In OpenCV (Python), why am I getting 3 channel images from a grayscale image?

Your code is correct, it seems that cv2.imread load an image with three channels unless CV_LOAD_IMAGE_GRAYSCALE is set.

>>> import cv2
>>> image = cv2.imread('foo.jpg')
>>> print image.shape
 (184, 300, 3)
>>> gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
>>> print gray_image.shape 
 (184, 300)
>>> cv2.imwrite('gray.jpg', gray_image)

Now if you load the image:

>>> image = cv2.imread('gray.jpg')
>>> print image.shape
 (184, 300, 3)

It seems that you have saved the image as BGR, however it is not true, it is just opencv, by default it reads the image with 3 channels, and in the case it is grayscale it copies its layer three times. If you load again the image with scipy you could see that the image is indeed grayscale:

>>> from scipy.ndimage import imread
>>> image2 = imread('gray.jpg')
>>> print image2.shape
 (184, 300)

So if you want to load a grayscale image you will need to set CV_LOAD_IMAGE_GRAYSCALE flag:

>>> image = cv2.imread('gray.jpg', cv2.CV_LOAD_IMAGE_GRAYSCALE)
>>> print image.shape
 (184, 300)

try this:

 img = cv2.imread('gray.jpg',0)

0 for gray and 1 for color

In openCV reading jpg images result 3 channel images by default. So i'm not sure if you can actually see from jpg file that it's already grayscaled but you can always load it as grayscaled. It would bring problems only if the image isn't grayscaled beforehand and for your case i believe that it wouldn't work. So short answer: you cant save jpg as onechanneled image. So you would need to grayscale it again after reading or figure out new way determine if image is grayscaled or not.