Commit 1b0f667d authored by kberry's avatar kberry
Browse files

Basic outline of subpixel_offset functionality

parent c820761a

autocnet/graph/network.py

+20 −0
Original line number Diff line number Diff line
@@ -14,6 +14,7 @@ from autocnet.fileio import io_json 
from autocnet.fileio.io_gdal import GeoDataset

from autocnet.matcher import feature_extractor as fe # extract features from image

from autocnet.matcher import outlier_detector as od

from autocnet.matcher import subpixel as sp



class CandidateGraph(nx.Graph):

    """
@@ -248,6 +249,25 @@ class CandidateGraph(nx.Graph): 
            attributes['homography'] = transformation_matrix

            attributes['ransac'] = mask



    # TODO: finish me!!!

    def compute_subpixel_offsets(self):

        for source, destination, attributes in self.edges_iter(data=True): #for each edge

            matches = attributes['matches'] #grab the matches

            src_image = self.node[source]['image']

            dest_image = self.node[destination]['image']

            tmp_lst = []

            for i, (idx, row) in enumerate(matches.iterrows()): #for each edge, calculate this for each keypoint pair

                s_idx = int(row['source_idx'])

                d_idx = int(row['destination_idx'])



                src_keypoint = self.node[source]['keypoints'][s_idx]

                dest_keypoint = self.node[destination]['keypoints'][d_idx]



                tmp_lst.append(sp.subpixel_offset(src_keypoint, dest_keypoint, src_image, dest_image))

            print(tmp_lst)

        return





    def to_cnet(self, clean_keys=[]):

        """

        Generate a control network (C) object from a graph

autocnet/graph/tests/test_network.py

+0 −1
Original line number Diff line number Diff line
@@ -41,7 +41,6 @@ class TestCandidateGraph(unittest.TestCase): 
        self.assertIsInstance(node['descriptors'][0], np.ndarray)

        self.assertEquals(self.graph.get_keypoints(node_number), node['keypoints'])





    def tearDown(self):

        try:

            os.remove('test_graph_to_json.json')

autocnet/matcher/subpixel.py

+24 −0
Original line number Diff line number Diff line 
import pandas as pd

from autocnet.matcher import matcher



# docs

# operates on one set of (src, dest) (kp, image)s

# error if passed in size is even. Don't do this....

# calculate an (x,y, strength) for each keypoint match in edge

# can we assume templates are square?

# look into the keypoint size and something with the descriptors to check physical area....



def subpixel_offset(template_kp, search_kp, template_img, search_img, template_size=9, search_size=27):

    # Get the x,y coordinates

    temp_x, temp_y = map(int, template_kp.pt)

    search_x, search_y = map(int, search_kp.pt)



    # Convert desired template and search sizes to offsets to get the bounding box

    t = int(template_size/2) #index offset for template

    s = int(search_size/2) #index offset for search



    template = template_img[temp_y-t:temp_y+t, temp_x-t:temp_x+t]

    search = search_img[search_y-s:search_y+s, search_x-s:search_x+s]



    # actually do the pattern match

    return matcher.pattern_match(template, search)

functional_tests/test_two_image.py

+2 −0
Original line number Diff line number Diff line
@@ -77,6 +77,8 @@ class TestTwoImageMatching(unittest.TestCase): 
            self.assertIn(len(matches.loc[mask]), range(75,101))



            cg.compute_homographies(clean_keys=['symmetry', 'ratio'])

            cg.compute_subpixel_offsets()





        # Step: And create a C object

        cnet = cg.to_cnet(clean_keys=['symmetry', 'ratio', 'ransac'])