Data and viz options
This commit is contained in:
Ruben van de Ven
parent
627b320ec7
commit
cc952424e0
7 changed files with 103 additions and 44 deletions
File diff suppressed because one or more lines are too long
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@ -95,7 +95,7 @@ class AnimationRenderer:
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corners=[[471, 304], [1797, 376], [467, 387], [1792, 484]])
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self.window.push_handlers(self.pins)
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pyglet.gl.glClearColor(0,0,0, 0)
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pyglet.gl.glClearColor(255,255,255,255)
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self.fps_display = pyglet.window.FPSDisplay(window=self.window, color=(255,255,255,255))
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self.fps_display.label.x = self.window.width - 50
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self.fps_display.label.y = self.window.height - 17
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@ -115,6 +115,7 @@ class AnimationRenderer:
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self.batch_overlay = pyglet.graphics.Batch()
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self.batch_anim = pyglet.graphics.Batch()
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if self.config.render_debug_shapes:
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self.debug_lines = [
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pyglet.shapes.Line(1370, self.config.camera.h-360, 1380, 670-360, 2, (255,255,255,255), batch=self.batch_overlay),#v
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pyglet.shapes.Line(0, 660-360, 1380, 670-360, 2, (255,255,255,255), batch=self.batch_overlay), #h
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@ -277,7 +278,7 @@ class AnimationRenderer:
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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.video_sprite.opacity = 90
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self.video_sprite.opacity = 10
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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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@ -306,12 +307,19 @@ class AnimationRenderer:
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# # TODO fade out
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# del self.drawn_tracks[track_id]
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if self.tracker_frame:
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for track_id, track in self.tracker_frame.tracks.items():
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if track_id not in self.drawn_tracks:
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self.drawn_tracks[track_id] = DrawnTrack(track_id, track, self, self.tracker_frame.H, PROJECTION_MAP, self.config.camera)
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else:
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self.drawn_tracks[track_id].set_track(track)
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if self.prediction_frame:
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for track_id, track in self.prediction_frame.tracks.items():
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if track_id not in self.drawn_tracks:
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self.drawn_tracks[track_id] = DrawnTrack(track_id, track, self, self.prediction_frame.H, PROJECTION_MAP, self.config.camera)
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else:
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self.drawn_tracks[track_id].set_track(track)
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self.drawn_tracks[track_id].set_predictions(track)
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# clean up
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for track_id in list(self.drawn_tracks.keys()):
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@ -364,6 +372,8 @@ class AnimationRenderer:
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shape.draw()
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# self.batch_anim.draw()
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self.batch_overlay.draw()
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if self.config.render_debug_shapes:
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self.pins.draw()
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# pyglet.graphics.draw(3, pyglet.gl.GL_LINE, ("v2i", (100,200, 600,800)), ('c3B', (255,255,255, 255,255,255)))
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@ -319,6 +319,9 @@ render_parser.add_argument("--render-window",
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render_parser.add_argument("--render-no-preview",
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help="No preview, but only animation",
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action='store_true')
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render_parser.add_argument("--render-debug-shapes",
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help="Lines and points for debugging/mapping",
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action='store_true')
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render_parser.add_argument("--full-screen",
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help="Set Window full screen",
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action='store_true')
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@ -303,16 +303,16 @@ class PredictionServer:
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history = history_cm_to_m(history)
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history = np.array(history)
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x = history[:, 0] #- cx
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y = history[:, 1] #- cy
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x = history[:, 0] #- cx # we can create bigger steps by doing history[::5,0]
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y = history[:, 1] #- cy # history[::5,1]
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if self.config.center_data:
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x -= cx
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y -= cy
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# TODO: calculate dt based on input
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vx = derivative_of(x, 0.1) #eval_scene.dt
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vy = derivative_of(y, 0.1)
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ax = derivative_of(vx, 0.1)
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ay = derivative_of(vy, 0.1)
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vx = derivative_of(x, .1) #eval_scene.dt
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vy = derivative_of(y, .1)
