Decoupled monitoring and draw iff lines

pyproject.toml

@@ -52,6 +52,7 @@ trap_stage = "trap.stage:Stage.parse_and_start"
 trap_prediction = "trap.prediction_server:PredictionServer.parse_and_start"
 trap_render_cv = "trap.cv_renderer:CvRenderer.parse_and_start"
 trap_monitor = "trap.monitor:Monitor.parse_and_start" # migrate timer
+trap_laser_calibration = "trap.laser_calibration:LaserCalibration.parse_and_start" # migrate timer
 
 [tool.uv]
 

supervisord.conf

@@ -28,7 +28,7 @@ directory=%(here)s
 directory=%(here)s
 
 [program:tracker]
-command=uv run trap_tracker
+command=uv run trap_tracker --smooth-tracks
 directory=%(here)s
 
 [program:stage]
@@ -40,7 +40,7 @@ command=uv run trap_prediction --eval_device cuda:0  --model_dir EXPERIMENTS/mod
 directory=%(here)s
 
 [program:render_cv]
-command=uv run trap_render_cv
+command=uv run trap_render_cv 
 directory=%(here)s
 environment=DISPLAY=":0"
 autostart=false

trap/cv_renderer.py

@@ -115,7 +115,7 @@ class CvRenderer(Node):
 
         cv2.namedWindow("frame", cv2.WINDOW_NORMAL)
         # https://gist.github.com/ronekko/dc3747211543165108b11073f929b85e
-        cv2.moveWindow("frame", 1920, -1)
+        cv2.moveWindow("frame", 0, -1)
         if self.config.full_screen:
             cv2.setWindowProperty("frame",cv2.WND_PROP_FULLSCREEN,cv2.WINDOW_FULLSCREEN)
         # bgsub = cv2.createBackgroundSubtractorMOG2(120, 50, detectShadows=True)
@@ -170,10 +170,10 @@ class CvRenderer(Node):
                 self.out_writer.write(img)
             if self.streaming_process:
                 self.streaming_process.stdin.write(img.tobytes())
-            if self.config.render_window:
+            if not self.config.no_window:
                 cv2.imshow('frame',cv2.resize(img, (1920, 1080)))
                 # cv2.imshow('frame',img)
-                cv2.waitKey(1)
+                cv2.waitKey(10)
 
             # clear out old tracks & predictions:
             
@@ -218,8 +218,8 @@ class CvRenderer(Node):
         render_parser.add_argument("--render-file",
                     help="Render a video file previewing the prediction, and its delay compared to the current frame",
                     action='store_true')
-        render_parser.add_argument("--render-window",
+        render_parser.add_argument("--no-window",
-                            help="Render a previewing to a window",
+                            help="Disable a previewing to a window",
                             action='store_true')
         
