Replace Yellow Background Image with Transparency

Question

I am trying to remove the yellow background from a set of images of this kind:

and replace it with transparency using masks using the opencv library. There is my code:

HSV_RANGES = {
    # red is a major color
    'red': [
        {
            'lower': np.array([0, 39, 64]),
            'upper': np.array([20, 255, 255])
        },
        {
            'lower': np.array([161, 39, 64]),
            'upper': np.array([180, 255, 255])
        }
    ],
    # yellow is a minor color
    'yellow': [
        {
            'lower': np.array([21, 39, 64]),
            'upper': np.array([40, 255, 255])
        }
    ],
    # green is a major color
    'green': [
        {
            'lower': np.array([41, 39, 64]),
            'upper': np.array([80, 255, 255])
        }
    ],
    # cyan is a minor color
    'cyan': [
        {
            'lower': np.array([81, 39, 64]),
            'upper': np.array([100, 255, 255])
        }
    ],
    # blue is a major color
    'blue': [
        {
            'lower': np.array([101, 39, 64]),
            'upper': np.array([140, 255, 255])
        }
    ],
    # violet is a minor color
    'violet': [
        {
            'lower': np.array([141, 39, 64]),
            'upper': np.array([160, 255, 255])
        }
    ],
    # next are the monochrome ranges
    # black is all H & S values, but only the lower 25% of V
    'black': [
        {
            'lower': np.array([0, 0, 0]),
            'upper': np.array([180, 255, 63])
        }
    ],
    # gray is all H values, lower 15% of S, & between 26-89% of V
    'gray': [
        {
            'lower': np.array([0, 0, 64]),
            'upper': np.array([180, 38, 228])
        }
    ],
    # white is all H values, lower 15% of S, & upper 10% of V
    'white': [
        {
            'lower': np.array([0, 0, 229]),
            'upper': np.array([180, 38, 255])
        }
    ]
}

def create_mask(hsv_img, colors):
    mask = np.zeros((hsv_img.shape[0], hsv_img.shape[1]), dtype=np.uint8)

    for color in colors:
        for color_range in HSV_RANGES[color]:
            mask += cv2.inRange(
                hsv_img,
                color_range['lower'],
                color_range['upper']
            )

    return mask

for file_name in os.listdir(fly_dataset):
    file_path = os.path.join(fly_dataset, file_name)
    
    image = cv2.imread(file_path)

    #remove background
    output = image
    
    # Create HSV Image and threshold it into the proper range.
    hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV) # Converting color space from BGR to HSV
    mask = create_mask(image, ['red'])
    
    cv2_imshow(mask)

    # Create the output image, using the mask created above. This will perform the removal of all unneeded colors, but will keep a black background.
    output = cv2.bitwise_and(image, image, mask=mask)
    
    # Add an alpha channel, and update the output image variable
    *_, alpha = cv2.split(output)
    dst = cv2.merge((output, alpha))
    output = dst

    #save image
    cv2.imwrite(fly_png + file_name.replace("jpg", "png") , output)

However, I am not having success, since the algorithm is not intelligent and therefore removes part of the flies.

Does anyone know a way to improve this algorithm or even know a better way to solve this problem?