def METHOD_NAME(self, img):
    input_names = self.predictor.get_input_names()
    input_handle = {}
    for i in range(len(input_names)):
        input_handle[input_names[i]] = self.predictor.get_input_handle(
            input_names[i])
    output_names = self.predictor.get_output_names()
    output_handle = self.predictor.get_output_handle(output_names[0])
    img_inputs = img.astype('float32')
    ori_h, ori_w = img_inputs.shape[:2]
    img_inputs = self._preprocess(img=img_inputs)
    input_handle[input_names[0]].copy_from_cpu(img_inputs)
    self.predictor.METHOD_NAME()
    results = output_handle.copy_to_cpu()
    result = results[0].squeeze().astype('uint8')
    result = cv2.resize(result, (ori_w, ori_h), interpolation=cv2.INTER_NEAREST)
    result = self.get_pseudo_color_map(result)
    # result = (result * 10).astype('uint8')
    return result