Loading autocnet/graph/network.py +13 −1 Original line number Diff line number Diff line Loading @@ -8,7 +8,7 @@ import networkx as nx import numpy as np import pandas as pd from autocnet.control.control import C from autocnet.control.control import CorrespondenceNetwork from autocnet.fileio import io_hdf from autocnet.fileio import io_json from autocnet.fileio import io_utils Loading Loading @@ -445,6 +445,18 @@ class CandidateGraph(nx.Graph): filelist.append(node.image_path) return filelist def get_cnet(self, clean_keys=[]): cn = CorrespondenceNetwork() for s, d, edge in self.edges_iter(data=True): if clean_keys: matches, _ = edge._clean(clean_keys) else: matches = edge.matches cn.add_correspondences(edge, matches) return cn def to_cnet(self, clean_keys=[], isis_serials=False): """ Generate a control network (C) object from a graph Loading Loading
autocnet/graph/network.py +13 −1 Original line number Diff line number Diff line Loading @@ -8,7 +8,7 @@ import networkx as nx import numpy as np import pandas as pd from autocnet.control.control import C from autocnet.control.control import CorrespondenceNetwork from autocnet.fileio import io_hdf from autocnet.fileio import io_json from autocnet.fileio import io_utils Loading Loading @@ -445,6 +445,18 @@ class CandidateGraph(nx.Graph): filelist.append(node.image_path) return filelist def get_cnet(self, clean_keys=[]): cn = CorrespondenceNetwork() for s, d, edge in self.edges_iter(data=True): if clean_keys: matches, _ = edge._clean(clean_keys) else: matches = edge.matches cn.add_correspondences(edge, matches) return cn def to_cnet(self, clean_keys=[], isis_serials=False): """ Generate a control network (C) object from a graph Loading