Forward the image through the LSTM network model

        Parameters
        ----------
        img_: int of array

        Returns
        ----------
        label_list: string of list

def forward_ocr(self, img_):
        """Forward the image through the LSTM network model

        Parameters
        ----------
        img_: int of array

        Returns
        ----------
        label_list: string of list
        """
        img_ = cv2.resize(img_, (80, 30))
        img_ = img_.transpose(1, 0)
        print(img_.shape)
        img_ = img_.reshape((1, 80, 30))
        print(img_.shape)
        # img_ = img_.reshape((80 * 30))
        img_ = np.multiply(img_, 1 / 255.0)
        self.predictor.forward(data=img_, **self.init_state_dict)
        prob = self.predictor.get_output(0)
        label_list = []
        for p in prob:
            print(np.argsort(p))
            max_index = np.argsort(p)[::-1][0]
            label_list.append(max_index)
        return self.__get_string(label_list)