Merge pull request #52 from jlaura/master (261a67fe) · Commits · aflab / astrogeology / Autocnet

autocnet/examples/Apollo15/adjacency.json

+24 −24

Original line number	Diff line number	Diff line
		{"autocnet/examples/Apollo15/AS15-M-0297_SML.png"
		: ["autocnet/examples/Apollo15/AS15-M-0298_SML.png",
		"autocnet/examples/Apollo15/AS15-M-0300_SML.png",
		"autocnet/examples/Apollo15/AS15-M-0299_SML.png",
		"autocnet/examples/Apollo15/AS15-M-0296_SML.png"],
		"autocnet/examples/Apollo15/AS15-M-0300_SML.png"
		: ["autocnet/examples/Apollo15/AS15-M-0298_SML.png",
		"autocnet/examples/Apollo15/AS15-M-0297_SML.png",
		"autocnet/examples/Apollo15/AS15-M-0299_SML.png"],
		"autocnet/examples/Apollo15/AS15-M-0299_SML.png"
		: ["autocnet/examples/Apollo15/AS15-M-0298_SML.png",
		"autocnet/examples/Apollo15/AS15-M-0297_SML.png",
		"autocnet/examples/Apollo15/AS15-M-0300_SML.png",
		"autocnet/examples/Apollo15/AS15-M-0296_SML.png"],
		"autocnet/examples/Apollo15/AS15-M-0295_SML.png"
		{"AS15-M-0297_SML.png"
		: ["AS15-M-0298_SML.png",
		"AS15-M-0300_SML.png",
		"AS15-M-0299_SML.png",
		"AS15-M-0296_SML.png"],
		"AS15-M-0300_SML.png"
		: ["AS15-M-0298_SML.png",
		"AS15-M-0297_SML.png",
		"AS15-M-0299_SML.png"],
		"AS15-M-0299_SML.png"
		: ["AS15-M-0298_SML.png",
		"AS15-M-0297_SML.png",
		"AS15-M-0300_SML.png",
		"AS15-M-0296_SML.png"],
		"AS15-M-0295_SML.png"
		: [],
		"autocnet/examples/Apollo15/AS15-M-0296_SML.png"
		: ["autocnet/examples/Apollo15/AS15-M-0298_SML.png",
		"autocnet/examples/Apollo15/AS15-M-0297_SML.png",
		"autocnet/examples/Apollo15/AS15-M-0299_SML.png"],
		"autocnet/examples/Apollo15/AS15-M-0298_SML.png"
		: ["autocnet/examples/Apollo15/AS15-M-0297_SML.png",
		"autocnet/examples/Apollo15/AS15-M-0300_SML.png",
		"autocnet/examples/Apollo15/AS15-M-0299_SML.png",
		"autocnet/examples/Apollo15/AS15-M-0296_SML.png"]}
		"AS15-M-0296_SML.png"
		: ["AS15-M-0298_SML.png",
		"AS15-M-0297_SML.png",
		"AS15-M-0299_SML.png"],
		"AS15-M-0298_SML.png"
		: ["AS15-M-0297_SML.png",
		"AS15-M-0300_SML.png",
		"AS15-M-0299_SML.png",
		"AS15-M-0296_SML.png"]}

autocnet/graph/edge.py

+43 −33

Original line number	Diff line number	Diff line
		from collections import MutableMapping
		import warnings
		from collections import MutableMapping

		import numpy as np
		import pandas as pd
		from pysal.cg.shapes import Polygon

		from autocnet.matcher import subpixel as sp
		from autocnet.matcher.homography import Homography
		from autocnet.cg.cg import convex_hull_ratio
		from autocnet.cg.cg import overlapping_polygon_area
		from autocnet.vis.graph_view import plot_edge
		from autocnet.matcher import health
		from autocnet.matcher import outlier_detector as od
		from autocnet.cg.cg import convex_hull_ratio
		from autocnet.matcher import subpixel as sp
		from autocnet.transformation.transformations import FundamentalMatrix, Homography
		from autocnet.vis.graph_view import plot_edge


		class Edge(dict, MutableMapping):
		@@ -35,10 +36,14 @@ class Edge(dict, MutableMapping):
		self.source = source
		self.destination = destination

		self._homography = None
		self.homography = None
		self.fundamental_matrix = None
		self._subpixel_offsets = None
		self.provenance = {}
		self._pid = 0

		self._observers = set()

