# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import os
import sys
import importlib

__dir__ = os.path.dirname(__file__)

import paddle
from paddle.utils import try_import

sys.path.append(os.path.join(__dir__, ""))

import cv2
import logging
import numpy as np
from pathlib import Path
import base64
from io import BytesIO
import pprint
from PIL import Image
from tools.infer import predict_system


def _import_file(module_name, file_path, make_importable=False):
    spec = importlib.util.spec_from_file_location(module_name, file_path)
    module = importlib.util.module_from_spec(spec)
    spec.loader.exec_module(module)
    if make_importable:
        sys.modules[module_name] = module
    return module


tools = _import_file(
    "tools", os.path.join(__dir__, "tools/__init__.py"), make_importable=True
)
ppocr = importlib.import_module("ppocr", "paddleocr")
ppstructure = importlib.import_module("ppstructure", "paddleocr")
from ppocr.utils.logging import get_logger

logger = get_logger()
from ppocr.utils.utility import (
    check_and_read,
    get_image_file_list,
    alpha_to_color,
    binarize_img,
)
from ppocr.utils.network import (
    maybe_download,
    download_with_progressbar,
    is_link,
    confirm_model_dir_url,
)
from tools.infer.utility import draw_ocr, str2bool, check_gpu
from ppstructure.utility import init_args, draw_structure_result
from ppstructure.predict_system import StructureSystem, save_structure_res, to_excel

logger = get_logger()
__all__ = [
    "PaddleOCR",
    "PPStructure",
    "draw_ocr",
    "draw_structure_result",
    "save_structure_res",
    "download_with_progressbar",
    "to_excel",
]

SUPPORT_DET_MODEL = ["DB"]
SUPPORT_REC_MODEL = ["CRNN", "SVTR_LCNet"]
BASE_DIR = os.path.expanduser("~/.paddleocr/")

