def _save_features(feature_path, opensfm_config, filepath, points, descriptors, colors=None): io.mkdir_p(feature_path) features.save_features(filepath, points, descriptors, colors, opensfm_config)
def _save_features( self, filepath: str, points: np.ndarray, descriptors: np.ndarray, colors: Optional[np.ndarray] = None, segmentations: Optional[np.ndarray] = None, instances: Optional[np.ndarray] = None, ) -> None: io.mkdir_p(self._feature_path()) features.save_features( filepath, points, descriptors, colors, segmentations, instances, self.segmentation_labels(), self.config, )
def _save_features( self, filepath, points, descriptors, colors=None, segmentations=None, instances=None, ): io.mkdir_p(self._feature_path()) features.save_features( filepath, points, descriptors, colors, segmentations, instances, self.segmentation_labels(), self.config, )
def insert_features(feats, feats_file_path, config): """ Input: feats: Features to add to existing ORB features as a tuple (points, desc, color) feats_file_path: where the npz file is stored incl. npz file name config: SfM configuration info Output: saves a new npz file with extra features on it """ fts = features.load_features(feats_file_path, config) assert (feats[0].shape[1] == fts[0].shape[1] ) # make sure we have the same dimension assert (feats[1].shape[1] == fts[1].shape[1] ) # make sure we have the same dimension assert (feats[2].shape[1] == fts[2].shape[1] ) # make sure we have the same dimension new_feat_pts = np.vstack((fts[0], feats[0])) # append features together new_feat_desc = np.vstack((fts[1], feats[1])) new_feat_col = np.vstack((fts[2], feats[2])) features.save_features(feats_file_path, new_feat_pts, new_feat_desc, new_feat_col, config) # save features yeaaaaaah boi
def _save_features(self, filepath, points, descriptors, colors=None): io.mkdir_p(self._feature_path()) features.save_features(filepath, points, descriptors, colors, self.config)