def decode_segmap(image: np.ndarray, nc: int = 21):
   
    label_colors = np.array([(0, 0, 0),  # 0=background
                # 1=aeroplane, 2=bicycle, 3=bird, 4=boat, 5=bottle
                (128, 0, 0), (0, 128, 0), (128, 128, 0), (0, 0, 128), (128, 0, 128),
                # 6=bus, 7=car, 8=cat, 9=chair, 10=cow
                (0, 128, 128), (128, 128, 128), (64, 0, 0), (192, 0, 0), (64, 128, 0),
                # 11=dining table, 12=dog, 13=horse, 14=motorbike, 15=person
                (192, 128, 0), (64, 0, 128), (192, 0, 128), (64, 128, 128), (192, 128, 128),
                # 16=potted plant, 17=sheep, 18=sofa, 19=train, 20=tv/monitor
                (0, 64, 0), (128, 64, 0), (0, 192, 0), (128, 192, 0), (0, 64, 128)])

    r = np.full_like(image, fill_value=255).astype(np.uint8)
    g = np.full_like(image, fill_value=255).astype(np.uint8)
    b = np.full_like(image, fill_value=255).astype(np.uint8)
   
    for l in range(0, nc):
        idx = image == l
        r[idx] = label_colors[l, 0]
        g[idx] = label_colors[l, 1]
        b[idx] = label_colors[l, 2]
     
    rgb = np.stack([r, g, b], axis=2)
    return rgb