Uses bit shift vs. adaptative normalization

Adaptative normalization to the current frame extrema is ok
for visualizing but turns data meaningless for any other purpose.
So in order to keep the example useful for all those purpose
the dept are just shifted to maximize the dynamic range of the
received 11 bits over the 16 representation bits.

Signed-off-by: David García Garzón <[email protected]>

Author: David García Garzón

wrappers/python/demo_cv_async.py

@@ -9,8 +9,7 @@
 die = False
 
 def display_depth(dev, data, timestamp):
-    data -= np.min(data.ravel())
-    data *= 65536 / np.max(data.ravel())
+    data <<= (16-11) # 11 bits -> 16 bits
     image = cv.CreateImageHeader((data.shape[1], data.shape[0]),
                                  cv.IPL_DEPTH_16U,
                                  1)