Allow reconstruction step to allow images to be added

Author: Brook Roberts

bin/clean

@@ -15,3 +15,4 @@ mv -vf $1/navigation_graph.json $trash
 mv -vf $1/plot_inliers $trash
 mv -vf $1/depthmaps $trash
 mv -vf $1/tracks.csv $trash
+mv -vf $1/track_sets.pkl $trash

opensfm/dataset.py

@@ -329,18 +329,18 @@ def find_matches(self, im1, im2):
                     return im2_matches[im1][:, [1, 0]]
         return []
 
-    def __unionfind_file(self, filename=None):
+    def __track_sets_file(self, filename=None):
         """Return path of unionfind file"""
-        return os.path.join(self.data_path, filename or 'unionfind.pkl')
+        return os.path.join(self.data_path, filename or 'track_sets.pkl')
 
-    def load_unionfind_file(self, filename=None):
+    def load_track_sets_file(self, filename=None):
         """Return unionfind of tracks"""
-        with open(self.__unionfind_file(filename)) as fin:
-            return load_unionfind_file(fin)
+        with open(self.__track_sets_file(filename)) as fin:
+            return load_track_sets_file(fin)
 
-    def save_unionfind_file(self, unionfind, filename=None):
-        with open(self.__unionfind_file(filename), 'w') as fout:
-            save_unionfind_file(fout, unionfind)
+    def save_track_sets_file(self, unionfind, filename=None):
+        with open(self.__track_sets_file(filename), 'w') as fout:
+            save_track_sets_file(fout, unionfind)
 
     def __tracks_graph_file(self, filename=None):
         """Return path of tracks file"""
@@ -515,8 +515,8 @@ def save_tracks_graph(fileobj, graph):
                 fileobj.write('%s\t%s\t%d\t%g\t%g\t%g\t%g\t%g\n' % (
                     str(image), str(track), fid, x, y, r, g, b))
 
-def load_unionfind_file(fileobj):
+def load_track_sets_file(fileobj):
     return pickle.load(fileobj)
 
-def save_unionfind_file(fileobj, unionfind):
+def save_track_sets_file(fileobj, unionfind):
     pickle.dump(unionfind, fileobj, protocol=pickle.HIGHEST_PROTOCOL)

opensfm/matching.py

@@ -146,9 +146,11 @@ def create_tracks_graph(features, colors, matches, config, data):
     logger.debug('Merging features onto tracks')
 
     try:
-        uf = data.load_unionfind_file()
+        uf, track_ids, max_id = data.load_track_sets_file()
     except IOError:
         uf = UnionFind()
+        track_ids = {}
+        max_id = 0
 
     for im1, im2 in matches:
         for f1, f2 in matches[im1, im2]:
@@ -161,14 +163,17 @@ def create_tracks_graph(features, colors, matches, config, data):
             sets[p].append(i)
         else:
             sets[p] = [i]
+            if p not in track_ids:
+                track_ids[p] = max_id
+                max_id += 1
 
-    data.save_unionfind_file(uf)
-
-    tracks = [t for t in sets.values() if good_track(t, config.get('min_track_length', 2))]
+    track_sets = (uf, track_ids, max_id)
+    data.save_track_sets_file(track_sets)
+    tracks = [(track_ids[track_name], t) for track_name, t in sets.iteritems() if good_track(t, config.get('min_track_length', 2))]
     logger.debug('Good tracks: {}'.format(len(tracks)))
 
     tracks_graph = nx.Graph()
-    for track_id, track in enumerate(tracks):
+    for track_id, track in tracks:
         for image, featureid in track:
             if image not in features:
                 continue

opensfm/reconstruction.py

@@ -905,13 +905,32 @@ def incremental_reconstruction(data):
         data.invent_reference_lla()
 
     graph = data.load_tracks_graph()
+
+    try:
+        existing_reconstructions = data.load_reconstruction()
+        # we remove any points that were in the previous reconstruction but are no longer in our graph
+        for reconstruction in existing_reconstructions:
+            reconstruction.points = {k: point for k, point in reconstruction.points.iteritems() if k in graph}
+    except IOError:
+        existing_reconstructions = []
+
+    reconstructed_images = set(image for reconstruction in existing_reconstructions for image in reconstruction.shots.keys())
+
     tracks, images = matching.tracks_and_images(graph)
-    remaining_images = set(images)
+    remaining_images = set(images) - reconstructed_images
     gcp = None
     if data.ground_control_points_exist():
         gcp = data.load_ground_control_points()
-    common_tracks = matching.all_common_tracks(graph, tracks)
+
     reconstructions = []
+    for reconstruction in existing_reconstructions:
+        grow_reconstruction(data, graph, reconstruction, remaining_images, gcp)
+        reconstructions.append(reconstruction)
+        reconstructions = sorted(reconstructions,
+                                 key=lambda x: -len(x.shots))
+        data.save_reconstruction(reconstructions)
+
+    common_tracks = matching.all_common_tracks(graph, tracks)
     pairs = compute_image_pairs(common_tracks, data.config)
     for im1, im2 in pairs:
         if im1 in remaining_images and im2 in remaining_images: