Merging upstream/dev (a4402eb3) · Commits · aflab / astrogeology / Autocnet

autocnet/matcher/ciratefi.py

0 → 100644

+731 −0

File added.

Preview size limit exceeded, changes collapsed.

autocnet/matcher/matcher.py

+5 −0

Original line number	Diff line number	Diff line
		@@ -2,9 +2,13 @@ import warnings

		import cv2
		import pandas as pd
		import numpy as np
		import math

		from scipy.misc import imresize
		from scipy.ndimage.interpolation import zoom


		FLANN_INDEX_KDTREE = 1 # Algorithm to set centers,
		DEFAULT_FLANN_PARAMETERS = dict(algorithm=FLANN_INDEX_KDTREE,
		trees=3)
		@@ -178,3 +182,4 @@ class FlannMatcher(object):
		return pd.DataFrame(matched, columns=['source_image', 'source_idx',
		'destination_image', 'destination_idx',
		'distance'])

autocnet/matcher/tests/test_ciratefi.py

0 → 100644

+165 −0

Original line number	Diff line number	Diff line
		import math
		import unittest
		import warnings

		import numpy as np
		from scipy.misc import imread
		from scipy.misc import imresize
		from scipy.ndimage.interpolation import rotate

		from autocnet.examples import get_path
		from autocnet.matcher import subpixel as sp
		from .. import ciratefi


		class TestCiratefi(unittest.TestCase):

		@classmethod
		def setUpClass(cls):
		img = imread(get_path('AS15-M-0298_SML.png'), flatten=True)
		img_coord = (482.09783936, 652.40679932)

		cls.template = sp.clip_roi(img, img_coord, 5)
		cls.template = rotate(cls.template, 90)
		cls.template = imresize(cls.template, 1.)

		cls.search = sp.clip_roi(img, img_coord, 21)
		cls.search = rotate(cls.search, 0)
		cls.search = imresize(cls.search, 1.)

		cls.offset = (1, 1)

		cls.offset_template = sp.clip_roi(img, np.add(img_coord, cls.offset), 5)
		cls.offset_template = rotate(cls.offset_template, 0)
		cls.offset_template = imresize(cls.offset_template, 1.)

		cls.search_center = [math.floor(cls.search.shape[0]/2),
		math.floor(cls.search.shape[1]/2)]

		cls.upsampling = 10
		cls.alpha = math.pi/2
		cls.cifi_thresh = 90
		cls.rafi_thresh = 90
		cls.tefi_thresh = 100
		cls.use_percentile = True
		cls.radii = list(range(1, 3))

		cls.cifi_number_of_warnings = 2
		cls.rafi_number_of_warnings = 2

		def test_cifi(self):
		# check all warnings
		with warnings.catch_warnings(record=True) as w:
		warnings.simplefilter("always")
		ciratefi.cifi(self.template, self.search, 1.0, radii=[100], use_percentile=False)
		self.assertEqual(len(w), self.cifi_number_of_warnings)

		# Threshold out of bounds error
		self.assertRaises(ValueError, ciratefi.cifi, self.template, self.search, -1.1, use_percentile=False)
		# radii list empty/none error
		self.assertRaises(ValueError, ciratefi.cifi, self.template, self.search, 90, radii=None)
		# scales list empty/none error
		self.assertRaises(ValueError, ciratefi.cifi, self.template, self.search, 90, scales=None)
		# template is bigger than search error
		self.assertRaises(ValueError, ciratefi.cifi, self.search, self.template, -1.1, use_percentile=False)

		with warnings.catch_warnings(record=True) as w:
		warnings.simplefilter("always")
		pixels, scales = ciratefi.cifi(self.template, self.search, thresh=self.cifi_thresh,
		radii=self.radii, use_percentile=True)

		self.assertEqual(len(w), 0)

		self.assertEqual(self.search.shape, scales.shape)
		self.assertIn((np.floor(self.search.shape[0]/2), np.floor(self.search.shape[1]/2)), pixels)
		self.assertTrue(pixels.size in range(0, self.search.size))

		def test_rafi(self):
		rafi_pixels = [(10, 10)]

		rafi_scales = np.ones(self.search.shape, dtype=float)

		# check all warnings
		with warnings.catch_warnings(record=True) as w:
		warnings.simplefilter("always")
		ciratefi.rafi(self.template, self.search, rafi_pixels,
		rafi_scales, thresh=1, radii=[100],
		use_percentile=False)

		self.assertEqual(len(w), self.rafi_number_of_warnings)

		# Threshold out of bounds error
		self.assertRaises(ValueError, ciratefi.rafi, self.template, self.search, rafi_pixels, rafi_scales,
		-1.1, use_percentile=False)

