Function infer_mv_pointclouds

eval_code/recons/interfaces/pi3.py:152–168

(filelist: str, model: Pi3, hydra_cfg: DictConfig, data_size: Tuple[int, int])

    return poses_c2w_all[0], None

def infer_mv_pointclouds(filelist: str, model: Pi3, hydra_cfg: DictConfig, data_size: Tuple[int, int]):

    imgs = load_and_resize14(filelist, new_width=hydra_cfg.load_img_size, device=hydra_cfg.device, verbose=hydra_cfg.verbose)

    dtype = torch.bfloat16 if torch.cuda.get_device_capability()[0] >= 8 else torch.float16

    with torch.no_grad():
        with torch.amp.autocast(hydra_cfg.device, dtype=dtype):
            pred = model(imgs)
    
    global_points = pred['points'][0]  # (N, h, w, 3)
    global_points = F.interpolate(
        global_points.permute(0, 3, 1, 2), data_size,
        mode="bilinear", align_corners=False, antialias=True
    ).permute(0, 2, 3, 1)  # align to gt

    return global_points.cpu().numpy()