servoing_designed_features_quad_panda3d_env.py 文件源码

def __init__(self, action_space, feature_type=None, filter_features=None,
                 max_time_steps=100, distance_threshold=4.0, **kwargs):
        """
        filter_features indicates whether to filter out key points that are not
        on the object in the current image. Key points in the target image are
        always filtered out.
        """
        SimpleQuadPanda3dEnv.__init__(self, action_space, **kwargs)
        ServoingEnv.__init__(self, env=self, max_time_steps=max_time_steps, distance_threshold=distance_threshold)

        lens = self.camera_node.node().getLens()
        self._observation_space.spaces['points'] = BoxSpace(np.array([-np.inf, lens.getNear(), -np.inf]),
                                                            np.array([np.inf, lens.getFar(), np.inf]))
        film_size = tuple(int(s) for s in lens.getFilmSize())
        self.mask_camera_sensor = Panda3dMaskCameraSensor(self.app, (self.skybox_node, self.city_node),
                                                          size=film_size,
                                                          near_far=(lens.getNear(), lens.getFar()),
                                                          hfov=lens.getFov())
        for cam in self.mask_camera_sensor.cam:
            cam.reparentTo(self.camera_sensor.cam)

        self.filter_features = True if filter_features is None else False
        self._feature_type = feature_type or 'sift'
        if cv2.__version__.split('.')[0] == '3':
            from cv2.xfeatures2d import SIFT_create, SURF_create
            from cv2 import ORB_create
            if self.feature_type == 'orb':
                # https://github.com/opencv/opencv/issues/6081
                cv2.ocl.setUseOpenCL(False)
        else:
            SIFT_create = cv2.SIFT
            SURF_create = cv2.SURF
            ORB_create = cv2.ORB
        if self.feature_type == 'sift':
            self._feature_extractor = SIFT_create()
        elif self.feature_type == 'surf':
            self._feature_extractor = SURF_create()
        elif self.feature_type == 'orb':
            self._feature_extractor = ORB_create()
        else:
            raise ValueError("Unknown feature extractor %s" % self.feature_type)
        if self.feature_type == 'orb':
            self._matcher = cv2.BFMatcher(cv2.NORM_HAMMING, crossCheck=True)
        else:
            self._matcher = cv2.BFMatcher(cv2.NORM_L2, crossCheck=True)
        self._target_key_points = None
        self._target_descriptors = None