image_test = params.small_images[0]
mask = np.zeros(image_test.shape, dtype=np.uint8)
roi_corners = np.array([[0, 14], [13.33, 28], [26.66, 28], [39, 14], [26.66, 0], [13.33, 0]], dtype=np.int32)
# fill the ROI so it doesn't get wiped out when the mask is applied
channel_count = image_test.shape[2]  # i.e. 3 or 4 depending on your image
ignore_mask_color = (255,)*channel_count
cv.fillConvexPoly(mask, roi_corners, ignore_mask_color)
# apply the mask
masked_image = cv.bitwise_and(image_test, mask)
# save the result
cv.imwrite('image_masked.png', masked_image)