(path, resolution=128, device="cpu")
| 19 | |
| 20 | |
| 21 | def load_voxgrid(path, resolution=128, device="cpu"): |
| 22 | voxgrid = np.load(path)["vox_grid"][:] |
| 23 | voxgrid = torch.from_numpy(voxgrid).bool().to(device) |
| 24 | if max(voxgrid.shape) != resolution: |
| 25 | new_shape = [int(x * resolution / max(voxgrid.shape)) for x in voxgrid.shape] |
| 26 | voxgrid = F.adaptive_max_pool3d(voxgrid[None, None].float(), new_shape)[0, 0].bool() |
| 27 | return voxgrid |
| 28 | |
| 29 | |
| 30 | def pairwise_IoU_dist(data_list: list): |
no outgoing calls
no test coverage detected