		#Subscribe the heatlh observer
		self._health = health.EdgeHealth()

		def __repr__(self):
		return """
		@@ -49,34 +54,29 @@ class Edge(dict, MutableMapping):

		@property
		def masks(self):
		mask_lookup = {'fundamental': 'fundamental_matrix'}
		if not hasattr(self, '_masks'):
		self._masks = pd.Panel({self._pid: pd.DataFrame(index=self.matches.index)})
		if hasattr(self, 'matches'):
		self._masks = pd.DataFrame(True, columns=['symmetry', 'ratio'],
		index=self.matches.index)
		else:
		self._masks = pd.DataFrame()
		# If the mask is coming form another object that tracks
		# state, dynamically draw the mask from the object.
		for c in self._masks.columns:
		if c in mask_lookup:
		self._masks[c] = getattr(self, mask_lookup[c]).mask
		return self._masks

		@masks.setter
		def masks(self, v):
		column_name = v[0]
		boolean_mask = v[1]
		current = self.masks[self._pid]
		current[column_name] = boolean_mask

		@property
		def error(self):
		if not hasattr(self, '_error'):
		self._error = pd.Panel({self._pid: pd.DataFrame(index=self.matches.index)})
		return self._error

		@error.setter
		def error(self, v):
		pass
		self.masks[column_name] = boolean_mask

		@property
		def homography(self):
		return self._homography

		@homography.setter
		def homography(self, v):
		self._homography = v
		def health(self):
		return self._health.health

		def keypoints(self, clean_keys=[]):
		"""
		@@ -124,6 +124,9 @@ class Edge(dict, MutableMapping):
		else:
		raise AttributeError('Matches have not been computed for this edge')

		all_source_keypoints = self.source.keypoints.iloc[matches['source_idx']]
		all_destin_keypoints = self.destination.keypoints.iloc[matches['destination_idx']]

		if clean_keys:
		matches, mask = self._clean(clean_keys)

		@@ -140,8 +143,17 @@ class Edge(dict, MutableMapping):
		mask[mask == True] = fundam_mask
		else:
		mask = fundam_mask
		self.fundamental_matrix = FundamentalMatrix(transformation_matrix,
		all_source_keypoints[['x', 'y']],
		all_destin_keypoints[['x', 'y']],
		mask=mask)

		# Subscribe the health watcher to the fundamental matrix observable
		self.fundamental_matrix.subscribe(self._health.update)
		self.fundamental_matrix._notify_subscribers(self.fundamental_matrix)

		# Set the initial state of the fundamental mask in the masks
		self.masks = ('fundamental', mask)
		self.fundamental_matrix = transformation_matrix

		def compute_homography(self, method='ransac', clean_keys=[], pid=None, **kwargs):
		"""
		@@ -188,7 +200,7 @@ class Edge(dict, MutableMapping):
		self.homography = Homography(transformation_matrix,
		s_keypoints[ransac_mask][['x', 'y']],
		d_keypoints[ransac_mask][['x', 'y']],
		index=mask[mask == True].index)
		mask=mask[mask == True].index)

