSCRIBE, b'')
-        self.frame_sock.connect(config.zmq_frame_addr)
+        self.frame_noimg_sock.connect(config.zmq_frame_noimg_addr)
     
         self.H = self.config.H
 
@@ -324,26 +324,27 @@ class AnimationRenderer:
         
         new_tracks = False
         try:
-            self.frame: Frame = self.frame_sock.recv_pyobj(zmq.NOBLOCK)
+            self.frame: Frame = self.frame_noimg_sock.recv_pyobj(zmq.NOBLOCK)
             if not self.first_time:
                 self.first_time = self.frame.time
-            img = self.frame.img
+            if self.frame.img:
-            # 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]))
+                img = self.frame.img
-            img = cv2.undistort(img, self.config.camera.mtx, self.config.camera.dist, None, self.config.camera.newcameramtx)
+                # 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]))
-            img = cv2.warpPerspective(img, convert_world_space_to_img_space(self.config.camera.H), (self.config.camera.w, self.config.camera.h))
+                img = cv2.undistort(img, self.config.camera.mtx, self.config.camera.dist, None, self.config.camera.newcameramtx)
-            # img = cv2.GaussianBlur(img, (15, 15), 0)
+                img = cv2.warpPerspective(img, convert_world_space_to_img_space(self.config.camera.H), (self.config.camera.w, self.config.camera.h))
-            img = cv2.flip(cv2.cvtColor(img, cv2.COLOR_BGR2RGB), 0)
+                # img = cv2.GaussianBlur(img, (15, 15), 0)
-            img = pyglet.image.ImageData(self.frame_size[0], self.frame_size[1], 'RGB', img.tobytes())
+                img = cv2.flip(cv2.cvtColor(img, cv2.COLOR_BGR2RGB), 0)
-            # don't draw in batch, so that it is the background
+                img = pyglet.image.ImageData(self.frame_size[0], self.frame_size[1], 'RGB', img.tobytes())
-            if hasattr(self, 'video_sprite') and self.video_sprite:
+                # don't draw in batch, so that it is the background
-                self.video_sprite.delete()
+                if hasattr(self, 'video_sprite') and self.video_sprite:
-            self.frame.img = None
+                    self.video_sprite.delete()
-                
+                self.frame.img = None
-            self.video_sprite = pyglet.sprite.Sprite(img=img, batch=self.batch_bg)
+                    
-            # transform to flipped coordinate system for pyglet
+                self.video_sprite = pyglet.sprite.Sprite(img=img, batch=self.batch_bg)
-            self.video_sprite.y = self.window.height - self.video_sprite.height
+                # transform to flipped coordinate system for pyglet
-            # self.frame.img = np.array([]) # clearing memory?
+                self.video_sprite.y = self.window.height - self.video_sprite.height
-            # self.video_sprite.opacity = 70
+                # self.frame.img = np.array([]) # clearing memory?
+                # self.video_sprite.opacity = 70
         except zmq.ZMQError as e:
             # idx = frame.index if frame else "NONE"
             # logger.debug(f"reuse video frame {idx}")

trap/config.py

@@ -251,7 +251,12 @@ connection_parser.add_argument('--zmq-prediction-addr',
 connection_parser.add_argument('--zmq-frame-addr',
                     help='Manually specity communication addr for the frame messages',
                     type=str,
-                    default="ipc:///tmp/feeds_frame")
+                    default="ipc:///tmp/feeds_frame") 
+
+connection_parser.add_argument('--zmq-frame-noimg-addr',
+                    help='Manually specity communication addr for the frame messages',
+                    type=str,
+                    default="ipc:///tmp/feeds_frame2")
 
 
 connection_parser.add_argument('--ws-port',

trap/cv_renderer.py

@@ -334,7 +334,7 @@ class CvRenderer:
         
 
     
-    def run(self):
+    def run(self, timer_counter):
         frame = None
         prediction_frame = None
         tracker_frame = None
@@ -349,6 +349,8 @@ class CvRenderer:
 
         while self.is_running.is_set():
             i+=1
+            with timer_counter.get_lock():
+                timer_counter.value+=1
 
 
             # zmq_ev = self.frame_sock.poll(timeout=2000)
@@ -406,10 +408,10 @@ class CvRenderer:
             # clear out old tracks & predictions:
             
             for track_id, track in list(self.tracks.items()):
-                if get_opacity(track, frame) == 0:
+                if get_animation_position(track, frame) == 1:
                     self.tracks.pop(track_id)
             for prediction_id, track in list(self.predictions.items()):
-                if get_opacity(track, frame) == 0:
+                if get_animation_position(track, frame) == 1:
                     self.predictions.pop(prediction_id)
 
         logger.info('Stopping')
@@ -443,10 +445,10 @@ colorset = [
 #     (0,0,0),
 #  ]
 
