filter lidar pcd with space outline
This commit is contained in:
Ruben van de Ven
parent
acdb869430
commit
e09c9d44e8
3 changed files with 107 additions and 27 deletions
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@ -161,6 +161,7 @@ class LidarTracker(Node):
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self.debug_lines = load_lines_from_svg(self.config.debug_map, 100, '') if self.config.debug_map else []
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self.map_outline = None
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self.map_outline_volume = None
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if self.config.map_outlines:
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lines = load_lines_from_svg(self.config.map_outlines, 100, '')
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@ -170,6 +171,17 @@ class LidarTracker(Node):
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if len(lines) > 1:
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logger.warning("Multiple lines in outline file, using first only")
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self.map_outline = shapely.Polygon([p.position for p in lines[0].points])
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self.map_outline_volume = o3d.visualization.SelectionPolygonVolume()
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self.map_outline_volume.orthogonal_axis = "Z" # extrusion direction of polygon
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self.map_outline_volume.axis_min = 0
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self.map_outline_volume.axis_max = 3.5
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polygon_points =np.array([[*p.position, 0] for p in lines[0].points])
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self.map_outline_volume.bounding_polygon = o3d.utility.Vector3dVector(polygon_points)
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self.remotes = {}
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@ -276,10 +288,46 @@ class LidarTracker(Node):
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lidar_items = next(self.sequence_generator)
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current_pcd = self.build_cloud(lidar_items)
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current_pcd = filter_pcd_points_below_z(current_pcd, .1)
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current_pcd = filter_raw_points_by_distance(current_pcd, 10)
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if self.map_outline and self.get_setting('lidar.crop_map_boundaries', False):
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current_pcd = filter_pcd_points_outside_bounds(current_pcd, self.map_outline)
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# current_pcd = filter_pcd_points_below_z(current_pcd, .1)
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# current_pcd = filter_raw_points_by_distance(current_pcd, 10)
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filtered_pcds: List[o3d.geometry.PointCloud] = []
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updated_live_pcd = False
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if self.map_outline_volume:
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# t0 = time.perf_counter()
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if self.get_setting('lidar.crop_map_boundaries', True):
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if not self.get_setting('lidar.viz_cropping', False):
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current_pcd = self.map_outline_volume.crop_point_cloud(current_pcd)
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else: # some more effort to visualise what falls outside
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cropping_indexes = self.map_outline_volume.crop_in_polygon(current_pcd)
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in_color = np.array([1,1,0]).reshape(1,-1)
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out_color = np.array([0,0,1]).reshape(1,-1)
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mask_array = np.zeros(len(current_pcd.points), dtype=int)
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mask_array[cropping_indexes] = 1
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# print(any(cropping_indexes), all(cropping_indexes))
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colors = np.where(mask_array[:,None], in_color, out_color)
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# update drawn pcd with two colors
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updated_live_pcd = True
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live_pcd.points = current_pcd.points
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live_pcd.colors = o3d.utility.Vector3dVector(colors)
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# still crop
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current_pcd = current_pcd.select_by_index(cropping_indexes)
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if self.config.viz and not updated_live_pcd:
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live_pcd.points = current_pcd.points
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live_pcd.colors = current_pcd.colors
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# current_pcd = current_pcd.select_by_index(cropping_indexes)
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# outside_pcd = current_pcd.select_by_index(cropping_indexes, invert=True)
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# print(time.perf_counter()- t0)
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# pass
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# current_pcd = self.map_outline_volume.crop_point_cloud(current_pcd)
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# if self.map_outline and self.get_setting('lidar.crop_map_boundaries', False):
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# current_pcd = filter_pcd_points_outside_bounds(current_pcd, self.map_outline)
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# a = list(lidar_items.keys())
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# stamp, lidar_points = lidar_items[a[0]]
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@ -309,23 +357,25 @@ class LidarTracker(Node):
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# a = time.perf_counter()
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filtered_pcd = self.room_filter.remove_static(current_pcd)
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filtered_pcd, dropped_indexes = self.room_filter.remove_static(current_pcd)
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if self.config.viz:
