[FIXED] Create gradient image in numpy for LUT (Look Up Tables)

Issue

What I'm trying to achieve: lookup tables to create duotone effect also called false color.

Say I have two colours: pure red and pure green provided in hex format ff0000 and 00ff00 respectively. We know its essentially (255, 0, 0) and (0, 255, 0). I need to create a 256x1 gradient image in numpy with red and green at both ends of the gradient.

I would strongly prefer to limit the dependancies to numpy and cv2.

Below is a code that works for me just fine, however all the rgb values are already hardcoded and I need to compute LUT gradient map dynamically for any given left and right colors (LUT tables truncated for brevity):

lut = np.zeros((256, 1, 3), dtype=np.uint8)

lut[:, 0, 0] = [250,248,246,244,242,240,238,236,234,232,230, ...]
lut[:, 0, 1] = [109,107,105,103,101,99,97,95,93,91,89,87,85, ...]
lut[:, 0, 2] = [127,127,127,127,127,127,127,127,127,127,127, ...]

im_color = cv2.LUT(image, lut)

Solution

From here modifying to give numpy arrays

def hex_to_rgb(hex):
     hex = hex.lstrip('#')
     hlen = len(hex)
     return np.array([int(hex[i:i+hlen//3], 16) for i in range(0, hlen, hlen//3)])

Then the numpy part:

def gradient(hex1, hex2):
    np1 = hex_to_rgb(hex1)
    np2 = hex_to_rgb(hex2)
    return np.linspace(np1[:, None], np2[:, None], 256, dtype = int)

Answered By - Daniel F