-def get_opacity(track: Track, current_frame: Frame):
+def get_animation_position(track: Track, current_frame: Frame):
-    fade_duration = current_frame.camera.fps * 1.5
+    fade_duration = current_frame.camera.fps * 3
     diff = current_frame.index - track.history[-1].frame_nr
-    return max(0, 1 - diff / fade_duration)
+    return max(0, min(1, diff / fade_duration))
     # track.history[-1].frame_nr < (current_frame.index - current_frame.camera.fps * 3)
     # track.history[-1].frame_nr < (current_frame.index - current_frame.camera.fps * 3)
 
@@ -497,8 +499,8 @@ def decorate_frame(frame: Frame, tracker_frame: Frame, prediction_frame: Frame,
             inv_H = np.linalg.pinv(prediction_frame.H)
             # draw_track(img, track, int(track_id))
             draw_trackjectron_history(img, track, int(track.track_id), convert_world_points_to_img_points)
-            opacity = get_opacity(track, frame)
+            anim_position = get_animation_position(track, frame)
-            draw_track_predictions(img, track, int(track.track_id)+1, config.camera, convert_world_points_to_img_points, opacity=opacity)
+            draw_track_predictions(img, track, int(track.track_id)+1, config.camera, convert_world_points_to_img_points, anim_position=anim_position)
             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)
 
     base_color = (255,)*3
@@ -532,6 +534,6 @@ def decorate_frame(frame: Frame, tracker_frame: Frame, prediction_frame: Frame,
     return img
 
     
-def run_cv_renderer(config: Namespace, is_running: BaseEvent):
+def run_cv_renderer(config: Namespace, is_running: BaseEvent, timer_counter):
     renderer = CvRenderer(config, is_running)
-    renderer.run()
+    renderer.run(timer_counter)

trap/frame_emitter.py

@@ -420,6 +420,9 @@ class Frame:
             } for t in self.tracks.values()
         }
 
+    def without_img(self):
+        return Frame(self.index, None, self.time, self.tracks, self.H, self.camera)
+
 def video_src_from_config(config) -> UrlOrPath:
     if config.video_loop:
         video_srcs: Iterable[UrlOrPath] = cycle(config.video_src)
@@ -441,13 +444,18 @@ class FrameEmitter:
         self.frame_sock = context.socket(zmq.PUB)
         self.frame_sock.setsockopt(zmq.CONFLATE, 1) # only keep latest frame. make sure to set BEFORE connect/bind
         self.frame_sock.bind(config.zmq_frame_addr)
+
+        self.frame_noimg_sock = context.socket(zmq.PUB)
+        self.frame_noimg_sock.setsockopt(zmq.CONFLATE, 1) # only keep latest frame. make sure to set BEFORE connect/bind
+        self.frame_noimg_sock.bind(config.zmq_frame_noimg_addr)
         
         logger.info(f"Connection socket {config.zmq_frame_addr}")
+        logger.info(f"Connection socket {config.zmq_frame_noimg_addr}")
 
         self.video_srcs = video_src_from_config(self.config)
 
 
-    def emit_video(self):
+    def emit_video(self, timer_counter):
         i = 0
         delay_generation = False
         for video_path in self.video_srcs:
@@ -462,7 +470,7 @@ class FrameEmitter:
                 video.set(cv2.CAP_PROP_FPS, 5)
                 fps=5
             elif video_path.url.scheme == 'rtsp':
-                gst = f"rtspsrc location={video_path} latency=0 buffer-mode=auto ! decodebin ! videoconvert ! appsink max-buffers=1 drop=true"
+                gst = f"rtspsrc location={video_path} latency=0 buffer-mode=auto ! decodebin ! videoconvert ! appsink max-buffers=0 drop=true"
                 logger.info(f"Capture gstreamer (gst-launch-1.0): {gst}")
                 video = cv2.VideoCapture(gst, cv2.CAP_GSTREAMER)
                 fps=12
@@ -496,7 +504,11 @@ class FrameEmitter:
 
             prev_time = time.time()
             
+            
             while self.is_running.is_set():
+                with timer_counter.get_lock():
+                    timer_counter.value += 1
+
                 ret, img = video.read()
 
