Closed Elaineok closed 1 year ago
def _crf_with_alpha(cam_dict, alpha): v = np.array(list(cam_dict.values())) bg_score = np.power(1 - np.max(v, axis=0, keepdims=True), alpha) bgcam_score = np.concatenate((bg_score, v), axis=0) crf_score = imutils.crf_inference(orig_img, bgcam_score, labels=bgcam_score.shape[0]) pred_map = crf_score.argmax(0).astype(np.uint8) keys = np.array(list(cam_dict.keys()))+1 keys = np.pad(keys, (1, 0), mode='constant') pred_map = keys[pred_map] return pred_map for t in crf_alpha: crf = _crf_with_alpha(cam_dict, t) folder = args.out_crf + ('_%.1f' % t) if not os.path.exists(folder): os.makedirs(folder) import imageio imageio.imsave(os.path.join(folder, "%s.png" % img_name), crf.astype(np.uint8)) print(iter)
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