DEFAULT_OCR_MODEL_VERSION = "PP-OCRv4"
SUPPORT_OCR_MODEL_VERSION = ["PP-OCR", "PP-OCRv2", "PP-OCRv3", "PP-OCRv4"]
DEFAULT_STRUCTURE_MODEL_VERSION = "PP-StructureV2"
SUPPORT_STRUCTURE_MODEL_VERSION = ["PP-Structure", "PP-StructureV2"]
MODEL_URLS = {
    "OCR": {
        "PP-OCRv4": {
            "det": {
                "ch": {
                    "url": "https://paddleocr.bj.bcebos.com/PP-OCRv4/chinese/ch_PP-OCRv4_det_infer.tar",
                },
                "en": {
                    "url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_infer.tar",
                },
                "ml": {
                    "url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/Multilingual_PP-OCRv3_det_infer.tar"
                },
            },
            "rec": {
                "ch": {
                    "url": "https://paddleocr.bj.bcebos.com/PP-OCRv4/chinese/ch_PP-OCRv4_rec_infer.tar",
                    "dict_path": "./ppocr/utils/ppocr_keys_v1.txt",
                },
                "en": {
                    "url": "https://paddleocr.bj.bcebos.com/PP-OCRv4/english/en_PP-OCRv4_rec_infer.tar",
                    "dict_path": "./ppocr/utils/en_dict.txt",
                },
                "korean": {
                    "url": "https://paddleocr.bj.bcebos.com/PP-OCRv4/multilingual/korean_PP-OCRv4_rec_infer.tar",
                    "dict_path": "./ppocr/utils/dict/korean_dict.txt",
                },
                "japan": {
                    "url": "https://paddleocr.bj.bcebos.com/PP-OCRv4/multilingual/japan_PP-OCRv4_rec_infer.tar",
                    "dict_path": "./ppocr/utils/dict/japan_dict.txt",
                },
                "chinese_cht": {
                    "url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/chinese_cht_PP-OCRv3_rec_infer.tar",
                    "dict_path": "./ppocr/utils/dict/chinese_cht_dict.txt",
                },
                "ta": {
                    "url": "https://paddleocr.bj.bcebos.com/PP-OCRv4/multilingual/ta_PP-OCRv4_rec_infer.tar",
                    "dict_path": "./ppocr/utils/dict/ta_dict.txt",
                },
                "te": {
                    "url": "https://paddleocr.bj.bcebos.com/PP-OCRv4/multilingual/te_PP-OCRv4_rec_infer.tar",
                    "dict_path": "./ppocr/utils/dict/te_dict.txt",
                },
                "ka": {
                    "url": "https://paddleocr.bj.bcebos.com/PP-OCRv4/multilingual/ka_PP-OCRv4_rec_infer.tar",
                    "dict_path": "./ppocr/utils/dict/ka_dict.txt",
                },
                "latin": {
                    "url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/latin_PP-OCRv3_rec_infer.tar",
                    "dict_path": "./ppocr/utils/dict/latin_dict.txt",
                },
                "arabic": {
                    "url": "https://paddleocr.bj.bcebos.com/PP-OCRv4/multilingual/arabic_PP-OCRv4_rec_infer.tar",
                    "dict_path": "./ppocr/utils/dict/arabic_dict.txt",
                },
                "cyrillic": {
                    "url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/cyrillic_PP-OCRv3_rec_infer.tar",
                    "dict_path": "./ppocr/utils/dict/cyrillic_dict.txt",
                },
                "devanagari": {
                    "url": "https://paddleocr.bj.bcebos.com/PP-OCRv4/multilingual/devanagari_PP-OCRv4_rec_infer.tar",
                    "dict_path": "./ppocr/utils/dict/devanagari_dict.txt",
                },
            },
            "cls": {
                "ch": {
                    "url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar",
                }
            },
        },
        "PP-OCRv3": {
            "det": {
                "ch": {
                    "url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_infer.tar",
                },
                "en": {
                    "url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_infer.tar",
                },
                "ml": {
                    "url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/Multilingual_PP-OCRv3_det_infer.tar"
                },
            },
            "rec": {
                "ch": {
                    "url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar",
                    "dict_path": "./ppocr/utils/ppocr_keys_v1.txt",
                },
                "en": {
                    "url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_infer.tar",
                    "dict_path": "./ppocr/utils/en_dict.txt",
                },
                "korean": {
                    "url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/korean_PP-OCRv3_rec_infer.tar",
                    "dict_path": "./ppocr/utils/dict/korean_dict.txt",
                },
                "japan": {
                    "url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/japan_PP-OCRv3_rec_infer.tar",
                    "dict_path": "./ppocr/utils/dict/japan_dict.txt",
                },
                "chinese_cht": {
                    "url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/chinese_cht_PP-OCRv3_rec_infer.tar",
                    "dict_path": "./ppocr/utils/dict/chinese_cht_dict.txt",
                },
                "ta": {
                    "url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/ta_PP-OCRv3_rec_infer.tar",
                    "dict_path": "./ppocr/utils/dict/ta_dict.txt",
                },
                "te": {
                    "url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/te_PP-OCRv3_rec_infer.tar",
                    "dict_path": "./ppocr/utils/dict/te_dict.txt",
                },
                "ka": {
                    "url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/ka_PP-OCRv3_rec_infer.tar",
                    "dict_path": "./ppocr/utils/dict/ka_dict.txt",
                },
                "latin": {
                    "url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/latin_PP-OCRv3_rec_infer.tar",
                    "dict_path": "./ppocr/utils/dict/latin_dict.txt",
                },
                "arabic": {
                    "url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/arabic_PP-OCRv3_rec_infer.tar",
                    "dict_path": "./ppocr/utils/dict/arabic_dict.txt",
                },
                "cyrillic": {
                    "url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/cyrillic_PP-OCRv3_rec_infer.tar",
                    "dict_path": "./ppocr/utils/dict/cyrillic_dict.txt",
                },
