Updates for review comments. Also swapped in template based from OpenCV. (d53a24a9) · Commits · aflab / astrogeology / Autocnet

autocnet/graph/network.py

+12 −8

Original line number	Diff line number	Diff line
		@@ -389,6 +389,10 @@ class CandidateGraph(nx.Graph):
		if clean_keys:
		matches, mask = edge._clean(clean_keys)

		subpixel = False
		if 'subpixel' in clean_keys:
		subpixel = True

		kp1 = self.node[source].keypoints
		kp2 = self.node[destination].keypoints
		pt_idx = 0
		@@ -400,19 +404,19 @@ class CandidateGraph(nx.Graph):
		m1 = (source, int(row['source_idx']))
		m2 = (destination, int(row['destination_idx']))

		values.append([kp1.iloc[m1_pid]['x'],
		kp1.iloc[m1_pid]['y'],
		values.append([kp1.loc[m1_pid]['x'],
		kp1.loc[m1_pid]['y'],
		m1,
		pt_idx,
		source,
		idx])

		kp2x = kp2.iloc[m2_pid]['x']
		kp2y = kp2.iloc[m2_pid]['y']

		if 'subpixel' in clean_keys:
		kp2x += row['x_offset']
		kp2y += row['y_offset']
		if subpixel:
		kp2x = kp2.loc[m2_pid]['x'] + row['x_offset']
		kp2y = kp2.loc[m2_pid]['y'] + row['y_offset']
		else:
		kp2x = kp2.loc[m2_pid]['x']
		kp2y = kp2.loc[m2_pid]['y']

		values.append([kp2x,
		kp2y,

autocnet/graph/tests/test_node.py

+0 −12

Original line number	Diff line number	Diff line
		@@ -39,18 +39,6 @@ class TestNode(unittest.TestCase):
		# Convex hull computation is checked lower in the hull computation
		self.assertRaises(AttributeError, self.node.coverage_ratio)

		def test_provenance(self):
		image = self.node.get_array()
		self.node.extract_features(image, extractor_parameters={'nfeatures':10})
		self.node.extract_features(image, extractor_parameters={'nfeatures':15})
		p0 = self.node.provenance[0]
		p1 = self.node.provenance[1]
		print(self.node.provenance)
		self.assertEqual(len(self.node.provenance.keys()), 2)
		self.assertNotEqual(find_in_dict(p0, 'nfeatures'),
		find_in_dict(p1, 'nfeatures'))


		def test_isis_serial(self):
		serial = self.node.isis_serial
		self.assertEqual(None, serial)

autocnet/matcher/matcher.py

+32 −24

Original line number	Diff line number	Diff line
		import warnings

		import cv2
		import pandas as pd

		@@ -10,8 +12,7 @@ DEFAULT_FLANN_PARAMETERS = dict(algorithm=FLANN_INDEX_KDTREE,
		trees=3)


		def pattern_match(template, image, upsampling=16,
		func=match_template):
		def pattern_match(template, image, upsampling=16,func=cv2.TM_CCOEFF_NORMED, error_check=False):
		"""
		Call an arbitrary pattern matcher

		@@ -29,6 +30,12 @@ def pattern_match(template, image, upsampling=16,

		func : object
		The function to be used to perform the template based matching
		Options: {cv2.TM_CCORR_NORMED, cv2.TM_CCOEFF_NORMED, cv2.TM_SQDIFF_NORMED}
		In testing the first two options perform significantly better with Apollo data.

		error_check : bool
		If True, also apply a different matcher and test that the values
		are not too divergent. Default, False.

		Returns
		-------
		@@ -42,34 +49,35 @@ def pattern_match(template, image, upsampling=16,
		strength : float
		The strength of the correlation in the range [-1, 1].
		"""
		if upsampling < 1:
		raise ValueError

		u_template = zoom(template, upsampling)
		u_image = zoom(image, upsampling, )
		# Find the the upper left origin of the template in the image
		match = func(u_image, u_template)
		y, x = np.unravel_index(np.argmax(match), match.shape)
		different = {cv2.TM_SQDIFF_NORMED: cv2.TM_CCOEFF_NORMED,
		cv2.TM_CCORR_NORMED: cv2.TM_SQDIFF_NORMED,
		cv2.TM_CCOEFF_NORMED: cv2.TM_SQDIFF_NORMED}

		# Resample the match back to the native image resolution
		x /= upsampling
		y /= upsampling
		if upsampling < 1:
		raise ValueError

		# Offset from the UL origin to the image center
		x += (template.shape[1] / 2)
		y += (template.shape[0] / 2)
		u_template = zoom(template, upsampling, order=1)
		u_image = zoom(image, upsampling, order=1)

		# Compute the offset to adjust the image match point location
		ideal_y = image.shape[0] / 2
		ideal_x = image.shape[1] / 2
		result = cv2.matchTemplate(u_image, u_template, method=func)
		min_corr, max_corr, min_loc, max_loc = cv2.minMaxLoc(result)
		if func == cv2.TM_SQDIFF or func == cv2.TM_SQDIFF_NORMED:
		x,y = (min_loc[0], min_loc[1])
		else:
		x, y = (max_loc[0], max_loc[1])

		x = ideal_x - x
		y = ideal_y - y
		# Compute the idealized shift (image center)
		ideal_y = u_image.shape[0] / 2
		ideal_x = u_image.shape[1] / 2

		# Find the maximum correlation
		strength = np.max(match)
		# Compute the shift from template upper left to template center
		y += (u_template.shape[0] / 2)
		x += (u_template.shape[1] / 2)

		return x, y, strength
		x = (ideal_x - x) / upsampling
		y = (ideal_y - y) / upsampling
		return x, y, max_corr


		class FlannMatcher(object):
		@@ -168,7 +176,7 @@ class FlannMatcher(object):
		i.queryIdx,
		i.distance))
		else:
		raise ValueError('Likely self neighbor in query!')
		warnings.warn('Likely self neighbor in query!')
		return pd.DataFrame(matched, columns=['source_image', 'source_idx',
		'destination_image', 'destination_idx',
		'distance'])

autocnet/matcher/outlier_detector.py

+9 −0

Original line number	Diff line number	Diff line
		@@ -31,6 +31,10 @@ class DistanceRatio(Observable):
		mask are assumed to have passed the ratio test. Else
		False.

		References
		----------
		[Lowe2004]_

		"""

		def __init__(self, matches):
		@@ -126,6 +130,11 @@ class SpatialSuppression(Observable):

		domain : tuple
		The (x,y) extent of the input domain

		References
		----------
		[Gauglitz2011]_

		"""

		def __init__(self, df, domain, min_radius=2, k=250, error_k=0.1):

autocnet/matcher/subpixel.py

+1 −1

Original line number	Diff line number	Diff line
		@@ -45,7 +45,7 @@ def clip_roi(img, center, img_size):
		x_start:x_start + x_stop + 1]
		else:
		clipped_img = img.read_array(pixels=[x_start, y_start,
		x_stop, y_stop])
		x_stop + 1, y_stop + 1])
		return clipped_img