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live_pcd = live_pcd.select
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stat_static = len(filtered_pcd.points)
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if self.config.viz:
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live_pcd.points = current_pcd.points
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if self.room_filter.initialised:
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# filtered_pcd, _ = filtered_pcd.remove_statistical_outlier(nb_neighbors=20, std_ratio=2.0)
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filtered_pcd, _ = filtered_pcd.remove_radius_outlier(nb_points=5, radius=0.2)
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filtered_pcd, inlier_indexes = filtered_pcd.remove_radius_outlier(nb_points=5, radius=0.2)
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stat_denoise = len(filtered_pcd.points)
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# down sample
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filtered_pcd = filtered_pcd.voxel_down_sample(voxel_size=0.15)
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filtered_pcd = filtered_pcd.voxel_down_sample(voxel_size=0.05)
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if self.config.viz:
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live_filtered_pcd.points = filtered_pcd.points
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@ -338,7 +388,7 @@ class LidarTracker(Node):
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# filtered_pcd2 = room_filter2.remove_static(current_pcd)
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# c = time.perf_counter()
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# print(f"after static object removal: {stat_static} / after outlier removal: {stat_denoise} / after_downsample: {stat_downsampled}")
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print(f"after static object removal: {stat_static} / after outlier removal: {stat_denoise} / after_downsample: {stat_downsampled}")
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# pcd.points = filtered_pcd.points
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@ -443,7 +493,7 @@ class LidarTracker(Node):
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if self.config.viz:
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color = [0.5, 0.5, 0.7] if self.room_filter.initialised else [0.7, 0.7, 0.7]
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live_pcd.paint_uniform_color(color)
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# live_pcd.paint_uniform_color(color)
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live_filtered_pcd.paint_uniform_color([0.2, 0.7, 0.2])
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if not geom_added:
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@ -774,10 +824,13 @@ class VoxelOccupancyFilter:
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# Filter out static points from current point cloud
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filtered_points = []
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for pt in np.asarray(current_pcd.points):
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dropped_indexes = []
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for i, pt in enumerate(np.asarray(current_pcd.points)):
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voxel = tuple(np.floor(pt / self.voxel_size).astype(np.int32))
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if voxel not in self.static_voxels:
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filtered_points.append(pt)
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else:
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dropped_indexes.append(i)
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# Update history: until full, from there every n frame
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@ -804,7 +857,7 @@ class VoxelOccupancyFilter:
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filtered_pcd = o3d.geometry.PointCloud()
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if filtered_points:
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filtered_pcd.points = o3d.utility.Vector3dVector(np.array(filtered_points))
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return filtered_pcd
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return filtered_pcd, dropped_indexes
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class DecayingVoxelOccupancyFilter:
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@ -33,7 +33,8 @@ class Settings(Node):
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dpg.add_button(label="Save", callback=self.save)
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with dpg.window(label="Lidar", pos=(0, 150)):
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self.register_setting(f'lidar.crop_map_boundaries', dpg.add_checkbox(label="crop_map_boundaries", default_value=self.get_setting(f'lidar.crop_map_boundaries', False), callback=self.on_change))
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self.register_setting(f'lidar.crop_map_boundaries', dpg.add_checkbox(label="crop_map_boundaries", default_value=self.get_setting(f'lidar.crop_map_boundaries', True), callback=self.on_change))
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self.register_setting(f'lidar.viz_cropping', dpg.add_checkbox(label="viz_cropping", default_value=self.get_setting(f'lidar.viz_cropping', True), callback=self.on_change))
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for lidar in ["192.168.0.16", "192.168.0.10"]:
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name = lidar.replace(".", "_")
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with dpg.window(label=f"Lidar {lidar}", pos=(200, 0),autosize=True):
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@ -75,7 +75,7 @@ class ScenarioScene(Enum):
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SUBSTANTIAL = SceneInfo(6, "Multiple detections")
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FIRST_PREDICTION = SceneInfo(10, "Prediction is ready")
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CORRECTED_PREDICTION = SceneInfo(11, "Multiple predictions")
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LOITERING = SceneInfo(7, "Foundto be loitering", takeover_possible=True)
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LOITERING = SceneInfo(7, "Foundto be loitering", takeover_possible=True) # TODO: create "possible after"
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PLAY = SceneInfo(7, description="After many predictions; just fooling around", takeover_possible=True)