         render_parser.add_argument("--full-screen",

trap/laser_calibration.py

@@ -0,0 +1,273 @@
+
+
+from argparse import ArgumentParser
+import json
+from pathlib import Path
+from typing import Optional
+
+import cv2
+import numpy as np
+
+from trap.base import DataclassJSONEncoder, DistortedCamera, Frame
+from trap.lines import CoordinateSpace, RenderableLines, SrgbaColor, cross_points
+from trap.node import Node
+from trap.stage import Coordinate
+
+
+
+class LaserCalibration(Node):
+    """
+    A calibrated camera can be used to reverse-map the points of the laser to world coordinates.
+    Note, it publishes on the address of the stage node, so they cannot run at the same time.
+
+    1. Draw points with the laser (use 1-9 to create/select, then position them with arrow keys)
+    2. Use cursor on camera stream to create an image point for.
+        - Locate nearby point to select and drag
+    3. Use image coordinate of point, undistort, homograph, gives world coordinate.
+    4. Perform homography on world coordinates + laser coordinates
+    """
+
+    def setup(self):
+        # self.scenarios: List[DrawnScenario] = []
+        
+        self.frame_sock = self.sub(self.config.zmq_frame_addr)
+        self.laser_sock = self.pub(self.config.zmq_stage_addr)
+
+        self.camera: Optional[DistortedCamera] = None
+
+        self._selected_point = None
+        self._is_dragging = False
+        self.laser_points = {}
+        self.image_points = {}
+        self.H = None
+
+        self.img_size = (1920,1080)
+        self.frame_img_factor = (1,1)
+
+        if self.config.calibfile.exists():
+            with self.config.calibfile.open('r') as fp:
+                calibdata = json.load(fp)
+                self.laser_points = calibdata['laser_points']
+                self.image_points = calibdata['image_points']
+                self.H = calibdata['H']
+
+        
+        
+    
+    def run(self):
+
+        cv2.namedWindow("laser_calib", cv2.WINDOW_NORMAL)
+        # https://gist.github.com/ronekko/dc3747211543165108b11073f929b85e
+        # cv2.moveWindow("laser_calib", 0, -1)
+        cv2.setMouseCallback('laser_calib',self.mouse_event)
+        cv2.setWindowProperty("laser_calib",cv2.WND_PROP_FULLSCREEN,cv2.WINDOW_FULLSCREEN)
+        
+        # arrow up (82), down (84), arrow left(81) 
+        
+        frame = None
+        while self.run_loop_capped_fps(60):
+            if self.frame_sock.poll(0):
+                frame: Frame = self.frame_sock.recv_pyobj()
+                if not self.camera:
+                    self.camera = frame.camera
+
+            if frame is None:
+                continue
+
+            self.frame_img_factor = frame.img.shape[1] / self.img_size[0], frame.img.shape[0] / self.img_size[1]
+            
+
+            img = frame.img
+            img = cv2.resize(img, self.img_size)
+
+            cv2.putText(img, 'press 1-0 to create/edit points', (10,20), cv2.FONT_HERSHEY_SIMPLEX, .5, (255,255,255))
+            if len(self.laser_points) < 4:
+                cv2.putText(img, 'add points to calculate homography', (10,40), cv2.FONT_HERSHEY_SIMPLEX, .5, (255,255,255))
+            else:
+                cv2.putText(img, 'press c to calculate homography', (10,40), cv2.FONT_HERSHEY_SIMPLEX, .5, (255,255,0))
+            
+            cv2.putText(img, str(self.config.calibfile), (10,self.img_size[1]-30), cv2.FONT_HERSHEY_SIMPLEX, .5, (255,255,0))
+
+            if self._selected_point:
+                color = (0,255,255)
+                cv2.putText(img, f'selected {self._selected_point}', (10,60), cv2.FONT_HERSHEY_SIMPLEX, .5, color)
+                cv2.putText(img, 'press d to delete', (10,80), cv2.FONT_HERSHEY_SIMPLEX, .5, color)
+                cv2.putText(img, 'use arrows to position laser for this point', (10,100), cv2.FONT_HERSHEY_SIMPLEX, .5, color)
+                target = self.camera.points_img_to_world([self.image_points[self._selected_point]])[0].tolist()
+                target = round(target[0], 2), round(target[1], 2)
+                cv2.putText(img, f'map {self.laser_points[self._selected_point]} to {target} ({self.image_points[self._selected_point]})', (10,120), cv2.FONT_HERSHEY_SIMPLEX, .5, color)
+            
+
+            for k, coord in self.image_points.items():
+                color = (0,0,255) if self._selected_point == k else (255,0,0)
+                coord = int(coord[0] / self.frame_img_factor[0]), int(coord[1] / self.frame_img_factor[1])
+                cv2.circle(img, coord, 4, color, thickness=2)
+                cv2.putText(img, str(k), (coord[0]+10, coord[1]), cv2.FONT_HERSHEY_SIMPLEX, .5, color)
+
+            key = cv2.waitKey(5) # or for arrows: full_key_code = cv2.waitKeyEx(0)
+            self.key_event(key)
+            # nr_keys = [ord(i) for i in range(10)] # select/add point
+            # cv2.
+            cv2.imshow('laser_calib', img)
+
+            lines = []
+            if self._selected_point:
+                point = self.laser_points[self._selected_point]
+                lines.extend(cross_points(point[0], point[1], 100, SrgbaColor(0,1,0,1)))
+            
+            # render in laser space
+            rl = RenderableLines(lines, CoordinateSpace.LASER)
+            self.laser_sock.send_json(rl, cls=DataclassJSONEncoder)