		# Radii list is empty.None error
		self.assertRaises(ValueError, ciratefi.rafi, self.search, self.template, rafi_pixels, -1.1, radii=None)
		# candidate pixel list empty/none error
		self.assertRaises(ValueError, ciratefi.rafi, self.template, self.search, [], rafi_scales)
		# scales list empty/none error
		self.assertRaises(ValueError, ciratefi.rafi, self.template, self.search, rafi_pixels, None)
		# template is bigger than search error
		self.assertRaises(ValueError, ciratefi.rafi, self.search, self.template, rafi_pixels, rafi_scales)
		# best scale nd array is not equal image shape
		self.assertRaises(ValueError, ciratefi.rafi, self.template, self.search, rafi_pixels, rafi_scales[:10])

		with warnings.catch_warnings(record=True) as w:
		pixels, scales = ciratefi.rafi(self.template, self.search, rafi_pixels, rafi_scales,
		thresh=self.rafi_thresh, radii=self.radii, use_percentile=True,
		alpha=self.alpha)
		self.assertEqual(len(w), 0)

		self.assertIn((np.floor(self.search.shape[0]/2), np.floor(self.search.shape[1]/2)), pixels)
		self.assertTrue(pixels.size in range(0, self.search.size))

		def test_tefi(self):
		tefi_pixels = [(10, 10)]
		tefi_scales = np.ones(self.search.shape, dtype=float)
		tefi_angles = [3.14159265]

		# Threshold out of bounds error
		self.assertRaises(ValueError, ciratefi.tefi, self.template, self.search, tefi_pixels, tefi_scales,
		tefi_angles, thresh=-1.1, use_percentile=False, alpha=self.alpha)

		# angle list is empty/None error
		self.assertRaises(ValueError, ciratefi.tefi, self.search, self.template, tefi_pixels, tefi_scales, None)
		# candidate pixel list empty/none error
		self.assertRaises(ValueError, ciratefi.tefi, self.template, self.search, None, tefi_scales, tefi_angles)
		# scales list empty/none error
		self.assertRaises(ValueError, ciratefi.tefi, self.template, self.search, tefi_pixels, None, tefi_angles)
		# template is bigger than search error
		self.assertRaises(ValueError, ciratefi.tefi, self.search, self.template, tefi_pixels, tefi_scales, -1.1)
		# best scale nd array is smaller than number of candidate pixels
		self.assertRaises(ValueError, ciratefi.tefi, self.template, self.search, tefi_pixels, tefi_scales[:10], -1.1)

		with warnings.catch_warnings(record=True) as w:
		warnings.simplefilter("always")
		pixel = ciratefi.tefi(self.template, self.search, tefi_pixels, tefi_scales, tefi_angles,
		thresh=self.tefi_thresh, use_percentile=True, alpha=self.alpha,
		upsampling=self.upsampling)

		for warn in w:
		print(warn)

		self.assertEqual(len(w), 0)
		self.assertIn((np.floor(self.search.shape[0]/2), np.floor(self.search.shape[1]/2)), pixel)
		self.assertTrue(pixel[0][0] == self.search_center[0] and pixel[0][1] == self.search_center[1])

		def test_ciratefi(self):
		results = ciratefi.ciratefi(self.template, self.search, upsampling=10, cifi_thresh=self.cifi_thresh,
		rafi_thresh=self.rafi_thresh, tefi_thresh=self.tefi_thresh,
		use_percentile=self.use_percentile, alpha=self.alpha, radii=self.radii)

		self.assertEqual(len(results), 1)
		self.assertTrue(np.equal(results[0], self.search_center).all())

		results = ciratefi.ciratefi(self.offset_template, self.search, upsampling=self.upsampling,
		cifi_thresh=self.cifi_thresh, rafi_thresh=self.rafi_thresh,
		tefi_thresh=self.tefi_thresh,
		use_percentile=self.use_percentile, alpha=self.alpha, radii=self.radii)

		print(results)
		self.assertTrue(np.equal(results[0], np.add(self.search_center, list(self.offset))).all())

		def tearDown(self):
		pass

autocnet/utils/utils.py

+35 −0

Original line number	Diff line number	Diff line
		from functools import reduce

		import numpy as np
		import pandas as pd

		@@ -270,3 +271,37 @@ def calculate_slope(x1, x2):
		slopes = pd.Series(slopes, index=index)
		return slopes


		def cartesian(arrays, out=None):

		"""
		Generate a cartesian product of input arrays.
		Parameters
		----------
		arrays : list of array-like
		1-D arrays to form the cartesian product of.
		out : ndarray
		Array to place the cartesian product in.
		Returns
		-------
		out : ndarray
		2-D array of shape (M, len(arrays)) containing cartesian products
		formed of input arrays.

		from scikit-learn
		https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/utils/extmath.py
		"""
		arrays = [np.asarray(x) for x in arrays]
		shape = (len(x) for x in arrays)
		dtype = arrays[0].dtype

		ix = np.indices(shape)
		ix = ix.reshape(len(arrays), -1).T

		if out is None:
		out = np.empty_like(ix, dtype=dtype)

		for n, arr in enumerate(arrays):
		out[:, n] = arrays[n][ix[:, n]]

		return out

notebooks/Ciratefi.ipynb

0 → 100644

+246 −0

File added.

Preview size limit exceeded, changes collapsed.