                 # seek to 0 if video has finished. Infinite loop
@@ -515,6 +527,7 @@ class FrameEmitter:
                 frame = Frame(index=i, img=img, H=self.config.H, camera=self.config.camera)
                 # TODO: this is very dirty, need to find another way.
                 # perhaps multiprocessing Array?
+                self.frame_noimg_sock.send(pickle.dumps(frame.without_img()))
                 self.frame_sock.send(pickle.dumps(frame))
 
                 # only delay consuming the next frame when using a file.
@@ -540,7 +553,7 @@ class FrameEmitter:
 
       
 
-def run_frame_emitter(config: Namespace, is_running: Event):
+def run_frame_emitter(config: Namespace, is_running: Event, timer_counter: int):
     router = FrameEmitter(config, is_running)
-    router.emit_video()
+    router.emit_video(timer_counter)
     is_running.clear()

trap/plumber.py

@@ -13,6 +13,7 @@ from trap.prediction_server import run_prediction_server
 from trap.preview_renderer import run_preview_renderer
 from trap.animation_renderer import run_animation_renderer
 from trap.socket_forwarder import run_ws_forwarder
+from trap.timer import TimerCollection
 from trap.tracker import run_tracker
 
 from setproctitle import setproctitle, setthreadtitle
@@ -83,20 +84,23 @@ def start():
     
         # queue_listener.handlers.append(socket_handler)
 
-
+    timers = TimerCollection()
+    timer_fe = timers.new('frame_emitter')
+    timer_tracker = timers.new('tracker')
 
     # instantiating process with arguments
     procs = [
         # ExceptionHandlingProcess(target=run_ws_forwarder, kwargs={'config': args, 'is_running': isRunning}, name='forwarder'),
-        ExceptionHandlingProcess(target=run_frame_emitter, kwargs={'config': args, 'is_running': isRunning}, name='frame_emitter'),
+        ExceptionHandlingProcess(target=run_frame_emitter, kwargs={'config': args, 'is_running': isRunning, 'timer_counter': timer_fe.iterations}, name='frame_emitter'),
-        ExceptionHandlingProcess(target=run_tracker, kwargs={'config': args, 'is_running': isRunning}, name='tracker'),
+        ExceptionHandlingProcess(target=run_tracker, kwargs={'config': args, 'is_running': isRunning, 'timer_counter': timer_tracker.iterations}, name='tracker'),
     ]
     
     # if args.render_file or args.render_url or args.render_window:
     if args.render_window or args.render_file or args.render_url:
+        timer_preview = timers.new('preview')
         procs.append(
             # ExceptionHandlingProcess(target=run_cv_renderer, kwargs={'config': args, 'is_running': isRunning}, name='preview')
-            ExceptionHandlingProcess(target=run_cv_renderer, kwargs={'config': args, 'is_running': isRunning}, name='preview')
+            ExceptionHandlingProcess(target=run_cv_renderer, kwargs={'config': args, 'is_running': isRunning, 'timer_counter': timer_preview.iterations}, name='preview')
         )
     if args.render_animation:
         procs.append(
@@ -104,10 +108,21 @@ def start():
         )
 
     if not args.bypass_prediction:
+        timer_predict = timers.new('predict')
         procs.append(
-            ExceptionHandlingProcess(target=run_prediction_server, kwargs={'config': args, 'is_running':isRunning}, name='inference'),
+            ExceptionHandlingProcess(target=run_prediction_server, kwargs={'config': args, 'is_running':isRunning, 'timer_counter': timer_predict.iterations}, name='inference'),
         )
+        
+    def timer_process(timers: TimerCollection, is_running: Event):
+        while is_running.is_set():
+            time.sleep(1)
+            timers.snapshot()
+            print(timers.to_string())
 
+    procs.append(
+            ExceptionHandlingProcess(target=timer_process, kwargs={'is_running':isRunning, 'timers': timers}, name='timer'),
+        )
+    
     try:
         logger.info("start")
         for proc in procs:

trap/prediction_server.py

@@ -166,11 +166,11 @@ class PredictionServer:
     def send_frame(self, frame: Frame):
         if self.external_predictions:
             # data = json.dumps(frame, cls=DataclassJSONEncoder)
-            self.prediction_socket.send_json(frame, cls=DataclassJSONEncoder)
+            self.prediction_socket.send_json(obj=frame, cls=DataclassJSONEncoder)
         else:
             self.prediction_socket.send_pyobj(frame)
 