+        
+        # print(json.dumps(rl, cls=DataclassJSONEncoder))
+
+    def key_event(self, key: int):
+        if key < 0:
+            return
+        
+        if key == ord('q'):
+            exit()
+
+        if key == 27: #esc
+            self._selected_point = None
+
+        
+        if key == ord('c'):
+            self.calculate_homography()
+            self.save()
+        
+        if key == ord('d') and self._selected_point:
+            self.delete_point(self._selected_point)
+            
+        # arrow up (82), down (84), arrow left(81) 
+        if self._selected_point and key in [81, 84, 82, 83,
+                   ord('h'), ord('j'), ord('k'), ord('l'),
+                   ord('H'), ord('J'), ord('K'), ord('L'),
+                   ]:
+            diff = [0,0]
+            if key in [81, ord('h')]:
+                diff[0] -= 1
+            if key == ord('H'):
+                diff[0] -= 10
+            if key in [83, ord('l')]:
+                diff[0] += 1
+            if key == ord('L'):
+                diff[0] += 10
+
+            if key in [82, ord('k')]:
+                diff[1] += 1
+            if key == ord('K'):
+                diff[1] += 10
+            if key in [84, ord('j')]:
+                diff[1] -= 1
+            if key == ord('J'):
+                diff[1] -= 10
+            
+            self.laser_points[self._selected_point] = (
+                self.laser_points[self._selected_point][0] + diff[0],
+                self.laser_points[self._selected_point][1] + diff[1],
+                )
+
+        
+        nr_keys = [ord(str(i)) for i in range(10)]
+        if key in nr_keys:
+            select = str(nr_keys.index(key))
+            self.create_or_select(select)
+
+
+    
+
+    def mouse_event(self, event,x,y,flags,param):
+        x *= self.frame_img_factor[0]
+        y *= self.frame_img_factor[1]
+        if event == cv2.EVENT_MOUSEMOVE:
+            if not self._is_dragging or not self._selected_point:
+                return
+            
+            self.image_points[self._selected_point] = (x, y)
+            
+        if event == cv2.EVENT_LBUTTONDOWN:
+            # select or create
+            self._selected_point = None
+            for i, p in self.image_points.items():
+                d = (p[0]-x)**2 + (p[1]-y)**2
+                if d < 30:
+                    self._selected_point = i
+                    break
+            if self._selected_point is None:
+                self._selected_point = self.new_point((x,y), None)
+
+            self._is_dragging = True
+            
+        if event == cv2.EVENT_LBUTTONUP:
+            self._is_dragging = False
+            # ... point stays selected to tweak laser
+        
+    def create_or_select(self, nr: str):
+        if nr not in self.image_points:
+            self.new_point(None, None, nr)
+        self._selected_point = nr
+        return nr
+
+    def new_point(self, img_coord: Optional[Coordinate], laser_coord: Optional[Coordinate], nr: Optional[str]=None):
+        if nr:
+            new_nr = nr
+        else:
+            new_nr = None
+            for i in range(100):
+                k = str(i)
+                if k not in self.image_points:
+                    new_nr = k
+                    break
+            if not new_nr:
+                new_nr = 0 # cover unlikely case
+
+        self.image_points[new_nr] = img_coord or (100,100)
+        self.laser_points[new_nr] = laser_coord or (100,100)
+        return new_nr
+
+    def delete_point(self, point: str):
+        del self.image_points[point]
+        del self.laser_points[point]
+        self._selected_point = None
+
+    def calculate_homography(self):
+        if len(self.image_points) < 4:
+            return
+        
+        world_points = self.camera.points_img_to_world(list(self.image_points.values()))
+        laser_points = np.array(list(self.laser_points.values()))
+        print('from', world_points)
+        print('to', laser_points)
+        self.H, status = cv2.findHomography(world_points, laser_points)
+        
+        print('Found')
+        print(self.H)
+
+    def save(self):
+        with self.config.calibfile.open('w') as fp:
+            json.dump({
+                'laser_points': self.laser_points,
+                'image_points': self.image_points,
+                'H': self.H.tolist()
+                }, fp)
+        
+
+
+    @classmethod
+    def arg_parser(cls) -> ArgumentParser:
+        argparser = ArgumentParser()
+        argparser.add_argument('--zmq-frame-addr',
+                    help='Manually specity communication addr for the frame messages',
+                    type=str,
+                    default="ipc:///tmp/feeds_frame")
+        argparser.add_argument('--zmq-stage-addr',
+                            help='Manually specity communication addr for the stage  messages (the rendered lines)',
+                            type=str,
+                            default="tcp://0.0.0.0:99174")
+        argparser.add_argument('--calibfile',
+                            help='specify file to save & load points with',
+                            type=Path,
+                            default=Path("./laser_calib.json"))
+        
+        return argparser

