Color thresholding an HLS jpeg image

I am trying to color threshold a jpeg image so that I can keep the lane lines and hopefully get rid of the rest of the world.
I am reading the image using cv2 as follows:

test_image = cv2.imread(myimage)
#convert to RGB space from BGR
test_image = cv2.cvtColor(test_image, cv2.COLOR_BGR2RGB)

Then, I convert the test_image to HLS color space, to retain l channel as below:

def get_l_channel_hls(img):
    # Convert to HLS color space and separate the l channel
    hls = cv2.cvtColor(img, cv2.COLOR_RGB2HLS).astype(np.float)
    l_channel = hls[:,:,1]
    return l_channel

Then I apply some thresholds to this l channel and replace the pixel values by 0 or 1, so that I can retain only the pixels I want. (I will later multiply these values by 255, to make the retained pixels appear white)

def get_color_channel_thresholded_binary(channel, thresh=(0,255):
    # Threshold color channel
    print("min color threshold: {}".format(thresh[0]))
    print("max color threshold: {}".format(thresh[1])) 
    binary = np.zeros_like(channel)
    binary[(channel > thresh[0]) | (channel <= thresh[1])] = 1
    return binary

Then, I take this binary map and replace the retained pixels with 255

def get_overall_combined_binary(binary1):
    grayscaled_binary = np.zeros_like(binary1)
    grayscaled_binary [(binary1 == 1)] = 255
    return grayscaled_binary

And I display this binary using matplotlib pyplot as below:

import matplotlib.pyplot as plt
#grayscaled_binary = # get the grayscaled binary using above APIs
imshow(grayscaled_binary, cmap='gray')

What I am observing here is rather strange. The image appears all black for ANY values for which thresh[1] < thresh[0]. i.e. maximum threshold is LESS than the minimum threshold. And I have no clue as to why this is happening.

I have reviewed the code a few times now and I don’t see any bugs in it. The only difference between the code I have pasted here vs the one I am using is that, I’m using IPython widgets in Jupyter notebook to interact.

I’d greatly appreciate any help or insight with this topic.
I’m also attaching two examples of what I am talking about.
Thanks in advance.