                "devanagari": {
                    "url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/devanagari_PP-OCRv3_rec_infer.tar",
                    "dict_path": "./ppocr/utils/dict/devanagari_dict.txt",
                },
            },
            "cls": {
                "ch": {
                    "url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar",
                }
            },
        },
        "PP-OCRv2": {
            "det": {
                "ch": {
                    "url": "https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_infer.tar",
                },
            },
            "rec": {
                "ch": {
                    "url": "https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_rec_infer.tar",
                    "dict_path": "./ppocr/utils/ppocr_keys_v1.txt",
                }
            },
            "cls": {
                "ch": {
                    "url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar",
                }
            },
        },
        "PP-OCR": {
            "det": {
                "ch": {
                    "url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar",
                },
                "en": {
                    "url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/en_ppocr_mobile_v2.0_det_infer.tar",
                },
                "structure": {
                    "url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_det_infer.tar"
                },
            },
            "rec": {
                "ch": {
                    "url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar",
                    "dict_path": "./ppocr/utils/ppocr_keys_v1.txt",
                },
                "en": {
                    "url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/en_number_mobile_v2.0_rec_infer.tar",
                    "dict_path": "./ppocr/utils/en_dict.txt",
                },
                "french": {
                    "url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/french_mobile_v2.0_rec_infer.tar",
                    "dict_path": "./ppocr/utils/dict/french_dict.txt",
                },
                "german": {
                    "url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/german_mobile_v2.0_rec_infer.tar",
                    "dict_path": "./ppocr/utils/dict/german_dict.txt",
                },
                "korean": {
                    "url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/korean_mobile_v2.0_rec_infer.tar",
                    "dict_path": "./ppocr/utils/dict/korean_dict.txt",
                },
                "japan": {
                    "url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/japan_mobile_v2.0_rec_infer.tar",
                    "dict_path": "./ppocr/utils/dict/japan_dict.txt",
                },
                "chinese_cht": {
                    "url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/chinese_cht_mobile_v2.0_rec_infer.tar",
                    "dict_path": "./ppocr/utils/dict/chinese_cht_dict.txt",
                },
                "ta": {
                    "url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ta_mobile_v2.0_rec_infer.tar",
                    "dict_path": "./ppocr/utils/dict/ta_dict.txt",
                },
                "te": {
                    "url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/te_mobile_v2.0_rec_infer.tar",
                    "dict_path": "./ppocr/utils/dict/te_dict.txt",
                },
                "ka": {
                    "url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ka_mobile_v2.0_rec_infer.tar",
                    "dict_path": "./ppocr/utils/dict/ka_dict.txt",
                },
                "latin": {
                    "url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/latin_ppocr_mobile_v2.0_rec_infer.tar",
                    "dict_path": "./ppocr/utils/dict/latin_dict.txt",
                },
                "arabic": {
                    "url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/arabic_ppocr_mobile_v2.0_rec_infer.tar",
                    "dict_path": "./ppocr/utils/dict/arabic_dict.txt",
                },
                "cyrillic": {
                    "url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/cyrillic_ppocr_mobile_v2.0_rec_infer.tar",
                    "dict_path": "./ppocr/utils/dict/cyrillic_dict.txt",
                },
                "devanagari": {
                    "url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/devanagari_ppocr_mobile_v2.0_rec_infer.tar",
                    "dict_path": "./ppocr/utils/dict/devanagari_dict.txt",
                },
                "structure": {
                    "url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_rec_infer.tar",
                    "dict_path": "ppocr/utils/dict/table_dict.txt",
                },
            },
            "cls": {
                "ch": {
                    "url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar",
                }
            },
        },
    },
    "STRUCTURE": {
        "PP-Structure": {
            "table": {
                "en": {
                    "url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_structure_infer.tar",
                    "dict_path": "ppocr/utils/dict/table_structure_dict.txt",
                }
            }
        },
        "PP-StructureV2": {
            "table": {
                "en": {
                    "url": "https://paddleocr.bj.bcebos.com/ppstructure/models/slanet/en_ppstructure_mobile_v2.0_SLANet_infer.tar",
                    "dict_path": "ppocr/utils/dict/table_structure_dict.txt",
                },
                "ch": {
                    "url": "https://paddleocr.bj.bcebos.com/ppstructure/models/slanet/ch_ppstructure_mobile_v2.0_SLANet_infer.tar",
                    "dict_path": "ppocr/utils/dict/table_structure_dict_ch.txt",
                },
            },
            "layout": {
                "en": {
                    "url": "https://paddleocr.bj.bcebos.com/ppstructure/models/layout/picodet_lcnet_x1_0_fgd_layout_infer.tar",
                    "dict_path": "ppocr/utils/dict/layout_dict/layout_publaynet_dict.txt",
                },
                "ch": {
                    "url": "https://paddleocr.bj.bcebos.com/ppstructure/models/layout/picodet_lcnet_x1_0_fgd_layout_cdla_infer.tar",
                    "dict_path": "ppocr/utils/dict/layout_dict/layout_cdla_dict.txt",
                },
            },
        },
    },
}