trap/lines.py

@@ -1,7 +1,7 @@
 from __future__ import annotations
 
 from dataclasses import dataclass
-from enum import Enum
+from enum import Enum, IntEnum
 import math
 from typing import List, Tuple
 import numpy as np
@@ -13,6 +13,12 @@ See [notebook](../test_path_transforms.ipynb) for examples
 """
 
 RenderablePosition = Tuple[float,float]
+
+class CoordinateSpace(IntEnum):
+    CAMERA = 1
+    UNDISTORTED_CAMERA = 2
+    WORLD = 3
+    LASER = 4
     
 @dataclass
 class SrgbaColor():
@@ -55,12 +61,12 @@ class SimplifyMethod(Enum):
 class RenderableLine():
     points: List[RenderablePoint]
 
-    def as_simplified(self, method: SimplifyMethod = SimplifyMethod.RDP):
+    def as_simplified(self, method: SimplifyMethod = SimplifyMethod.RDP, factor = SIMPLIFY_FACTOR_RDP):
         linestring = [p.position for p in self.points]
         if method == SimplifyMethod.RDP:
-            indexes = simplify_coords_idx(linestring, SIMPLIFY_FACTOR_RDP)
+            indexes = simplify_coords_idx(linestring, factor)
         elif method == SimplifyMethod.VW:
-            indexes = simplify_coords_vw_idx(linestring, SIMPLIFY_FACTOR_VW)
+            indexes = simplify_coords_vw_idx(linestring, factor)
         points = [self.points[i] for i in indexes]
         return RenderableLine(points)
 
@@ -68,11 +74,12 @@ class RenderableLine():
 @dataclass
 class RenderableLines():
     lines: List[RenderableLine]
+    space: CoordinateSpace = CoordinateSpace.WORLD
 
-    def as_simplified(self, method: SimplifyMethod = SimplifyMethod.RDP):
+    def as_simplified(self, method: SimplifyMethod = SimplifyMethod.RDP, factor = SIMPLIFY_FACTOR_RDP):
         """Wraps RenderableLine simplification"""
         return RenderableLines(
-            [line.as_simplified(method) for line in self.lines]
+            [line.as_simplified(method, factor) for line in self.lines]
         )
     
     def append(self, rl: RenderableLine):
@@ -81,6 +88,9 @@ class RenderableLines():
     def append_lines(self, rls: RenderableLines):
         self.lines.extend(rls.lines)
 
+    def point_count(self):
+        return sum([len(l.points) for l in self.lines])
+
     # def merge(self, rl: RenderableLines):
 
 
@@ -91,7 +101,7 @@ def circle_arc(cx, cy, r, t, l, c: SrgbaColor):
     for l*2pi, offset by t. Both t and l are 0<= [t,l] <= 1
     """
     
-    resolution = 40
+    resolution = 30
     steps = int(resolution * l)
     offset = int(resolution * t)
     pointlist: list[RenderablePoint] = []
@@ -102,4 +112,24 @@ def circle_arc(cx, cy, r, t, l, c: SrgbaColor):
         pointlist.append(RenderablePoint((x, y),  c))
     
