From 5ceeda05d745c0c1fd056592a97eea0856559461 Mon Sep 17 00:00:00 2001 From: Ruben van de Ven Date: Tue, 17 Dec 2024 11:10:31 +0100 Subject: [PATCH] slowly fade predicted tracks --- trap/cv_renderer.py | 46 +++++++++++++++++++++++++++++++++++++-------- trap/tools.py | 7 ++++++- 2 files changed, 44 insertions(+), 9 deletions(-) diff --git a/trap/cv_renderer.py b/trap/cv_renderer.py index ccddfa4..8cac9cd 100644 --- a/trap/cv_renderer.py +++ b/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_track_predictions(img, track, int(track_id)+1, config.camera, convert_world_points_to_img_points) + draw_trackjectron_history(img, track, int(track.track_id), 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 diff --git a/trap/tools.py b/trap/tools.py index c638480..eafd495 100644 --- a/trap/tools.py +++ b/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: