OpenCV Python binds incredibly slow iterations through image data

Question

I recently took some code that tracked an object based on color in OpenCV c++ and rewrote it in the python bindings.

The overall results and method

Answer 1

Try using numpy to do your calculation, rather than nested loops. You should get C-like performance for simple calculations like this from numpy.

For example, your nested for loops can be replaced with a couple of numpy expressions...

I'm not terribly familiar with opencv, but I think the python bindings now have a numpy array interface, so your example above should be as simple as:

cv.PyrDown(img, dsimg)

data = np.asarray(dsimg)
blue, green, red = data.T

res = (green > (_RED_DIFF + red)) & (green > (_BLU_DIFF + blue))
res = res.astype(np.uint8) * 255

res = cv.fromarray(res)

(Completely untested, of course...) Again, I'm really not terribly familar with opencv, but nested python for loops are not the way to go about modifying an image element-wise, regardless...

Hope that helps a bit, anyway!