 
-    return RenderableLine(pointlist)
+    return RenderableLine(pointlist)
+
+def cross_points(cx, cy, r, c: SrgbaColor):
+    # r = 100
+    steps = 3
+    pointlist: list[RenderablePoint] = []
+    for i in range(steps):
+        x = int(cx)
+        y = int(cy + r - i * 2 * r/steps)
+        pos = (x, y)
+        pointlist.append(RenderablePoint(pos, c))
+    path = RenderableLine(pointlist)
+    pointlist: list[RenderablePoint] = []
+    for i in range(steps):
+        y = int(cy)
+        x = int(cx + r - i * 2 * r/steps)
+        pos = (x, y)
+        pointlist.append(RenderablePoint(pos, c))
+    path2 = RenderableLine(pointlist)
+
+    return [path, path2]

trap/monitor.py

@@ -0,0 +1,65 @@
+
+from argparse import ArgumentParser
+import time
+from trap.counter import CounterListerner
+from trap.node import Node
+
+
+class Monitor(Node):
+    """
+    Render a stage, on which different TrackScenarios take place to a
+    single image of lines. Which can be passed to different renderers
+    E.g. the laser or image renderers.
+    """
+
+    FPS = 1
+
+    def setup(self):
+        # self.scenarios: List[DrawnScenario] = []
+        self.counter_listener = CounterListerner()
+            
+    def run(self):
+        prev_time = time.perf_counter()
+        while self.is_running.is_set():
+            # self.tick()  # don't polute it with own data
+
+            self.counter_listener.snapshot()
+            stats = self.counter_listener.to_string()
+            if len(stats):
+                self.logger.info(stats)
+            # else:
+            #     self.logger.info("no stats")
+
+            # for i, (k, v) in enumerate(self.counter_listener.get_latest().items()):
+            #     print(k,v)
+    #     cv2.putText(img, f"{k} {v.value()}", (20,img.shape[0]-(40*i)-40),  cv2.FONT_HERSHEY_PLAIN, 1, base_color, 1)
+            
+            # 3) calculate latency for desired FPS
+            now = time.perf_counter()
+            time_diff = (now - prev_time)
+            if time_diff < 1/self.FPS:
+                # print(f"sleep {1/self.FPS - time_diff}")
+                time.sleep(1/self.FPS - time_diff)
+                now += 1/self.FPS - time_diff
+            
+            prev_time = now
+
+  
+    @classmethod
+    def arg_parser(cls) -> ArgumentParser:
+        argparser = ArgumentParser()
+        # argparser.add_argument('--zmq-trajectory-addr',
+        #             help='Manually specity communication addr for the trajectory messages',
+        #             type=str,
+        #             default="ipc:///tmp/feeds_traj")
+        # argparser.add_argument('--zmq-prediction-addr',
+        #                     help='Manually specity communication addr for the prediction messages',
+        #                     type=str,
+        #                     default="ipc:///tmp/feeds_preds")
+        # argparser.add_argument('--zmq-stage-addr',
+        #                     help='Manually specity communication addr for the stage  messages (the rendered lines)',
+        #                     type=str,
+        #                     default="tcp://0.0.0.0:99174")
+        return argparser
+
+    

trap/node.py

@@ -3,6 +3,7 @@ from logging.handlers import QueueHandler, QueueListener, SocketHandler
 import multiprocessing
 from multiprocessing.synchronize import Event as BaseEvent
 from argparse import ArgumentParser, Namespace
+import time
 from typing import Optional
 
 import zmq
@@ -19,6 +20,8 @@ class Node():
         self.zmq_context = zmq.Context()
         self.logger = self._logger()
 
+        self._prev_loop_time = 0
+
         self.setup()
 
     @classmethod
@@ -43,6 +46,21 @@ class Node():
         self.tick()
         return self.is_running.is_set()
     
+    def run_loop_capped_fps(self, max_fps: float):
+        """Use in run(), to check if it should keep looping
+        Takes care of tick()'ing the iterations/second counter
+        """
+        
+        now = time.perf_counter()
+        time_diff = (now - self._prev_loop_time)
+        if time_diff < 1/max_fps:
+            # print(f"sleep {1/max_fps - time_diff}")
+            time.sleep(1/max_fps - time_diff)
+            now += 1/max_fps - time_diff
+        self._prev_loop_time = now
+        
+        return self.run_loop()
+    
     @classmethod
     def arg_parser(cls) -> ArgumentParser:
         raise RuntimeError("Not implemented arg_parser()")

trap/stage.py

@@ -24,7 +24,7 @@ from trap import shapes
 from trap.base import Camera, DataclassJSONEncoder, DistortedCamera, Frame, ProjectedTrack, Track
 from trap.counter import CounterSender
 from trap.laser_renderer import circle_points, rotateMatrix
-from trap.lines import RenderableLine, RenderableLines, RenderablePoint, RenderablePosition, SrgbaColor, circle_arc
+from trap.lines import RenderableLine, RenderableLines, RenderablePoint, RenderablePosition, SimplifyMethod, SrgbaColor, circle_arc
 from trap.node import Node
 from trap.timer import Timer
 from trap.utils import exponentialDecay, exponentialDecayRounded, relativePointToPolar, relativePolarToPoint
@@ -56,6 +56,9 @@ class AppendableLine(LineGenerator):
         self.ready = len(self.points) == 0
         self.draw_decay_speed = draw_decay_speed
 
