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diff --git a/tests/swig_python/lsh_tests.py b/tests/swig_python/lsh_tests.py
new file mode 100755
index 0000000..83c4fe4
--- /dev/null
+++ b/tests/swig_python/lsh_tests.py
@@ -0,0 +1,122 @@
+#!/usr/bin/env python
+
+# 2009-01-12, Xavier Delacour <xavier.delacour@gmail.com>
+
+# gdb --cd ~/opencv-lsh/tests/python --args /usr/bin/python lsh_tests.py
+# set env PYTHONPATH /home/x/opencv-lsh/debug/interfaces/swig/python:/home/x/opencv-lsh/debug/lib
+# export PYTHONPATH=/home/x/opencv-lsh/debug/interfaces/swig/python:/home/x/opencv-lsh/debug/lib
+
+import unittest
+from numpy import *;
+from numpy.linalg import *;
+import sys;
+
+import cvtestutils
+from cv import *;
+from adaptors import *;
+
+def planted_neighbors(query_points, R = .4):
+    n,d = query_points.shape
+    data = zeros(query_points.shape)
+    for i in range(0,n):
+        a = random.rand(d)
+        a = random.rand()*R*a/sqrt(sum(a**2))
+        data[i] = query_points[i] + a
+    return data
+
+class lsh_test(unittest.TestCase):
+
+    def test_basic(self):
+        n = 10000;
+        d = 64;
+        query_points = random.rand(n,d)*2-1;
+        data = planted_neighbors(query_points)
+
+        lsh = cvCreateMemoryLSH(d, n);
+        cvLSHAdd(lsh, data);
+        indices,dist = cvLSHQuery(lsh, query_points, 1, 100);
+        correct = sum([i == j for j,i in enumerate(indices)])
+        assert(correct >= n * .75);
+
+    def test_sensitivity(self):
+        n = 10000;
+        d = 64;
+        query_points = random.rand(n,d);
+        data = random.rand(n,d);
+
+        lsh = cvCreateMemoryLSH(d, 1000, 10, 10);
+        cvLSHAdd(lsh, data);
+
+        good = 0
+        trials = 20
+        print 
+        for x in query_points[0:trials]:
+            x1 = asmatrix(x) # PyArray_to_CvArr doesn't like 1-dim arrays
+            indices,dist = cvLSHQuery(lsh, x1, n, n);
+            indices = Ipl2NumPy(indices)
+            indices = unique(indices[where(indices>=0)])
+
+            brute = vstack([(sqrt(sum((a-x)**2)),i,0) for i,a in enumerate(data)])
+            lshp = vstack([(sqrt(sum((x-data[i])**2)),i,1) for i in indices])
+            combined = vstack((brute,lshp))
+            combined = combined[argsort(combined[:,0])]
+
+            spread = [i for i,a in enumerate(combined[:,2]) if a==1]
+            spread = histogram(spread,bins=4,new=True)[0]
+            print spread, sum(diff(spread)<0)
+            if sum(diff(spread)<0) == 3: good = good + 1
+        print good,"pass"
+        assert(good > trials * .75);
+
+    def test_remove(self):
+        n = 10000;
+        d = 64;
+        query_points = random.rand(n,d)*2-1;
+        data = planted_neighbors(query_points)
+        lsh = cvCreateMemoryLSH(d, n);
+        indices = cvLSHAdd(lsh, data);
+        assert(LSHSize(lsh)==n);
+        cvLSHRemove(lsh,indices[0:n/2])
+        assert(LSHSize(lsh)==n/2);
+
+    def test_destroy(self):
+        n = 10000;
+        d = 64;
+        lsh = cvCreateMemoryLSH(d, n);
+
+    def test_destroy2(self):
+        n = 10000;
+        d = 64;
+        query_points = random.rand(n,d)*2-1;
+        data = planted_neighbors(query_points)
+        lsh = cvCreateMemoryLSH(d, n);
+        indices = cvLSHAdd(lsh, data);
+
+
+# move this to another file
+
+# img1 = cvLoadImage(img1_fn);
+# img2 = cvLoadImage(img2_fn);
+# pts1,desc1 = cvExtractSURF(img1); # * make util routine to extract points and descriptors
+# pts2,desc2 = cvExtractSURF(img2);
+# lsh = cvCreateMemoryLSH(d, n);
+# cvLSHAdd(lsh, desc1);
+# indices,dist = cvLSHQuery(lsh, desc2, 2, 100);
+# matches = [((pts1[x[0]].pt.x,pts1[x[0]].pt.y),(pts2[j].pt.x,pts2[j].pt.y)) \
+#            for j,x in enumerate(hstack((indices,dist))) \
+#            if x[2] and (not x[3] or x[2]/x[3]>.6)]
+# out = cvCloneImage(img1);
+# for p1,p2 in matches:
+#     cvCircle(out,p1,3,CV_RGB(255,0,0));
+#     cvLine(out,p1,p2,CV_RGB(100,100,100));
+# cvNamedWindow("matches");
+# cvShowImage("matches",out);
+# cvWaitKey(0);
+
+        
+def suite():
+    return unittest.TestLoader().loadTestsFromTestCase(lsh_test)
+
+if __name__ == '__main__':
+    unittest.TextTestRunner(verbosity=2).run(suite())
+