Commit 2ddbd73e authored by Evin Dunn's avatar Evin Dunn
Browse files

Added overlap param to Edge.get_keypoints()

parent a0e50317

autocnet/graph/edge.py

+16 −4
Original line number Diff line number Diff line
@@ -201,18 +201,30 @@ class Edge(dict, MutableMapping): 
            self.masks[maskname] = mask



    @utils.methodispatch

    def get_keypoints(self, node, index=None, homogeneous=False):

    def get_keypoints(self, node, index=None, homogeneous=False, overlap=False):

        if not hasattr(index, '__iter__') and index is not None:

            raise TypeError

        return node.get_keypoint_coordinates(index=index, homogeneous=homogeneous)

        keypts = node.get_keypoint_coordinates(index=index, homogeneous=homogeneous)

        # If we only want keypoints in the overlap

        if overlap:

            # Compute overlap if we don't have it

            if not self["source_mbr"] or self["destin_mbr"]:

                self.compute_overlap()

            # Create overlap's bounding polygon in pixel space

            bounds_poly = node.reproject_geom(self.overlap_latlon_coords)

            # Mask for node keypts based on bounding poly

            overlap_mask = cg.geom_mask(node.keypoints, bounds_poly)

            # Return masked keypts

            return keypts[overlap_mask]

        return keypts



    @get_keypoints.register(str)

    def _(self, node, index=None, homogeneous=False):

    def _(self, node, index=None, homogeneous=False, overlap=False):

        if not hasattr(index, '__iter__') and index is not None:

            raise TypeError

        node = node.lower()

        node = getattr(self, node)

        return node.get_keypoint_coordinates(index=index, homogeneous=homogeneous)

        return self.get_keypoints(node, index=index, homogeneous=homogeneous, overlap=overlap)



    def compute_fundamental_error(self, clean_keys=[]):

        """

autocnet/matcher/cpu_decompose.py

+3 −2
Original line number Diff line number Diff line
@@ -67,8 +67,9 @@ def decompose_and_match(self, k=2, maxiteration=3, size=18, buf_dist=3,**kwargs) 
    dsize = ddata.shape



    # Grab all the available candidate keypoints

    skp = self.source.get_keypoints()

    dkp = self.destination.get_keypoints()

    overlap = kwargs.get("overlap", False)

    skp = self.get_keypoints(self.source, overlap=overlap)

    dkp = self.get_keypoints(self.destination, overlap=overlap)



    # Set up the membership arrays

    self.smembership = np.zeros(sdata.shape, dtype=np.int16)