Function process_human_model_output

ADHMR/lib/utils/preprocessing.py:244–514

(human_model_param, cam_param, do_flip, img_shape, img2bb_trans, rot, human_model_type, joint_img=None)

def process_human_model_output(human_model_param, cam_param, do_flip, img_shape, img2bb_trans, rot, human_model_type, joint_img=None):
    if human_model_type == 'smplx':
        human_model = smpl_x
        rotation_valid = np.ones((smpl_x.orig_joint_num), dtype=np.float32)
        coord_valid = np.ones((smpl_x.joint_num), dtype=np.float32)

        root_pose, body_pose, shape, trans = human_model_param['root_pose'], human_model_param['body_pose'], \
                                             human_model_param['shape'], human_model_param['trans']
        if body_pose is None:
            body_valid = False
        elif (np.array(body_pose) == 0).all():
            body_valid = False
        else:
            body_valid = True
            
        if not body_valid:
            rotation_valid[smpl_x.orig_joint_part['body']] = 0
            coord_valid[smpl_x.joint_part['body']] = 0
            
        if 'lhand_pose' in human_model_param and human_model_param['lhand_valid']:
            lhand_pose = human_model_param['lhand_pose']
        else:
            lhand_pose = np.zeros((3 * len(smpl_x.orig_joint_part['lhand'])), dtype=np.float32)
            rotation_valid[smpl_x.orig_joint_part['lhand']] = 0
            coord_valid[smpl_x.joint_part['lhand']] = 0
        if 'rhand_pose' in human_model_param and human_model_param['rhand_valid']:
            rhand_pose = human_model_param['rhand_pose']
        else:
            rhand_pose = np.zeros((3 * len(smpl_x.orig_joint_part['rhand'])), dtype=np.float32)
            rotation_valid[smpl_x.orig_joint_part['rhand']] = 0
            coord_valid[smpl_x.joint_part['rhand']] = 0
        if 'jaw_pose' in human_model_param and 'expr' in human_model_param and human_model_param['face_valid']:
            jaw_pose = human_model_param['jaw_pose']
            expr = human_model_param['expr']
            expr_valid = True
        else:
            jaw_pose = np.zeros((3), dtype=np.float32)
            expr = np.zeros((smpl_x.expr_code_dim), dtype=np.float32)
            rotation_valid[smpl_x.orig_joint_part['face']] = 0
            coord_valid[smpl_x.joint_part['face']] = 0
            expr_valid = False
        if 'gender' in human_model_param:
            gender = human_model_param['gender']
        else:
            gender = 'neutral'
        root_pose = torch.FloatTensor(root_pose).view(1, 3)  # (1,3)
        body_pose = torch.FloatTensor(body_pose).view(-1, 3)  # (21,3)
        lhand_pose = torch.FloatTensor(lhand_pose).view(-1, 3)  # (15,3)
        rhand_pose = torch.FloatTensor(rhand_pose).view(-1, 3)  # (15,3)
        jaw_pose = torch.FloatTensor(jaw_pose).view(-1, 3)  # (1,3)
        shape = torch.FloatTensor(shape).view(1, -1)  # SMPLX shape parameter
        expr = torch.FloatTensor(expr).view(1, -1)  # SMPLX expression parameter
        trans = torch.FloatTensor(trans).view(1, -1)  # translation vector

        # apply camera extrinsic (rotation)
        # merge root pose and camera rotation
        if 'R' in cam_param:
            R = np.array(cam_param['R'], dtype=np.float32).reshape(3, 3)