-    def run(self):
+    def run(self, timer_counter):
         print(self.config)
         if self.config.seed is not None:
             random.seed(self.config.seed)
@@ -247,6 +247,8 @@ class PredictionServer:
         prev_run_time = 0
         while self.is_running.is_set():
             timestep += 1
+            with timer_counter.get_lock():
+                timer_counter.value+=1
             
             # this_run_time = time.time()
             # logger.debug(f'test {prev_run_time - this_run_time}')
@@ -477,7 +479,7 @@ class PredictionServer:
 
             
 
-def run_prediction_server(config: Namespace, is_running: Event):
+def run_prediction_server(config: Namespace, is_running: Event, timer_counter):
 
     # attempt to trace the warnings coming from pytorch
     # def warn_with_traceback(message, category, filename, lineno, file=None, line=None):
@@ -488,4 +490,4 @@ def run_prediction_server(config: Namespace, is_running: Event):
 
     # warnings.showwarning = warn_with_traceback
     s = PredictionServer(config, is_running)
-    s.run()
+    s.run(timer_counter)

trap/timer.py

@@ -1,6 +1,9 @@
+import collections
+from re import A
 import time
 from multiprocessing.sharedctypes import RawValue, Value, Array
 from ctypes import c_double
+from typing import MutableSequence
 
 
 class Timer():
@@ -8,47 +11,58 @@ class Timer():
     Measure 2 independent things: the freuency of tic, and the duration of tic->toc
     Note that indeed these don't need to be equal
     """
-    def __init__(self) -> None:
+    def __init__(self, name = 'timer') -> None:
-        self.last_tic = RawValue(c_double, -1)
+        self.name = name
-        self.last_toc = RawValue(c_double, -1)
+        self.tocs: MutableSequence[(float, int)] = collections.deque(maxlen=5)
-        self.fps = RawValue(c_double, -1)
+        self.iterations = Value('i', 0)
-        self.processing_duration = RawValue(c_double, -1)
-
-        self.smoothing = .1
-
-    def tic(self):
-        now = time.time()
-        if self.last_tic is None:
-            
-            self.last_tic = now
-            return
         
-        duration = now - self.last_tic
+    # def tic(self):
-        self.last_tic = now
+    #     now = time.time()
+    #     if self.last_tic is None:
+            
+    #         self.last_tic = now
+    #         return
+        
+    #     duration = now - self.last_tic
+    #     self.last_tic = now
 
-        current_fps = 1 / duration
+    #     current_fps = 1 / duration
-        if not self.fps:
+    #     if not self.fps:
-            self.fps = current_fps
+    #         self.fps = current_fps
-        else:
+    #     else:
-            self.fps = self.fps * (1-self.smoothing) + current_fps * self.smoothing
+    #         self.fps = self.fps * (1-self.smoothing) + current_fps * self.smoothing
         
     def toc(self):
-        self.last_toc = time.time()
+        self.iterations += 1
-        duration = self.last_toc - self.last_tic
+    
-
+    def snapshot(self):
-        self.processing_duration = self.processing_duration * (1-self.smoothing) + duration * self.smoothing
+        self.tocs.append((time.perf_counter(), self.iterations.value))
-        
 
     @property
     def fps(self):
-        
+        fpses = []
-        pass
+        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
+
 
 class TimerCollection():
     def __init__(self) -> None:
         self._timers = set()
     
-    def print(self)->str:
+    def snapshot(self):
-        print('Update', end='\r')
+        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
 
         

trap/tools.py

@@ -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:
+    opacity = 1-min(1, max(0, inv_lerp(0.8, 1, anim_position))) # fade out
-        current_point = convert_points([current_point])[0]
+    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)):
+        for start, end in zip(line_points[:-1], line_points[1:]):
-            if ci == 0:
+        # for ci in range(0, len(pred_coords)):
-                # TODO)) prev point
+            # if ci == 0:
-                # continue
+            #     # TODO)) prev point
-                start = [int(p) for p in current_point]
+            #     # continue
-                # start = [int(p) for p in coords[-1]]
+            #     start = [int(p) for p in current_point]
-                # start = [0,0]?
+            #     # start = [int(p) for p in coords[-1]]
-                # print(start)
+            #     # start = [0,0]?
-            else:
+            #     # print(start)
-                start = [int(p) for p in pred_coords[ci-1]]
+            # else:
-            end = [int(p) for p in pred_coords[ci]]
+            #     start = [int(p) for p in pred_coords[ci-1]]
-            cv2.line(img, start, end, color, 1, lineType=cv2.LINE_AA)
+            # 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]):

trap/tracker.py

@@ -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 []
@@ -98,6 +98,10 @@ 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):
@@ -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)