def parse_args(mMain=True):
    import argparse

    parser = init_args()
    parser.add_help = mMain
    parser.add_argument("--lang", type=str, default="ch")
    parser.add_argument("--det", type=str2bool, default=True)
    parser.add_argument("--rec", type=str2bool, default=True)
    parser.add_argument("--type", type=str, default="ocr")
    parser.add_argument("--savefile", type=str2bool, default=False)
    parser.add_argument(
        "--ocr_version",
        type=str,
        choices=SUPPORT_OCR_MODEL_VERSION,
        default="PP-OCRv4",
        help="OCR Model version, the current model support list is as follows: "
        "1. PP-OCRv4/v3 Support Chinese and English detection and recognition model, and direction classifier model"
        "2. PP-OCRv2 Support Chinese detection and recognition model. "
        "3. PP-OCR support Chinese detection, recognition and direction classifier and multilingual recognition model.",
    )
    parser.add_argument(
        "--structure_version",
        type=str,
        choices=SUPPORT_STRUCTURE_MODEL_VERSION,
        default="PP-StructureV2",
        help="Model version, the current model support list is as follows:"
        " 1. PP-Structure Support en table structure model."
        " 2. PP-StructureV2 Support ch and en table structure model.",
    )

    for action in parser._actions:
        if action.dest in [
            "rec_char_dict_path",
            "table_char_dict_path",
            "layout_dict_path",
        ]:
            action.default = None
    if mMain:
        return parser.parse_args()
    else:
        inference_args_dict = {}
        for action in parser._actions:
            inference_args_dict[action.dest] = action.default
        return argparse.Namespace(**inference_args_dict)


def parse_lang(lang):
    latin_lang = [
        "af",
        "az",
        "bs",
        "cs",
        "cy",
        "da",
        "de",
        "es",
        "et",
        "fr",
        "ga",
        "hr",
        "hu",
        "id",
        "is",
        "it",
        "ku",
        "la",
        "lt",
        "lv",
        "mi",
        "ms",
        "mt",
        "nl",
        "no",
        "oc",
        "pi",
        "pl",
        "pt",
        "ro",
        "rs_latin",
        "sk",
        "sl",
        "sq",
        "sv",
        "sw",
        "tl",
        "tr",
        "uz",
        "vi",
        "french",
        "german",
    ]
    arabic_lang = ["ar", "fa", "ug", "ur"]
    cyrillic_lang = [
        "ru",
        "rs_cyrillic",
        "be",
        "bg",
        "uk",
        "mn",
        "abq",
        "ady",
        "kbd",
        "ava",
        "dar",
        "inh",
        "che",
        "lbe",
        "lez",
        "tab",
    ]
    devanagari_lang = [
        "hi",
        "mr",
        "ne",
        "bh",
        "mai",
        "ang",
        "bho",
        "mah",
        "sck",
        "new",
        "gom",
        "sa",
        "bgc",
    ]
    if lang in latin_lang:
        lang = "latin"
    elif lang in arabic_lang:
        lang = "arabic"
    elif lang in cyrillic_lang:
        lang = "cyrillic"
    elif lang in devanagari_lang:
        lang = "devanagari"
    assert (
        lang in MODEL_URLS["OCR"][DEFAULT_OCR_MODEL_VERSION]["rec"]
    ), "param lang must in {}, but got {}".format(
        MODEL_URLS["OCR"][DEFAULT_OCR_MODEL_VERSION]["rec"].keys(), lang
    )
    if lang == "ch":
        det_lang = "ch"
    elif lang == "structure":
        det_lang = "structure"
    elif lang in ["en", "latin"]:
        det_lang = "en"
    else:
        det_lang = "ml"
    return lang, det_lang


def get_model_config(type, version, model_type, lang):
    if type == "OCR":
        DEFAULT_MODEL_VERSION = DEFAULT_OCR_MODEL_VERSION
    elif type == "STRUCTURE":
        DEFAULT_MODEL_VERSION = DEFAULT_STRUCTURE_MODEL_VERSION
    else:
        raise NotImplementedError