+    def nr_of_passed_points(self):
+        """The number of points passed in the animation"""
+        return len(self._drawn_points) - 1
 
     def update_drawn_positions(self, dt: DeltaT):
         if len(self.points) == 0:
@@ -164,6 +167,7 @@ class DiffSegment():
      Scenario's anomaly score.
     """
     DRAW_DECAY_SPEED = 25
+    POINT_INTERVAL = 4
 
     def __init__(self, prediction: ProjectedTrack):
         self.ptrack = prediction
@@ -177,6 +181,12 @@ class DiffSegment():
 
     def finish(self):
         self.finished = True
+    
+    def nr_of_passed_points(self):
+        if isinstance(self.line, AppendableLine):
+            return self.line.nr_of_passed_points()  * self.POINT_INTERVAL
+        else:
+            return len(self.points) * self.POINT_INTERVAL
 
     # run on each track update received
     def update_track(self, track: ProjectedTrack):
@@ -204,7 +214,7 @@ class DiffSegment():
             line = []
             for i, (p1, p2) in enumerate(zip(trajectory_range, prediction_range)):
                 offset_from_start = (pred_diff_steps_forward + i)
-                if offset_from_start % 4 == 0:
+                if offset_from_start % self.POINT_INTERVAL == 0:
                     self.line.points.extend([p1, p2])
                     self.points.extend([p1, p2])
         
@@ -222,33 +232,6 @@ class DiffSegment():
         if isinstance(self.line, ProceduralChain):
             self.line.target = self._target_track.projected_history[-1]
 
-        # if len(self.points) == 0:
-        #     # nothing to draw yet
-        #     return
-
-        # # self._drawn_points = self.points
-        
-        # if len(self._drawn_points) == 0:
-        #     # create origin
-        #     self._drawn_points.append(self.points[0])
-        #     # and drawing head
-        #     self._drawn_points.append(self.points[0]) 
-        
-        # idx = len(self._drawn_points) - 1
-        # target = self.points[idx]
-
-        # if np.isclose(self._drawn_points[-1], target, atol=.05).all():
-        #     # TODO: might want to migrate to np.isclose()
-        #     if len(self._drawn_points) == len(self.points):
-        #         self.ready = True
-        #         return # done until a new point is added
-        #     # add new point as drawing head
-        #     self._drawn_points.append(self._drawn_points[-1]) 
-        # self.ready = False
-
-        # x = exponentialDecayRounded(self._drawn_points[-1][0], target[0], self.DRAW_DECAY_SPEED, dt, .05)
-        # y = exponentialDecayRounded(self._drawn_points[-1][1], target[1], self.DRAW_DECAY_SPEED, dt, .05)
-        # self._drawn_points[-1] = (float(x), float(y))
 
         # if not self.finished or not self.line.ready:
         self.line.update_drawn_positions(dt)
@@ -284,8 +267,8 @@ PREDICTION_FADE_SLOPE: float = -10
 PREDICTION_FADE_AFTER_DURATION: float = 10 # seconds
 PREDICTION_END_FADE = 2 #frames
 # TRACK_MAX_POINTS = 100
-TRACK_FADE_AFTER_DURATION = 10. # seconds
+TRACK_FADE_AFTER_DURATION = 8. # seconds
-TRACK_END_FADE = 50 # points
+TRACK_END_FADE = 30 # points
 TRACK_FADE_ASSUME_FPS = 12
 
 # Don't render the first n points of the prediction,
@@ -309,6 +292,7 @@ class TrackScenario(StateMachine):
 
     receive_prediction = detected.to(first_prediction) | substantial.to(first_prediction) | first_prediction.to(corrected_prediction, cond="prediction_is_stale") | corrected_prediction.to(play, cond="prediction_is_playing")
 
