Update to 2.0.0 tree from current Fremantle build

[opencv] / tests / swig_python / homography_tests.py

diff --git a/tests/swig_python/homography_tests.py b/tests/swig_python/homography_tests.py
new file mode 100755 (executable)
index 0000000..2d2ed58
--- /dev/null
+++ b/tests/swig_python/homography_tests.py
@@ -0,0 +1,97 @@
+#!/usr/bin/env python
+
+# 2009-01-16, Xavier Delacour <xavier.delacour@gmail.com>
+
+import unittest
+from numpy import *;
+from numpy.linalg import *;
+import sys;
+
+import cvtestutils
+from cv import *;
+from adaptors import *;
+
+def transform(H,x):
+    x1 = H * asmatrix(r_[x[0],x[1],1]).transpose()
+    x1 = asarray(x1).flatten()
+    return r_[x1[0]/x1[2],x1[1]/x1[2]]
+
+class homography_test(unittest.TestCase):
+
+    def test_ransac_identity(self):
+        pts1 = random.rand(100,2);
+        result,H = cvFindHomography(pts1, pts1, CV_RANSAC, 1e-5);
+        assert(result and all(abs(Ipl2NumPy(H) - eye(3)) < 1e-5));
+
+    def test_ransac_0_outliers(self):
+        pts1 = random.rand(100,2);
+        H1 = asmatrix(random.rand(3,3));
+        H1 = H1 / H1[2,2]
+        pts2 = [transform(H1,x) for x in pts1]
+        result,H = cvFindHomography(pts1, pts2, CV_RANSAC, 1e-5);
+        assert(result and all(abs(H1-H)<1e-5))
+
+    def test_ransac_30_outliers(self):
+        pts1 = random.rand(100,2);
+        H1 = asmatrix(random.rand(3,3));
+        H1 = H1 / H1[2,2]
+        pts2 = [transform(H1,x) for x in pts1]
+        pts2[0:30] = random.rand(30,2)
+        result,H = cvFindHomography(pts1, pts2, CV_RANSAC, 1e-5);
+        assert(result and all(abs(H1-H)<1e-5))
+
+    def test_ransac_70_outliers(self):
+        pts1 = random.rand(100,2);
+        H1 = asmatrix(random.rand(3,3));
+        H1 = H1 / H1[2,2]
+        pts2 = [transform(H1,x) for x in pts1]
+        pts2[0:70] = random.rand(70,2)
+        result,H = cvFindHomography(pts1, pts2, CV_RANSAC, 1e-5);
+        assert(result and all(abs(H1-H)<1e-5))
+
+    def test_ransac_90_outliers(self):
+        pts1 = random.rand(100,2);
+        H1 = asmatrix(random.rand(3,3));
+        H1 = H1 / H1[2,2]
+        pts2 = [transform(H1,x) for x in pts1]
+        pts2[0:90] = random.rand(90,2)
+        result,H = cvFindHomography(pts1, pts2, CV_RANSAC, 1e-5);
+        assert(not result or not all(abs(H1-H)<1e-5))
+
+    def test_lmeds_identity(self):
+        pts1 = random.rand(100,2);
+        result,H = cvFindHomography(pts1, pts1, CV_LMEDS);
+        assert(result and all(abs(Ipl2NumPy(H) - eye(3)) < 1e-5));
+
+    def test_lmeds_0_outliers(self):
+        pts1 = random.rand(100,2);
+        H1 = asmatrix(random.rand(3,3));
+        H1 = H1 / H1[2,2]
+        pts2 = [transform(H1,x) for x in pts1]
+        result,H = cvFindHomography(pts1, pts2, CV_LMEDS);
+        assert(result and all(abs(H1-H)<1e-5))
+
+    def test_lmeds_30_outliers(self):
+        pts1 = random.rand(100,2);
+        H1 = asmatrix(random.rand(3,3));
+        H1 = H1 / H1[2,2]
+        pts2 = [transform(H1,x) for x in pts1]
+        pts2[0:30] = random.rand(30,2)
+        result,H = cvFindHomography(pts1, pts2, CV_LMEDS);
+        assert(result and all(abs(H1-H)<1e-5))
+
+    def test_lmeds_70_outliers(self):
+        pts1 = random.rand(100,2);
+        H1 = asmatrix(random.rand(3,3));
+        H1 = H1 / H1[2,2]
+        pts2 = vstack([transform(H1,x) for x in pts1])
+        pts2[0:70] = random.rand(70,2)
+        result,H = cvFindHomography(pts1, pts2, CV_LMEDS);
+        assert(not result or not all(abs(H1-H)<1e-5))
+
+def suite():
+    return unittest.TestLoader().loadTestsFromTestCase(homography_test)
+
+if __name__ == '__main__':
+    unittest.TextTestRunner(verbosity=2).run(suite())
+