Commit da0e5e42 authored by jay's avatar jay
Browse files

Updates for a non-deterministic test for KP extraction

parent 864de6ab

autocnet/graph/edge.py

+9 −1
Original line number Diff line number Diff line
@@ -92,7 +92,7 @@ class Edge(dict, MutableMapping): 
        boolean_mask = v[1]

        self.masks[column_name] = boolean_mask"""



    def match(self, k=2, overlap=False, **kwargs):

    def match(self, k=2, **kwargs):



        """

        Given two sets of descriptors, utilize a FLANN (Approximate Nearest
@@ -113,6 +113,14 @@ class Edge(dict, MutableMapping): 
        """

        pass    



    def match_overlap(self, k=2, **kwargs):

        """

        Given two sets of descriptors, apply the matcher with the

        source and destination overlaps.

        """

        overlaps = [self['source_mbr'], self['destin_mbr']]

        self.match(k=k, overlap=overlaps, **kwargs)

        

    def decompose(self):

        """

        Apply coupled decomposition to the images and

autocnet/graph/tests/test_node.py

+1 −1
Original line number Diff line number Diff line
@@ -54,7 +54,7 @@ class TestNode(object): 
        node.extract_features_with_downsampling(5,

                                                extractor_parameters={'nfeatures':10})



        assert len(node.keypoints) == 10

        assert len(node.keypoints) in range(8,12)

        assert node.keypoints['x'].max() > 500

autocnet/matcher/cpu_matcher.py

+5 −6
Original line number Diff line number Diff line
@@ -8,7 +8,7 @@ FLANN_INDEX_KDTREE = 1 # Algorithm to set centers, 
DEFAULT_FLANN_PARAMETERS = dict(algorithm=FLANN_INDEX_KDTREE, trees=3)





def match(self, k=2, overlap=False, **kwargs):

def match(self, k=2, overlap=[], **kwargs):

    """

    Given two sets of descriptors, utilize a FLANN (Approximate Nearest

    Neighbor KDTree) matcher to find the k nearest matches.  Nearness is
@@ -85,8 +85,8 @@ def match(self, k=2, overlap=False, **kwargs): 
        kwargs.pop('aidx')

    elif overlap:

        # Query the source keypoints for those in the MBR

        source_mbr = self['source_mbr']

        query_result = self.source.keypoints.query()

        source_mbr = overlap[0]

        query_result = self.source.keypoints.query('x >= {} and x <= {} and y >= {} and y <= {}'.format(*source_mbr))

        aidx = query_result.index

    else:

        aidx = None
@@ -95,8 +95,8 @@ def match(self, k=2, overlap=False, **kwargs): 
        bidx = kwargs['bidx']

        kwargs.pop('bidx')

    elif overlap:

        destin_mbr = self['destin_mbr']

        query_result = self.destination.keypoints.query()

        destin_mbr = overlap[1]

        query_result = self.destination.keypoints.query('x >= {} and x <= {} and y >= {} and y <= {}'.format(*destin_mbr))

        bidx = query_result.index

    else:

        bidx = None
@@ -105,7 +105,6 @@ def match(self, k=2, overlap=False, **kwargs): 
    # Swap the indices since mono_matches is generic and source/destin are

    # swapped

    mono_matches(self.destination, self.source, aidx=bidx, bidx=aidx, **kwargs)



    self.matches.sort_values(by=['distance'])

autocnet/matcher/cuda_matcher.py

+5 −3
Original line number Diff line number Diff line
@@ -4,7 +4,7 @@ import cudasift as cs 
import numpy as np

import pandas as pd



def match(self, ratio=0.8, overlap=False, **kwargs):

def match(self, ratio=0.8, overlap=[], **kwargs):



    """

    Apply a composite CUDA matcher and ratio check.  If this method is used,
@@ -15,12 +15,14 @@ def match(self, ratio=0.8, overlap=False, **kwargs): 
    """



    if overlap:

        source_kps = self.source.keypoints.query('x >= {} and x <= {} and y >= {} and y <= {}'.format(*self['source_mbr']))

        source_overlap = overlap[0]

        source_kps = self.source.keypoints.query('x >= {} and x <= {} and y >= {} and y <= {}'.format(*source_overlap))

        idx = source_kps.index

        sremap = {k:v for k, v in enumerate(idx)}

        source_des = self.source.descriptors[idx]



        destin_kps = self.destination.keypoints.query('x >= {} and x <= {} and y >= {} and y <= {}'.format(*self['destin_mbr']))

        destin_overlap = overlap[1]

        destin_kps = self.destination.keypoints.query('x >= {} and x <= {} and y >= {} and y <= {}'.format(*destin_overlap))

        idx = destin_kps.index

        dremap = {k:v for k, v in enumerate(idx)}

        destin_des = self.destination.descriptors[idx]