Commit 07985aae authored by kberry's avatar kberry
Browse files

Removed unnecessary comments

parent e5ba13f4

autocnet/graph/network.py

+2 −2
Original line number Diff line number Diff line
@@ -51,7 +51,7 @@ class CandidateGraph(nx.Graph): 
            adjacency_dict[n] = self.neighbors(n)

        io_json.write_json(adjacency_dict, outputfile)



    def add_matches(self, source_node, matches): #src node = query node; destination node = train node

    def add_matches(self, source_node, matches):

        """



        Adds match data to a node and attributes the data to the
@@ -79,7 +79,7 @@ class CandidateGraph(nx.Graph): 


            if 'matches' in edge.keys():

                df = edge['matches']

                edge['matches'] = pd.merge(df, matches, left_on='queryIdx', right_on='trainIdx') #how do we know it does the right thing?

                edge['matches'] = pd.merge(df, matches, left_on='queryIdx', right_on='trainIdx')

            else:

                edge['matches'] = matches

autocnet/matcher/matcher.py

+1 −4
Original line number Diff line number Diff line
@@ -8,7 +8,6 @@ FLANN_INDEX_KDTREE = 1 # Algorithm to set centers, 
DEFAULT_FLANN_PARAMETERS = dict(algorithm=FLANN_INDEX_KDTREE,

                                trees=3)





class FlannMatcher(object):

    """

    A wrapper to the OpenCV Flann based matcher class that adds
@@ -55,7 +54,6 @@ class FlannMatcher(object): 
        """

        self._flann_matcher.train()



    #consider changing this back to returning (matches, data_frame)

    def query(self, descriptor, k=3, self_neighbor=True):

        """
@@ -89,9 +87,8 @@ class FlannMatcher(object): 
                                i.queryIdx,

                                i.trainIdx,

                                i.distance))

        data_frame = pd.DataFrame(matched, columns=['matched_to', 'queryIdx',

        return pd.DataFrame(matched, columns=['matched_to', 'queryIdx',data_frame

                                              'trainIdx', 'distance'])

        return data_frame



#don't throw anything out, just have dataframes and masks

#TODO: decide on a consistent mask format to output. Do we want to also accept existing masks and just mask more things?