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- def point_clouds(flags, data):
- """
- Converts depth maps to point clouds and merges them all into one global point cloud.
- flags: command line arguments
- data: dict with keys ['intrinsics', 'poses']
- returns: [open3d.geometry.PointCloud]
- """
- pcs = []
- intrinsics = get_intrinsics(data['intrinsics'])
- pc = o3d.geometry.PointCloud()
- meshes = []
- rgb_path = os.path.join(flags.path, 'rgb.mp4')
- video = skvideo.io.vreader(rgb_path)
- for i, (T_WC, rgb) in enumerate(zip(data['poses'], video)):
- if i % flags.every != 0:
- continue
- print(f"Point cloud {i}", end="\r")
- T_CW = np.linalg.inv(T_WC)
- confidence = load_confidence(os.path.join(flags.path, 'confidence', f'{i:06}.png'))
- depth_path = data['depth_frames'][i]
- depth = load_depth(depth_path, confidence, filter_level=flags.confidence)
- rgb = Image.fromarray(rgb)
- rgb = rgb.resize((DEPTH_WIDTH, DEPTH_HEIGHT))
- rgb = np.array(rgb)
- rgbd = o3d.geometry.RGBDImage.create_from_color_and_depth(
- o3d.geometry.Image(rgb), depth,
- depth_scale=1.0, depth_trunc=MAX_DEPTH, convert_rgb_to_intensity=False)
- pc += o3d.geometry.PointCloud.create_from_rgbd_image(rgbd, intrinsics, extrinsic=T_CW)
- return [pc]
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