		# Finalize the array to get custom attrs to propagate
		self.homography.__array_finalize__(self.homography)
		@@ -362,9 +374,7 @@ class Edge(dict, MutableMapping):
		mask : series
		A boolean series to inflate back to the full match set
		"""
		if not pid:
		pid = self._pid
		panel = self.masks[pid]
		panel = self.masks
		mask = panel[clean_keys].all(axis=1)
		matches = self.matches[mask]
		return matches, mask

autocnet/graph/network.py

+8 −6

Original line number	Diff line number	Diff line
		@@ -175,7 +175,6 @@ class CandidateGraph(nx.Graph):

		raise NotImplementedError
		self.add_node(self.node_counter, args, *kwargs)
		#self.node_labels[self.node[self.node_counter]['image_name']] = self.node_counter
		self.node_counter += 1

		def extract_features(self, method='orb', extractor_parameters={}):
		@@ -225,7 +224,7 @@ class CandidateGraph(nx.Graph):
		def add_matches(self, matches):
		"""
		Adds match data to a node and attributes the data to the
		appropriate edges, e.g. if A-B have a match, edge A-B is attributes
		appropriate edges, e.g. if A-B have a match, edge A-B is attributed
		with the pandas dataframe.

		Parameters
		@@ -233,13 +232,16 @@ class CandidateGraph(nx.Graph):
		matches : dataframe
		The pandas dataframe containing the matches
		"""
		edges = self.edges()
		source_groups = matches.groupby('source_image')
		for i, source_group in source_groups:
		for j, dest_group in source_group.groupby('destination_image'):
		source_key = dest_group['source_image'].values[0]
		destination_key = dest_group['destination_image'].values[0]

		if (source_key, destination_key) in edges:
		edge = self.edge[source_key][destination_key]
		else:
		edge = self.edge[destination_key][source_key]

		if hasattr(edge, 'matches'):
		df = edge.matches

autocnet/graph/tests/test_network.py

+12 −6

Original line number	Diff line number	Diff line
		@@ -15,7 +15,10 @@ class TestCandidateGraph(unittest.TestCase):

		@classmethod
		def setUpClass(cls):
		cls.graph = network.CandidateGraph.from_adjacency(get_path('adjacency.json'))
		basepath = get_path('Apollo15')
		cls.graph = network.CandidateGraph.from_adjacency(get_path('three_image_adjacency.json'),
		basepath=basepath)
		cls.disconnected_graph = network.CandidateGraph.from_adjacency(get_path('adjacency.json'))

		def test_get_name(self):
		node_number = self.graph.node_name_map['AS15-M-0297_SML.png']
		@@ -35,18 +38,21 @@ class TestCandidateGraph(unittest.TestCase):
		pass

		def test_island_nodes(self):
		self.assertEqual(len(self.graph.island_nodes()), 1)
		self.assertEqual(len(self.disconnected_graph.island_nodes()), 1)

		def test_connected_subgraphs(self):
		subgraph_list = self.graph.connected_subgraphs()
		subgraph_list = self.disconnected_graph.connected_subgraphs()
		self.assertEqual(len(subgraph_list), 2)
		island = self.graph.island_nodes()[0]
		self.assertTrue(island in subgraph_list[1])
		islands = self.disconnected_graph.island_nodes()
		self.assertTrue(islands[0] in subgraph_list[1])

		subgraph_list = self.graph.connected_subgraphs()
		self.assertEqual(len(subgraph_list), 1)


		def test_save_load(self):
		self.graph.save('test_save.cg')
		loaded = self.graph.from_graph('test_save.cg')

		self.assertEqual(self.graph.node[0].nkeypoints, loaded.node[0].nkeypoints)
		self.assertEqual(self.graph.edge[0][1], loaded.edge[0][1])

autocnet/matcher/health.py

0 → 100644

+29 −0

Original line number	Diff line number	Diff line


		class EdgeHealth(object):
		"""
		Storage and computation of the health of a graph edge using the metric:


		"""
		def __init__(self):
		self.FundamentalMatrix = 0.0

		@property
		def health(self):
		return self.recompute_health()

		def update(self, args, *kwargs):
		"""
		Pass through called when the observable (model) changes.
		args and *kwargs are passed through from the observable.
		"""
		for a in args:
		if hasattr(self, a.__class__.__name__):
		setattr(self, a.__class__.__name__, a)

		def recompute_health(self):
		"""
		Recompute the health of the edge.
		"""
		return self.FundamentalMatrix.error.mean()