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ax = derivative_of(vx, .1)
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ay = derivative_of(vy, .1)
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data_dict = {('position', 'x'): x[:], # [-10:-1]
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('position', 'y'): y[:], # [-10:-1]
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@ -445,6 +445,7 @@ class PredictionServer:
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frame = self.smoother.smooth_frame_predictions(frame)
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self.prediction_socket.send_pyobj(frame)
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time.sleep(.5)
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logger.info('Stopping')
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@ -72,6 +72,7 @@ class DrawnTrack:
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self.camera = camera
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self.H = H # TODO)) Move H to Camera object
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self.set_track(track, H)
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self.set_predictions(track, H)
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self.drawn_positions = []
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self.drawn_predictions = []
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self.shapes: list[pyglet.shapes.Line] = []
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@ -87,6 +88,8 @@ class DrawnTrack:
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# perhaps only do in constructor:
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self.inv_H = np.linalg.pinv(self.H)
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def set_predictions(self, track: Track, H = None):
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pred_coords = []
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if track.predictions:
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if self.draw_projection == PROJECTION_IMG:
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@ -116,7 +119,7 @@ class DrawnTrack:
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for i, pos in enumerate(drawn_prediction):
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# TODO: this should be done in polar space starting from origin (i.e. self.drawn_posision[-1])
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decay = max(3, (18/i) if i else 10) # points further away move with more delay
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decay = 6
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decay = 16
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origin = self.drawn_positions[-1]
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drawn_r, drawn_angle = relativePointToPolar( origin, drawn_prediction[i])
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pred_r, pred_angle = relativePointToPolar(origin, self.pred_coords[a][i])
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@ -179,7 +182,8 @@ class DrawnTrack:
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# for i, pos in drawn_predictions.enumerate():
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for ci in range(0, len(drawn_predictions)):
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if ci == 0:
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x, y = [int(p) for p in self.drawn_positions[-1]]
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continue
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# x, y = [int(p) for p in self.drawn_positions[-1]]
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else:
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x, y = [int(p) for p in drawn_predictions[ci-1]]
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@ -191,7 +195,9 @@ class DrawnTrack:
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if ci >= len(self.pred_shapes[a]):
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# TODO: add color2
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line = self.renderer.gradientLine(x, y, x2, y2, 3, color, color, batch=self.renderer.batch_anim)
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# line = self.renderer.gradientLine(x, y, x2, y2, 3, color, color, batch=self.renderer.batch_anim)
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line = pyglet.shapes.Line(x,y ,x2, y2, 1.5, color, batch=self.renderer.batch_anim)
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# line = pyglet.shapes.Arc(x,y ,1.5, thickness=1.5, color=color, batch=self.renderer.batch_anim)
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line.opacity = 5
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self.pred_shapes[a].append(line)
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@ -203,9 +209,9 @@ class DrawnTrack:
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decay = (16/ci) if ci else 16
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half = len(drawn_predictions) / 2
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if ci < half:
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target_opacity = 180
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target_opacity = 60
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else:
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target_opacity = (1 - ((ci - half) / half)) * 180
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target_opacity = (1 - ((ci - half) / half)) * 60
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line.opacity = int(exponentialDecay(line.opacity, target_opacity, decay, dt))
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@ -688,10 +694,13 @@ class PreviewRenderer:
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# (255, 0, 255),
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# (255, 255, 0)
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# ]
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# colorset = [
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# (255,255,100),
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# (255,100,255),
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# (100,255,255),
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# ]
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colorset = [
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(255,255,100),
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(255,100,255),
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(100,255,255),
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(0,0,0),
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]
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# Deprecated
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@ -90,7 +90,7 @@ def augment(scene):
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# maybe_makedirs('trajectron-data')
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# for desired_source in [ 'hof2', ]:# ,'hof-maskrcnn', 'hof-yolov8', 'VIRAT-0102-parsed', 'virat-resnet-keypoints-full']:
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def process_data(src_dir: Path, dst_dir: Path, name: str, smooth_tracks: bool, cm_to_m: bool, center_data: bool):
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def process_data(src_dir: Path, dst_dir: Path, name: str, smooth_tracks: bool, cm_to_m: bool, center_data: bool, bin_positions: bool):
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print(f"Process data in {src_dir}, to {dst_dir}, identified by {name}")
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nl = 0
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@ -117,12 +117,18 @@ def process_data(src_dir: Path, dst_dir: Path, name: str, smooth_tracks: bool, c
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all_data['pos_x'] /= 100
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all_data['pos_y'] /= 100
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mean_x, mean_y = all_data['pos_x'].mean(), all_data['pos_y'].mean()
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cx = .5 * all_data['pos_x'].min() + .5 * all_data['pos_x'].max()
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cy = .5 * all_data['pos_y'].min() + .5 * all_data['pos_y'].max()
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print(f"Dataset means: {mean_x=} {mean_y=}")
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print(f"Dataset centers: {cx=} {cy=}")
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# bins of .5 meter
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# print(np.ceil(all_data['pos_x'].max())*2))
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if bin_positions:
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space_x = np.linspace(0, np.ceil(all_data['pos_x'].max()), int(np.ceil(all_data['pos_x'].max())*2)+1)
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space_y = np.linspace(0, np.ceil(all_data['pos_y'].max()), int(np.ceil(all_data['pos_y'].max())*2)+1)
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print(f"Dataset means: {mean_x=} {mean_y=}, (min: ({all_data['pos_x'].min()}, {all_data['pos_y'].min()}), max: ({all_data['pos_x'].max()}, {all_data['pos_y'].max()}))")
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print(f"Dataset centers: {cx=} {cy=}")
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for data_class in ['train', 'val', 'test']:
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env = Environment(node_type_list=['PEDESTRIAN'], standardization=standardization)
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@ -174,6 +180,12 @@ def process_data(src_dir: Path, dst_dir: Path, name: str, smooth_tracks: bool, c
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data['pos_x'] -= cx
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data['pos_y'] -= cy
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if bin_positions:
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data['pos_x'] =np.digitize(data['pos_x'], bins=space_x)
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data['pos_y'] =np.digitize(data['pos_y'], bins=space_y)
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print(data['pos_x'])
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# Mean Position
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print("Means: x:", data['pos_x'].mean(), "y:", data['pos_y'].mean())
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@ -199,9 +211,22 @@ def process_data(src_dir: Path, dst_dir: Path, name: str, smooth_tracks: bool, c
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skipped_for_error += 1
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continue
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# without repeats, there will mostli likely only be straight movements
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# better to filter by time
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# only_diff = node_df[['pos_x', 'pos_y']].diff().fillna(1).any(axis=1)
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# # print(node_df[['pos_x', 'pos_y']], )
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# # exit()
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# # mask positions
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# node_values = node_df[only_diff][['pos_x', 'pos_y']].values
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# print(node_values)
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if bin_positions:
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node_values = node_df.iloc[::5, :][['pos_x', 'pos_y']].values
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else:
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node_values = node_df[['pos_x', 'pos_y']].values
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# print(node_values)
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if node_values.shape[0] < min_track_length:
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continue
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@ -262,6 +287,7 @@ def main():
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parser.add_argument("--smooth-tracks", action='store_true', help=f"Enable smoother. Set to {smooth_window} frames")
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parser.add_argument("--cm-to-m", action='store_true', help=f"If homography is in cm, convert tracked points to meter for beter results")
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parser.add_argument("--center-data", action='store_true', help=f"Normalise around center")
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parser.add_argument("--bin-positions", action='store_true', help=f"Experiment to put round positions to a grid")
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args = parser.parse_args()
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process_data(**args.__dict__)
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@ -443,7 +443,8 @@ class Smoother:
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else:
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# "Unlike Kalman filtering, which focuses on predicting and updating the current state using historical measurements, Kalman smoothing enhances the accuracy of past state values"
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# see https://medium.com/@shahalkp1/kalman-smoothing-using-tsmoothie-0175260464e5
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self.smoother = KalmanSmoother(component='level_trend_season', component_noise={'level':0.03, 'season': .02, 'trend':0.04},n_seasons = 2, copy=None)
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self.smoother = KalmanSmoother(component='level_trend', component_noise={'level':0.03, 'season': .02, 'trend':0.04},n_seasons = 2, copy=None)
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def smooth(self, points: List[float]):
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