    model_urls = MODEL_URLS[type]
    if version not in model_urls:
        version = DEFAULT_MODEL_VERSION
    if model_type not in model_urls[version]:
        if model_type in model_urls[DEFAULT_MODEL_VERSION]:
            version = DEFAULT_MODEL_VERSION
        else:
            logger.error(
                "{} models is not support, we only support {}".format(
                    model_type, model_urls[DEFAULT_MODEL_VERSION].keys()
                )
            )
            sys.exit(-1)

    if lang not in model_urls[version][model_type]:
        if lang in model_urls[DEFAULT_MODEL_VERSION][model_type]:
            version = DEFAULT_MODEL_VERSION
        else:
            logger.error(
                "lang {} is not support, we only support {} for {} models".format(
                    lang,
                    model_urls[DEFAULT_MODEL_VERSION][model_type].keys(),
                    model_type,
                )
            )
            sys.exit(-1)
    return model_urls[version][model_type][lang]


def img_decode(content: bytes):
    np_arr = np.frombuffer(content, dtype=np.uint8)
    return cv2.imdecode(np_arr, cv2.IMREAD_UNCHANGED)


def check_img(img, alpha_color=(255, 255, 255)):
    """
    Check the image data. If it is another type of image file, try to decode it into a numpy array.
    The inference network requires three-channel images, So the following channel conversions are done
        single channel image: Gray to RGB R←Y,G←Y,B←Y
        four channel image: alpha_to_color
    args:
        img: image data
            file format: jpg, png and other image formats that opencv can decode, as well as gif and pdf formats
            storage type: binary image, net image file, local image file
        alpha_color: Background color in images in RGBA format
        return: numpy.array (h, w, 3) or list (p, h, w, 3) (p: page of pdf), boolean, boolean
    """
    flag_gif, flag_pdf = False, False
    if isinstance(img, bytes):
        img = img_decode(img)
    if isinstance(img, str):
        # download net image
        if is_link(img):
            download_with_progressbar(img, "tmp.jpg")
            img = "tmp.jpg"
        image_file = img
        img, flag_gif, flag_pdf = check_and_read(image_file)
        if not flag_gif and not flag_pdf:
            with open(image_file, "rb") as f:
                img_str = f.read()
                img = img_decode(img_str)
            if img is None:
                try:
                    buf = BytesIO()
                    image = BytesIO(img_str)
                    im = Image.open(image)
                    rgb = im.convert("RGB")
                    rgb.save(buf, "jpeg")
                    buf.seek(0)
                    image_bytes = buf.read()
                    data_base64 = str(base64.b64encode(image_bytes), encoding="utf-8")
                    image_decode = base64.b64decode(data_base64)
                    img_array = np.frombuffer(image_decode, np.uint8)
                    img = cv2.imdecode(img_array, cv2.IMREAD_COLOR)
                except:
                    logger.error("error in loading image:{}".format(image_file))
                    return None, flag_gif, flag_pdf
        if img is None:
            logger.error("error in loading image:{}".format(image_file))
            return None, flag_gif, flag_pdf
    # single channel image array.shape:h,w
    if isinstance(img, np.ndarray) and len(img.shape) == 2:
        img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
    # four channel image array.shape:h,w,c
    if isinstance(img, np.ndarray) and len(img.shape) == 3 and img.shape[2] == 4:
        img = alpha_to_color(img, alpha_color)
    return img, flag_gif, flag_pdf


class PaddleOCR(predict_system.TextSystem):
    def __init__(self, **kwargs):
        """
        paddleocr package
        args:
            **kwargs: other params show in paddleocr --help
        """
        params = parse_args(mMain=False)
        params.__dict__.update(**kwargs)
        assert (
            params.ocr_version in SUPPORT_OCR_MODEL_VERSION
        ), "ocr_version must in {}, but get {}".format(
            SUPPORT_OCR_MODEL_VERSION, params.ocr_version
        )
        params.use_gpu = check_gpu(params.use_gpu)

        if not params.show_log:
            logger.setLevel(logging.INFO)
        self.use_angle_cls = params.use_angle_cls
        lang, det_lang = parse_lang(params.lang)

