if __name__ == "__main__": args = utility.parse_args() image_file_list = get_image_file_list(args.image_dir) text_detector = TextDetector(args) count = 0 total_time = 0 draw_img_save = "./inference_results" if not os.path.exists(draw_img_save): os.makedirs(draw_img_save) for image_file in image_file_list: img, flag = check_and_read_gif(image_file) if not flag: img = cv2.imread(image_file) if img is None: logger.info("error in loading image:{}".format(image_file)) continue dt_boxes, elapse = text_detector(img) if count > 0: total_time += elapse count += 1 logger.info("Predict time of {}: {}".format(image_file, elapse)) src_im = utility.draw_text_det_res(dt_boxes, image_file) img_name_pure = os.path.split(image_file)[-1] img_path = os.path.join(draw_img_save, "det_res_{}".format(img_name_pure)) cv2.imwrite(img_path, src_im) logger.info("The visualized image saved in {}".format(img_path)) if count > 1: logger.info("Avg Time: {}".format(total_time / (count - 1)))
count = 0 total_time = 0 for image_file in image_file_list: # if 'mcocr_private_145120pgiom' not in image_file: # continue img, flag = check_and_read_gif(image_file) if not flag: img = cv2.imread(image_file) if img is None: logger.info("error in loading image:{}".format(image_file)) continue dt_boxes, elapse = text_detector(img) if count > 0: total_time += elapse count += 1 logger.info("{} Predict time of {}: {}".format(count, image_file, elapse)) img_name_pure = os.path.split(image_file)[-1] output_txt_path = os.path.join(det_out_txt_dir, img_name_pure.replace('.jpg', '.txt')) src_im = utility.draw_text_det_res(dt_boxes, image_file, save_path=output_txt_path) if det_visualize: img_path = os.path.join(det_out_viz_dir, "{}".format(img_name_pure)) cv2.imwrite(img_path, src_im) logger.info("The visualized image saved in {}".format(img_path)) if count > 1: logger.info("Avg Time: {}".format(total_time / (count - 1)))