Function process_pose_file

wan/data/utils.py:279–316

Modified from https://github.com/hehao13/CameraCtrl/blob/main/inference.py

(pose_file_path, width=672, height=384, original_pose_width=1280, original_pose_height=720, device='cpu', return_poses=False)

    return plucker

def process_pose_file(pose_file_path, width=672, height=384, original_pose_width=1280, original_pose_height=720, device='cpu', return_poses=False):
    """Modified from https://github.com/hehao13/CameraCtrl/blob/main/inference.py
    """
    with open(pose_file_path, 'r') as f:
        poses = f.readlines()

    poses = [pose.strip().split(' ') for pose in poses[1:]]
    cam_params = [[float(x) for x in pose] for pose in poses]
    if return_poses:
        return cam_params
    else:
        cam_params = [Camera(cam_param) for cam_param in cam_params]

        sample_wh_ratio = width / height
        pose_wh_ratio = original_pose_width / original_pose_height  # Assuming placeholder ratios, change as needed

        if pose_wh_ratio > sample_wh_ratio:
            resized_ori_w = height * pose_wh_ratio
            for cam_param in cam_params:
                cam_param.fx = resized_ori_w * cam_param.fx / width
        else:
            resized_ori_h = width / pose_wh_ratio
            for cam_param in cam_params:
                cam_param.fy = resized_ori_h * cam_param.fy / height

        intrinsic = np.asarray([[cam_param.fx * width,
                                cam_param.fy * height,
                                cam_param.cx * width,
                                cam_param.cy * height]
                                for cam_param in cam_params], dtype=np.float32)

        K = torch.as_tensor(intrinsic)[None]  # [1, 1, 4]
        c2ws = get_relative_pose(cam_params)  # Assuming this function is defined elsewhere
        c2ws = torch.as_tensor(c2ws)[None]  # [1, n_frame, 4, 4]
        plucker_embedding = ray_condition(K, c2ws, height, width, device=device)[0].permute(0, 3, 1, 2).contiguous()  # V, 6, H, W
        plucker_embedding = plucker_embedding[None]
        plucker_embedding = rearrange(plucker_embedding, "b f c h w -> b f h w c")[0]
        return plucker_embedding

def process_pose_params(cam_params, width=672, height=384, original_pose_width=1280, original_pose_height=720, device='cpu'):
    """Modified from https://github.com/hehao13/CameraCtrl/blob/main/inference.py