        # init model dir
        det_model_config = get_model_config("OCR", params.ocr_version, "det", det_lang)
        params.det_model_dir, det_url = confirm_model_dir_url(
            params.det_model_dir,
            os.path.join(BASE_DIR, "whl", "det", det_lang),
            det_model_config["url"],
        )
        rec_model_config = get_model_config("OCR", params.ocr_version, "rec", lang)
        params.rec_model_dir, rec_url = confirm_model_dir_url(
            params.rec_model_dir,
            os.path.join(BASE_DIR, "whl", "rec", lang),
            rec_model_config["url"],
        )
        cls_model_config = get_model_config("OCR", params.ocr_version, "cls", "ch")
        params.cls_model_dir, cls_url = confirm_model_dir_url(
            params.cls_model_dir,
            os.path.join(BASE_DIR, "whl", "cls"),
            cls_model_config["url"],
        )
        if params.ocr_version in ["PP-OCRv3", "PP-OCRv4"]:
            params.rec_image_shape = "3, 48, 320"
        else:
            params.rec_image_shape = "3, 32, 320"
        # download model if using paddle infer
        if not params.use_onnx:
            maybe_download(params.det_model_dir, det_url)
            maybe_download(params.rec_model_dir, rec_url)
            maybe_download(params.cls_model_dir, cls_url)

        if params.det_algorithm not in SUPPORT_DET_MODEL:
            logger.error("det_algorithm must in {}".format(SUPPORT_DET_MODEL))
            sys.exit(0)
        if params.rec_algorithm not in SUPPORT_REC_MODEL:
            logger.error("rec_algorithm must in {}".format(SUPPORT_REC_MODEL))
            sys.exit(0)

        if params.rec_char_dict_path is None:
            params.rec_char_dict_path = str(
                Path(__file__).parent / rec_model_config["dict_path"]
            )

        logger.debug(params)
        # init det_model and rec_model
        super().__init__(params)
        self.page_num = params.page_num

    def ocr(
        self,
        img,
        det=True,
        rec=True,
        cls=True,
        bin=False,
        inv=False,
        alpha_color=(255, 255, 255),
        slice={},
    ):
        """
        OCR with PaddleOCR

        args:
            img: img for OCR, support ndarray, img_path and list or ndarray
            det: use text detection or not. If False, only rec will be exec. Default is True
            rec: use text recognition or not. If False, only det will be exec. Default is True
            cls: use angle classifier or not. Default is True. If True, the text with rotation of 180 degrees can be recognized. If no text is rotated by 180 degrees, use cls=False to get better performance. Text with rotation of 90 or 270 degrees can be recognized even if cls=False.
            bin: binarize image to black and white. Default is False.
            inv: invert image colors. Default is False.
            alpha_color: set RGB color Tuple for transparent parts replacement. Default is pure white.
            slice: use sliding window inference for large images, det and rec must be True. Requires int values for slice["horizontal_stride"], slice["vertical_stride"], slice["merge_x_thres"], slice["merge_y_thres] (See doc/doc_en/slice_en.md). Default is {}.
        """
        assert isinstance(img, (np.ndarray, list, str, bytes))
        if isinstance(img, list) and det == True:
            logger.error("When input a list of images, det must be false")
            exit(0)
        if cls == True and self.use_angle_cls == False:
            logger.warning(
                "Since the angle classifier is not initialized, it will not be used during the forward process"
            )

        img, flag_gif, flag_pdf = check_img(img, alpha_color)
        # for infer pdf file
        if isinstance(img, list) and flag_pdf:
            if self.page_num > len(img) or self.page_num == 0:
                imgs = img
            else:
                imgs = img[: self.page_num]
        else:
            imgs = [img]

        def preprocess_image(_image):
            _image = alpha_to_color(_image, alpha_color)
            if inv:
                _image = cv2.bitwise_not(_image)
            if bin:
                _image = binarize_img(_image)
            return _image

