diff --git a/modules/python/api b/modules/python/api
index c0b3d5d0d7..b56461d390 100644
--- a/modules/python/api
+++ b/modules/python/api
@@ -1499,6 +1499,15 @@ KalmanCorrect ROCvMat*
 KalmanPredict ROCvMat*
   CvKalman* kalman
   CvMat control NULL
+SnakeImage points
+  IplImage image
+  CvPoints points
+  floats alpha
+  floats beta
+  floats gamma
+  CvSize win
+  CvTermCriteria criteria
+  int calc_gradient 1
 
 # Optical Flow
 CalcOpticalFlowLK
diff --git a/modules/python/cv.cpp b/modules/python/cv.cpp
index 796d23c596..5bb444bcb6 100644
--- a/modules/python/cv.cpp
+++ b/modules/python/cv.cpp
@@ -1812,16 +1812,24 @@ struct floats {
 };
 static int convert_to_floats(PyObject *o, floats *dst, const char *name = "no_name")
 {
-  PyObject *fi = PySequence_Fast(o, name);
-  if (fi == NULL)
-    return 0;
-  dst->count = PySequence_Fast_GET_SIZE(fi);
-  dst->f = new float[dst->count];
-  for (Py_ssize_t i = 0; i < PySequence_Fast_GET_SIZE(fi); i++) {
-    PyObject *item = PySequence_Fast_GET_ITEM(fi, i);
-    dst->f[i] = (float)PyFloat_AsDouble(item);
+  if (PySequence_Check(o)) {
+    PyObject *fi = PySequence_Fast(o, name);
+    if (fi == NULL)
+      return 0;
+    dst->count = PySequence_Fast_GET_SIZE(fi);
+    dst->f = new float[dst->count];
+    for (Py_ssize_t i = 0; i < PySequence_Fast_GET_SIZE(fi); i++) {
+      PyObject *item = PySequence_Fast_GET_ITEM(fi, i);
+      dst->f[i] = (float)PyFloat_AsDouble(item);
+    }
+    Py_DECREF(fi);
+  } else if (PyNumber_Check(o)) {
+    dst->count = 1;
+    dst->f = new float[1];
+    dst->f[0] = PyFloat_AsDouble(o);
+  } else {
+    return failmsg("Expected list of floats, or float for argument '%s'", name);
   }
-  Py_DECREF(fi);
   return 1;
 }
 
@@ -2552,6 +2560,16 @@ static PyObject *FROM_CvSubdiv2DEdge(CvSubdiv2DEdge r)
   return (PyObject*)m;
 }
 
+static PyObject *FROM_CvPoints(CvPoints src)
+{
+  PyObject *pr;
+  pr = PyList_New(src.count);
+  for (int i = 0; i < src.count; i++) {
+    PyList_SetItem(pr, i, FROM_CvPoint(src.p[i]));
+  }
+  return pr;
+}
+
 /************************************************************************/
 
 /* A few functions are too odd to be generated, 
@@ -3763,6 +3781,17 @@ static int zero = 0;
 #define constCvMat const CvMat
 #define FROM_constCvMatPTR(x) FROM_CvMatPTR((CvMat*)x)
 
+#define cvSnakeImage(image, points, length, a, b, g, win, criteria, calc_gradient) \
+  do { \
+    int coeff_usage; \
+    if ((alpha.count == 1) && (beta.count == 1) && (gamma.count == 1)) \
+      coeff_usage = CV_VALUE; \
+    else if ((length == alpha.count) && (alpha.count == beta.count) && (beta.count == gamma.count)) \
+      coeff_usage = CV_ARRAY; \
+    else \
+      return (PyObject*)failmsg("SnakeImage weights invalid"); \
+    cvSnakeImage(image, points, length, a, b, g, coeff_usage, win, criteria, calc_gradient); \
+  } while (0)
 
 #include "generated0.i"
 
diff --git a/tests/python/test.py b/tests/python/test.py
index b62b07010d..8bdfb8de19 100644
--- a/tests/python/test.py
+++ b/tests/python/test.py
@@ -770,6 +770,26 @@ class FunctionTests(OpenCVTests):
                                 expected = 0.0
                             self.assertEqual(M[rj,cj], expected)
 
+    def test_SnakeImage(self):
+        src = self.get_sample("samples/c/lena.jpg", 0)
+        pts = [ (512-i,i) for i in range(0, 512, 8) ]
+
+        # Make sure that weight arguments get validated
+        self.assertRaises(TypeError, lambda: cv.SnakeImage(cv.GetImage(src), pts, [1,2], .01, .01, (7,7), (cv.CV_TERMCRIT_ITER, 100, 0.1)))
+
+        # Smoke by making sure that points are changed by call
+        r = cv.SnakeImage(cv.GetImage(src), pts, .01, .01, .01, (7,7), (cv.CV_TERMCRIT_ITER, 100, 0.1))
+        if 0:
+            cv.PolyLine(src, [ r ], 0, 255)
+            self.snap(src)
+        self.assertEqual(len(r), len(pts))
+        self.assertNotEqual(r, pts)
+
+        # Ensure that list of weights is same as scalar weight
+        w = [.01] * len(pts)
+        r2 = cv.SnakeImage(cv.GetImage(src), pts, w, w, w, (7,7), (cv.CV_TERMCRIT_ITER, 100, 0.1))
+        self.assertEqual(r, r2)
+
     def test_Sum(self):
         for r in range(1,11):
             for c in range(1, 11):