Updates for code comments.

import numpy as np

import pandas as pd

import cv2

             (4, n) projection matrix

    """

    if isinstance(pt, pd.DataFrame):

        pt = pt.values

    if isinstance(pt1, pd.DataFrame):

        pt1 = pt.values

    pt = np.asarray(pt)

    pt1 = np.asarray(pt1)

    # Transpose for the openCV call if needed

    if pt.shape[0] != 3:

        # Set the initial state of the fundamental mask in the masks

        self.masks = ('fundamental', mask)

    def add_putative_matches(self):

        if not hasattr(self, 'fundamental_matrix'):

            raise(ValueError, 'Fundamental matric has not been computed')

        F = self.fundamental_matrix

    def compute_homography(self, method='ransac', clean_keys=[], pid=None, **kwargs):

        """

        For each edge in the (sub) graph, compute the homography

                                d_keypoints.values)

        # Convert the truncated RANSAC mask back into a full length mask

        mask[mask] = self.homography.mask.ravel()

        mask[mask] = self.homography.mask

        self.masks = ('ransac', mask)

        # Finalize the array to get custom attrs to propagate