diff --git a/doc/cv_histograms.tex b/doc/cv_histograms.tex
index 8a06a55e70..bfd424b5d2 100644
--- a/doc/cv_histograms.tex
+++ b/doc/cv_histograms.tex
@@ -159,7 +159,7 @@ int main( int argc, char** argv )
 }
 \end{lstlisting}
 \else % }{
-% \lstinputlisting{calchist.py}
+\lstinputlisting{python_fragments/calchist.py}
 \fi % }
 
 \cvCPyFunc{CalcProbDensity}
diff --git a/doc/python_fragments/calchist.py b/doc/python_fragments/calchist.py
new file mode 100644
index 0000000000..f379dfec1a
--- /dev/null
+++ b/doc/python_fragments/calchist.py
@@ -0,0 +1,53 @@
+# Calculating and displaying 2D Hue-Saturation histogram of a color image
+
+import sys
+import cv
+
+def hs_histogram(src):
+    # Convert to HSV
+    hsv = cv.CreateImage(cv.GetSize(src), 8, 3)
+    cv.CvtColor(src, hsv, cv.CV_BGR2HSV)
+
+    # Extract the H and S planes
+    h_plane = cv.CreateMat(src.rows, src.cols, cv.CV_8UC1)
+    s_plane = cv.CreateMat(src.rows, src.cols, cv.CV_8UC1)
+    cv.Split(hsv, h_plane, s_plane, None, None)
+    planes = [h_plane, s_plane]
+
+    h_bins = 30
+    s_bins = 32
+    hist_size = [h_bins, s_bins]
+    # hue varies from 0 (~0 deg red) to 180 (~360 deg red again */
+    h_ranges = [0, 180]
+    # saturation varies from 0 (black-gray-white) to
+    # 255 (pure spectrum color)
+    s_ranges = [0, 255]
+    ranges = [h_ranges, s_ranges]
+    scale = 10
+    hist = cv.CreateHist([h_bins, s_bins], cv.CV_HIST_ARRAY, ranges, 1)
+    cv.CalcHist([cv.GetImage(i) for i in planes], hist)
+    (_, max_value, _, _) = cv.GetMinMaxHistValue(hist)
+
+    hist_img = cv.CreateImage((h_bins*scale, s_bins*scale), 8, 3)
+
+    for h in range(h_bins):
+        for s in range(s_bins):
+            bin_val = cv.QueryHistValue_2D(hist, h, s)
+            intensity = cv.Round(bin_val * 255 / max_value)
+            cv.Rectangle(hist_img,
+                         (h*scale, s*scale),
+                         ((h+1)*scale - 1, (s+1)*scale - 1),
+                         cv.RGB(intensity, intensity, intensity), 
+                         cv.CV_FILLED)
+    return hist_img
+
+if __name__ == '__main__':
+    src = cv.LoadImageM(sys.argv[1])
+    cv.NamedWindow("Source", 1)
+    cv.ShowImage("Source", src)
+
+    cv.NamedWindow("H-S Histogram", 1)
+    cv.ShowImage("H-S Histogram", hs_histogram(src))
+
+    cv.WaitKey(0)
+
diff --git a/tests/python/test.py b/tests/python/test.py
index fe32b13698..6f605b5bd6 100644
--- a/tests/python/test.py
+++ b/tests/python/test.py
@@ -1998,6 +1998,18 @@ class DocumentFragmentTests(OpenCVTests):
         cv.ConvertScale(disparity_left, disparity_left_visual, -16)
         # self.snap(disparity_left_visual)
 
+    def test_calchist(self):
+        from calchist import hs_histogram
+        i1 = self.get_sample("samples/c/lena.jpg")
+        i2 = self.get_sample("doc/pics/building.jpg")
+        i3 = cv.CloneMat(i1)
+        cv.Flip(i3, i3, 1)
+        h1 = hs_histogram(i1)
+        h2 = hs_histogram(i2)
+        h3 = hs_histogram(i3)
+        self.assertEqual(self.hashimg(h1), self.hashimg(h3))
+        self.assertNotEqual(self.hashimg(h1), self.hashimg(h2))
+
 class NewTests(OpenCVTests):
 
     pass