def METHOD_NAME(self, test_dir, out_dir):
    os.makedirs(out_dir, exist_ok=True)
    transform = ToTensor()
    all_files = glob.glob(os.path.join(test_dir, "*"))
    self.model.eval()
    for f in tqdm(all_files):
        image = np.asarray(Image.open(f), dtype='float32') / 255.
        image = transform(image).unsqueeze(0).to(self.device)
        centers, final = self.predict(image)
        # final = final.squeeze().cpu().numpy()
        final = (final * self.saving_factor).astype('uint16')
        basename = os.path.basename(f).split('.')[0]
        save_path = os.path.join(out_dir, basename + ".png")
        Image.fromarray(final.squeeze()).save(save_path)