Post review.

import pandas as pd

from autocnet.graph.network import CandidateGraph

FLANN_INDEX_KDTREE = 1

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

    Attributes

    ----------

    image_indices : dict

                    with key equal to the train image idx (returned by the DMatch object)

                    with key equal to the train image index (returned by the DMatch object),

                    e.g. an integer array index

                    and value equal to the image identifier, e.g. the name

    image_index_counter : int

        self_neighbor : bool

                        If the query descriptor is also a member

                        of the train descriptors, default True

                        of the KDTree avoid self neighbor, default True.

        Returns

        -------

        matched : dataframe

                  containing matched points

                  containing matched points with columns containg:

                  matched image name, query index, train index, and

                  descriptor distance

        """

        idx = 0

        if self_neighbor:

        # Check that self neighbors are being omitted

        distance = matched['distance']

        self.assertFalse(distance[distance == 0].any())

    def tearDown(self):

        pass