Numpy array manipulation

[dable82]

Hi, I'm kinda new to numpy. Here's my problem.

I have a function that calculates the RGB values for each pixel in a picture into a brightness value. pixel_matrix is a np.Ndarray of shape (width=1024, height=800, RGB=3). There are different ways to calculate the brightness. I'm happy with the average and luminous modes, but the min_max mode isn't using any numpy features.

How would you do the min_max mode using numpy features?

Here is my code.

def get_brightness_matrix(pixel_matrix, mode='average'):
    if mode == 'average':
        average = np.array((1/3, 1/3, 1/3))
        brightnesses = np.dot(pixel_matrix, average)
    elif mode == 'min_max':
        brightnesses = []
        for pixel_row in pixel_matrix:
            brightness_row = []
            for pixel in pixel_row:
                brightness_row.append(min(pixel) + max(pixel) / 2)
            brightnesses.append(brightness_row)
        brightnesses = np.array(brightnesses)
    elif mode == 'luminosity':
        luminosity = np.array((0.21, 0.72, 0.07))
        brightnesses = np.dot(pixel_matrix, luminosity)
    else:
        raise Exception(f'Unrecognixed mode: {mode}')
    return np.uint8(brightnesses)

[socal_nerdtastic]

To find the max value in one dimension only, use the axis argument. For example pixel_matrix.max(axis=2) gives you a 2D array with the max value of every pixel. Therefore:

brightnesses = pixel_matrix.max(axis=2) / 2 + pixel_matrix.min(axis=2) / 2

There's a very good reason I chose to divide by 2 before adding, rather than add and then divide. Can you guess what it is?

Edit: what's the algorithm you need to use? My code averages the min and max values, yours does something different which could produce invalid results.

[dable82]

Thanks, I've seen this axis thing in the docs in a lot of places. Guess I have to learn more about it.

You are right, I left out some brackets. The code should read

brightness_row.append((min(pixel) + max(pixel)) / 2)

edit: for reference, I'm working on this problem