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)