+
     def __init__(self):
         self.track: ProjectedTrack = None
         self.camera: Optional[Camera] = None
@@ -341,7 +325,7 @@ class TrackScenario(StateMachine):
         return False
     
     def check_lost(self):
-        if self.current_state is not self.lost and self.track and self.track.created_at < time.time() - 5:
+        if self.current_state is not self.lost and self.track and self.track.updated_at < time.time() - 5:
             self.mark_lost()
     
     def set_track(self, track: ProjectedTrack):
@@ -464,8 +448,8 @@ class DrawnScenario(TrackScenario):
     """
 
     ANOMALY_DECAY = .2 # speed with which the cirlce shrinks over time
-    DISTANCE_ANOMALY_FACTOR = .05 # the ammount to which the difference counts to the anomaly score
+    DISTANCE_ANOMALY_FACTOR = .03 # the ammount to which the difference counts to the anomaly score
-    MAX_HISTORY = 80 # points of history of trajectory to display (preventing too long lines)
+    MAX_HISTORY = 100 # points of history of trajectory to display (preventing too long lines)
     CUT_GAP = 5 # when adding a new prediction, keep the existing prediction until that point + this CUT_GAP margin
 
     def __init__(self):
@@ -525,7 +509,8 @@ class DrawnScenario(TrackScenario):
         # 1. track history, direct update
         
         # positions = self._track.get_projected_history(None, self.camera)[-MAX_HISTORY:]
-        self.drawn_positions = self.track.projected_history[-self.MAX_HISTORY:]
+        # self.drawn_positions = self.track.projected_history[-self.MAX_HISTORY:]
+        self.drawn_positions = self.track.projected_history
         
         # 3. predictions
         if len(self.drawn_predictions) < len(self.predictions):
@@ -533,21 +518,24 @@ class DrawnScenario(TrackScenario):
             if len(self.drawn_predictions) == 0:
                 self.drawn_predictions.append(self.predictions[-1].predictions[0])
             else:
-                # cut existing prediction
+                # if a new prediction has arised, transition from existing one.
-                end_step = self.predictions[-1].frame_index - self.predictions[-2].frame_index + self.CUT_GAP
+                # First, cut existing prediction
-                # print(end_step)
+                # CUT_GAP indicates that some is lost in the transition, to prevent glitches when velocity of person changes
+                end_step = self.predictions[-1].frame_index - self.predictions[-2].frame_index + self.CUT_GAP 
                 keep = self.drawn_predictions[-1][end_step:]
                 last_item: Coordinate = keep[-1]
-                self.drawn_predictions[-1] = self.drawn_predictions[-1][:end_step]
+                self.drawn_predictions[-1] = self.drawn_predictions[-1][:end_step] # cut the old part
                 # print(self.predictions[-1].frame_index, self.predictions[-2].frame_index, end_step, len(keep))
-                ext = [last_item] * (len(self.predictions[-1].predictions[0]) - len(keep))
+                # duplicate last item, so the new one has the same nr. of points as the incoming prediction (so it can actually transition)
-                # print(ext)
+                ext = [last_item] * (len(self.predictions[-1].predictions[0]) - len(keep)) 
                 keep.extend(ext)
                 self.drawn_predictions.append(keep)
         
         for a, drawn_prediction in enumerate(self.drawn_predictions):
             # origin =  self.predictions[a].predictions[0][0]
             origin =  self.predictions[a].predictions[0][0]
+            # associated_diff = self.prediction_diffs[a]
+            # progress = associated_diff.nr_of_passed_points()
             for i, pos in enumerate(drawn_prediction):
                 # TODO: this should be done in polar space starting from origin (i.e. self.drawn_posision[-1])
                 decay = max(3, (18/i) if i else 10) # points further away move with more delay
@@ -624,7 +612,7 @@ class DrawnScenario(TrackScenario):
 
     def to_renderable_lines(self) -> RenderableLines:
         t = time.time()
-        track_age = t - self.track.created_at
+        track_age = t - self.track.updated_at # Should be beginning
         lines = RenderableLines([])
         
