def gamma_augmentation(x):
    z_value = np.random.uniform(-0.25, 0.25)
    nominator = np.log(0.5 + 2 ** (-0.5) * z_value)
    denominator = np.log(0.5 - 2 ** (-0.5) * z_value)
    gamma_value = nominator / (denominator + EPSILON)
    return x ** gamma_value


def poisson_noise(x):
    peak = np.random.uniform(0.95, 1.0)
    noisy = np.random.poisson(x * 255.0 * peak) / peak / 255.0
    noisy = np.clip(noisy, 0.0, 1.0)
    return noisy


def brightness_change(x):
    x = cv2.cvtColor((x * 255).astype(np.float32), cv2.COLOR_RGB2HSV)
    random_bright = .5 + np.random.random()
    x[:, :, 2] *= random_bright
    x[:, :, 2] = np.clip(x[:, :, 2], 0, 255)
    x = cv2.cvtColor(x, cv2.COLOR_HSV2BGR)
    return x / 255.