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LOST = SceneInfo(-1, description="Track lost", takeover_possible=True)
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@ -191,7 +191,7 @@ class Scenario:
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if predictions == 1:
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self.set_scene(ScenarioScene.FIRST_PREDICTION)
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return True
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if predictions > 10:
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if predictions > 30:
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self.set_scene(ScenarioScene.PLAY)
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return True
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if predictions:
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@ -253,7 +253,19 @@ class Scenario:
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self.update_state()
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def build_line_others():
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others_color = SrgbaColor(1,1,0,1)
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line_others = LineAnimationStack(StaticLine([], others_color))
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# line_others.add(SegmentLine(line_others.tail, duration=3, anim_f=partial(SegmentLine.anim_grow, in_and_out=True, max_len=5)))
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line_others.add(CropAnimationLine(line_others.tail, lambda dt: 10 + math.sin(dt/4) * 70, assume_fps=TRACK_ASSUMED_FPS*2)) # speed up
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line_others.add(NoiseLine(line_others.tail, amplitude=0, t_factor=.3))
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# line_others.add(DashedLine(line_others.tail, t_factor=4, loop_offset=True))
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# line_others.get(DashedLine).skip = True
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line_others.add(FadedEndsLine(line_others.tail, 30, 30))
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line_others.add(FadeOutLine(line_others.tail))
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line_others.get(FadeOutLine).set_alpha(0)
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return line_others
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class DrawnScenario(Scenario):
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"""
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@ -288,16 +300,7 @@ class DrawnScenario(Scenario):
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self.line_prediction.add(FadeOutLine(self.line_prediction.tail))
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# when rendering tracks from others similar/close to the current one
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self.others_color = SrgbaColor(1,1,0,1)
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self.line_others = LineAnimationStack(StaticLine([], self.others_color))
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# self.line_others.add(SegmentLine(self.line_others.tail, duration=3, anim_f=partial(SegmentLine.anim_grow, in_and_out=True, max_len=5)))
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self.line_others.add(CropAnimationLine(self.line_others.tail, lambda dt: 10 + math.sin(dt/4) * 70, assume_fps=TRACK_ASSUMED_FPS*2)) # speed up
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self.line_others.add(NoiseLine(self.line_others.tail, amplitude=0, t_factor=.3))
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# self.line_others.add(DashedLine(self.line_others.tail, t_factor=4, loop_offset=True))
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# self.line_others.get(DashedLine).skip = True
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self.line_others.add(FadedEndsLine(self.line_others.tail, 30, 30))
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self.line_others.add(FadeOutLine(self.line_others.tail))
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self.line_others.get(FadeOutLine).set_alpha(0)
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self.line_others = build_line_others()
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self.tracks_to_self: Optional[Generator] = None
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self.tracks_to_self_pos = None
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@ -448,6 +451,27 @@ class DrawnScenario(Scenario):
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]), timings
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class NoTracksScenario():
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def __init__(self, stage: Stage):
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self.stage = stage
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self.line = build_line_others()
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def to_renderable_lines(self, dt: DeltaT):
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lines = RenderableLines([], CoordinateSpace.WORLD)
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if not self.line.is_running():
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track_id = random.choice(list(self.stage.history.state.tracks.keys()))
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# print('track_id', track_id)
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positions = self.stage.history.state.track_histories[track_id]
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self.line.root.points = positions
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self.line.start()
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lines.lines.append(
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self.line.as_renderable_line(dt)
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)
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# print(lines)
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return lines
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class DatasetDrawer():
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def __init__(self, stage: Stage):
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self.stage = stage
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@ -504,6 +528,8 @@ class Stage(Node):
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self.history = TrackHistory(self.config.tracker_output_dir, self.config.camera, self.config.cache_path)
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self.auxilary = DatasetDrawer(self)
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self.notrack_lines = [NoTracksScenario() for i in range(self.config.max_active_scenarios)]
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