 
@@ -633,8 +621,11 @@ class DrawnScenario(TrackScenario):
         # track_max_points = TRACK_FADE_AFTER_DURATION * TRACK_FADE_ASSUME_FPS - track_age_in_frames
 
         # 1. Trajectory history
+        # drawable_points, alphas = self.drawn_positions[:self.MAX_HISTORY], [1]*len(self.drawn_positions)
+
         drawable_points, alphas = points_fade_out_alpha_mask(self.drawn_positions, track_age, TRACK_FADE_AFTER_DURATION, TRACK_END_FADE)
         color = SrgbaColor(1.,0.,0.,1.-self.lost_factor())
+
         points = [RenderablePoint(pos, color.as_faded(a)) for pos, a in zip(drawable_points, alphas)]
         lines.append(RenderableLine(points))
 
@@ -642,9 +633,21 @@ class DrawnScenario(TrackScenario):
 
         anomaly_marker_color = SrgbaColor(0.,0.,1, 1.-self.lost_factor()) # fadeout
         # lines.append(circle_arc(self.drawn_positions[-1][0], self.drawn_positions[-1][1], 1, t, self.anomaly_score, anomaly_marker_color))
+        # last point, (but this draws line in circle, requiring a 'jump back' for the laser)
+        cx, cy = self.drawn_positions[-1][0], self.drawn_positions[-1][1],
+        radius = max(.1, self._drawn_anomaly_score * 1.)
+
+        steps=5
+        if len(self.drawn_positions) >= steps:
+            dx, dy = self.drawn_positions[-1][0] - self.drawn_positions[-steps][0], self.drawn_positions[-1][1] - self.drawn_positions[-steps][1],
+            diff = np.array([dx,dy])
+            diff = diff/np.linalg.norm(diff) * radius * 1.1
+            cx += diff[0]
+            cy += diff[1]
+
         lines.append(circle_arc(
-            self.drawn_positions[-1][0], self.drawn_positions[-1][1],
+            cx, cy,
-            max(.1, self._drawn_anomaly_score * 1.),
+            radius,
             0, 1,
             anomaly_marker_color)
             )
@@ -655,7 +658,11 @@ class DrawnScenario(TrackScenario):
             prediction_track_age = time.time() - self.predictions[0].created_at
             t_factor = prediction_track_age / PREDICTION_FADE_IN
             # positions = [RenderablePosition.from_list(pos) for pos in self.drawn_positions]
-            for drawn_prediction in self.drawn_predictions:
+            for a, drawn_prediction in enumerate(self.drawn_predictions):
+
+
+                associated_diff = self.prediction_diffs[a]
+                progress = associated_diff.nr_of_passed_points()
 
                 # drawn_prediction, alphas1 = points_fade_out_alpha_mask(drawn_prediction, prediction_track_age, TRACK_FADE_AFTER_DURATION, TRACK_END_FADE, no_frame_max=True)
                 
@@ -674,6 +681,7 @@ class DrawnScenario(TrackScenario):
                 
                 # points = [RenderablePoint(pos, pos_color) for pos, pos_color in zip(drawn_prediction[PREDICTION_OFFSET:], colors[PREDICTION_OFFSET:])]
                 points = [RenderablePoint(pos, pos_color) for pos, pos_color in zip(drawn_prediction, colors)]
+                points = points[progress//2:]
                 lines.append(RenderableLine(points))
 
         # 4. Diffs
@@ -870,10 +878,12 @@ class Stage(Node):
         # rl = RenderableLines(lines)
         # with open('/tmp/lines.pcl', 'wb') as fp:
         #     pickle.dump(rl, fp)
-        rl = lines.as_simplified() # or segmentise (see shapely)
+        rl = lines.as_simplified(SimplifyMethod.RDP, .01) # or segmentise (see shapely)
         self.counter.set("stage.lines", len(lines.lines))
+        self.counter.set("stage.points_orig", lines.point_count())
+        self.counter.set("stage.points", rl.point_count())
         # print(rl.__dict__)
-        self.stage_sock.send_json(rl, cls=DataclassJSONEncoder)
+        self.stage_sock.send_json(obj=rl, cls=DataclassJSONEncoder)
         
         # print(json.dumps(rl, cls=DataclassJSONEncoder))