slowly fade predicted tracks

trap/cv_renderer.py

@@ -18,7 +18,7 @@ import tempfile
 from pathlib import Path
 import shutil
 import math
-from typing import Iterable, Optional
+from typing import Dict, Iterable, Optional
 
 
 from pyglet import shapes
@@ -73,6 +73,9 @@ class CvRenderer:
         self.tracker_frame: Frame|None = None
         self.prediction_frame: Frame|None = None
 
+        self.tracks: Dict[str, Track] = {}
+        self.predictions: Dict[str, Track] = {}
+
         
         # self.init_shapes()
 
@@ -367,18 +370,24 @@ class CvRenderer:
             
             try:
                 prediction_frame: Frame = self.prediction_sock.recv_pyobj(zmq.NOBLOCK)
+                for track_id, track in prediction_frame.tracks.items():
+                    prediction_id = f"{track_id}-{track.history[-1].frame_nr}"
+                    self.predictions[prediction_id] = track
             except zmq.ZMQError as e:
                 logger.debug(f'reuse prediction')
             
             try:
                 tracker_frame: Frame = self.tracker_sock.recv_pyobj(zmq.NOBLOCK)
+
+                for track_id, track in tracker_frame.tracks.items():
+                    self.tracks[track_id] = track
             except zmq.ZMQError as e:
                 logger.debug(f'reuse tracks')
 
             if first_time is None:
                     first_time = frame.time
 
-            img = decorate_frame(frame, tracker_frame, prediction_frame, first_time, self.config)
+            img = decorate_frame(frame, tracker_frame, prediction_frame, first_time, self.config, self.tracks, self.predictions)
 
             img_path = (self.config.output_dir / f"{i:05d}.png").resolve()
 
@@ -390,6 +399,16 @@ class CvRenderer:
             if self.config.render_window:
                 cv2.imshow('frame',cv2.resize(img, (1920, 1080)))
                 cv2.waitKey(1)
+
+            # clear out old tracks & predictions:
+            
+            for track_id, track in list(self.tracks.items()):
+                if get_opacity(track, frame) == 0:
+                    self.tracks.pop(track_id)
+            for prediction_id, track in list(self.predictions.items()):
+                if get_opacity(track, frame) == 0:
+                    self.predictions.pop(prediction_id)
+
         logger.info('Stopping')
 
         # if i>2:
@@ -421,6 +440,13 @@ colorset = [
 #     (0,0,0),
 #  ]
 
+def get_opacity(track: Track, current_frame: Frame):
+    fade_duration = current_frame.camera.fps * 3
+    diff = current_frame.index - track.history[-1].frame_nr
+    return max(0, 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)
+
 def convert_world_space_to_img_space(H: cv2.Mat):
     """Transform the given matrix so that it immediately converts
     the points to img space"""
@@ -435,8 +461,11 @@ def convert_world_points_to_img_points(points: Iterable):
         return np.array(points) * 100
     return [[p[0]*100, p[1]*100] for p in points]
 
+
+
+
 # Deprecated
-def decorate_frame(frame: Frame, tracker_frame: Frame, prediction_frame: Frame, first_time: float, config: Namespace) -> np.array:
+def decorate_frame(frame: Frame, tracker_frame: Frame, prediction_frame: Frame, first_time: float, config: Namespace, tracks: Dict[str, Track], predictions: Dict[str, Track]) -> np.array:
     # TODO: replace opencv with QPainter to support alpha? https://doc.qt.io/qtforpython-5/PySide2/QtGui/QPainter.html#PySide2.QtGui.PySide2.QtGui.QPainter.drawImage
     # or https://github.com/pygobject/pycairo?tab=readme-ov-file
     # or https://pyglet.readthedocs.io/en/latest/programming_guide/shapes.html
@@ -450,7 +479,7 @@ def decorate_frame(frame: Frame, tracker_frame: Frame, prediction_frame: Frame,
     # Fill image with red color(set each pixel to red)
     overlay[:] = (0, 0, 0)
 
-    img = cv2.addWeighted(dst_img, .7, overlay, .3, 0)
+    img = cv2.addWeighted(dst_img, .1, overlay, .3, 0)
     # img = frame.img.copy()
 
     # all not working:
@@ -466,7 +495,7 @@ def decorate_frame(frame: Frame, tracker_frame: Frame, prediction_frame: Frame,
     if not tracker_frame:
         cv2.putText(img, f"and track", (650,17), cv2.FONT_HERSHEY_PLAIN, 1, (255,255,0), 1)
     else:
-        for track_id, track in tracker_frame.tracks.items():
+        for track_id, track in tracks.items():
             inv_H = np.linalg.pinv(tracker_frame.H)
             draw_track_projected(img, track, int(track_id), config.camera, convert_world_points_to_img_points)
     
@@ -474,11 +503,12 @@ def decorate_frame(frame: Frame, tracker_frame: Frame, prediction_frame: Frame,
         cv2.putText(img, f"Waiting for prediction...", (500,17), cv2.FONT_HERSHEY_PLAIN, 1, (255,255,0), 1)
         # continue
     else:
-        for track_id, track in prediction_frame.tracks.items():
+        for track_id, track in predictions.items():
             inv_H = np.linalg.pinv(prediction_frame.H)
             # draw_track(img, track, int(track_id))
-            draw_trackjectron_history(img, track, int(track_id), convert_world_points_to_img_points)
+            draw_trackjectron_history(img, track, int(track.track_id), convert_world_points_to_img_points)
-            draw_track_predictions(img, track, int(track_id)+1, config.camera, convert_world_points_to_img_points)
+            opacity = get_opacity(track, frame)
+            draw_track_predictions(img, track, int(track.track_id)+1, config.camera, convert_world_points_to_img_points, opacity=opacity)
             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

trap/tools.py

@@ -185,7 +185,10 @@ 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]):
+def draw_track_predictions(img: cv2.Mat, track: Track, color_index: int, camera:Camera, convert_points: Optional[Callable], opacity=1):
+    """
+    Opacity: 0-1
+    """
     if not track.predictions:
         return
 
@@ -201,6 +204,8 @@ def draw_track_predictions(img: cv2.Mat, track: Track, color_index: int, camera:
         # 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: