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)))