        if det and rec:
            ocr_res = []
            for idx, img in enumerate(imgs):
                img = preprocess_image(img)
                dt_boxes, rec_res, _ = self.__call__(img, cls, slice)
                if not dt_boxes and not rec_res:
                    ocr_res.append(None)
                    continue
                tmp_res = [[box.tolist(), res] for box, res in zip(dt_boxes, rec_res)]
                ocr_res.append(tmp_res)
            return ocr_res
        elif det and not rec:
            ocr_res = []
            for idx, img in enumerate(imgs):
                img = preprocess_image(img)
                dt_boxes, elapse = self.text_detector(img)
                if dt_boxes.size == 0:
                    ocr_res.append(None)
                    continue
                tmp_res = [box.tolist() for box in dt_boxes]
                ocr_res.append(tmp_res)
            return ocr_res
        else:
            ocr_res = []
            cls_res = []
            for idx, img in enumerate(imgs):
                if not isinstance(img, list):
                    img = preprocess_image(img)
                    img = [img]
                if self.use_angle_cls and cls:
                    img, cls_res_tmp, elapse = self.text_classifier(img)
                    if not rec:
                        cls_res.append(cls_res_tmp)
                rec_res, elapse = self.text_recognizer(img)
                ocr_res.append(rec_res)
            if not rec:
                return cls_res
            return ocr_res


class PPStructure(StructureSystem):
    def __init__(self, **kwargs):
        params = parse_args(mMain=False)
        params.__dict__.update(**kwargs)
        assert (
            params.structure_version in SUPPORT_STRUCTURE_MODEL_VERSION
        ), "structure_version must in {}, but get {}".format(
            SUPPORT_STRUCTURE_MODEL_VERSION, params.structure_version
        )
        params.use_gpu = check_gpu(params.use_gpu)
        params.mode = "structure"

        if not params.show_log:
            logger.setLevel(logging.INFO)
        lang, det_lang = parse_lang(params.lang)
        if lang == "ch":
            table_lang = "ch"
        else:
            table_lang = "en"
        if params.structure_version == "PP-Structure":
            params.merge_no_span_structure = False

        # init model dir
        det_model_config = get_model_config("OCR", params.ocr_version, "det", det_lang)
        params.det_model_dir, det_url = confirm_model_dir_url(
            params.det_model_dir,
            os.path.join(BASE_DIR, "whl", "det", det_lang),
            det_model_config["url"],
        )
        rec_model_config = get_model_config("OCR", params.ocr_version, "rec", lang)
        params.rec_model_dir, rec_url = confirm_model_dir_url(
            params.rec_model_dir,
            os.path.join(BASE_DIR, "whl", "rec", lang),
            rec_model_config["url"],
        )
        table_model_config = get_model_config(
            "STRUCTURE", params.structure_version, "table", table_lang
        )
        params.table_model_dir, table_url = confirm_model_dir_url(
            params.table_model_dir,
            os.path.join(BASE_DIR, "whl", "table"),
            table_model_config["url"],
        )
        layout_model_config = get_model_config(
            "STRUCTURE", params.structure_version, "layout", lang
        )
        params.layout_model_dir, layout_url = confirm_model_dir_url(
            params.layout_model_dir,
            os.path.join(BASE_DIR, "whl", "layout"),
            layout_model_config["url"],
        )
        # download model
        if not params.use_onnx:
            maybe_download(params.det_model_dir, det_url)
            maybe_download(params.rec_model_dir, rec_url)
            maybe_download(params.table_model_dir, table_url)
            maybe_download(params.layout_model_dir, layout_url)

        if params.rec_char_dict_path is None:
            params.rec_char_dict_path = str(
                Path(__file__).parent / rec_model_config["dict_path"]
            )
        if params.table_char_dict_path is None:
            params.table_char_dict_path = str(
                Path(__file__).parent / table_model_config["dict_path"]
            )
        if params.layout_dict_path is None:
            params.layout_dict_path = str(
                Path(__file__).parent / layout_model_config["dict_path"]
            )
        logger.debug(params)
        super().__init__(params)

    def __call__(
        self,
        img,
        return_ocr_result_in_table=False,
        img_idx=0,
        alpha_color=(255, 255, 255),
    ):
        img, flag_gif, flag_pdf = check_img(img, alpha_color)
        if isinstance(img, list) and flag_pdf:
            res_list = []
            for index, pdf_img in enumerate(img):
                logger.info("processing {}/{} page:".format(index + 1, len(img)))
                res, _ = super().__call__(
                    pdf_img, return_ocr_result_in_table, img_idx=index
                )
                res_list.append(res)
            return res_list
        res, _ = super().__call__(img, return_ocr_result_in_table, img_idx=img_idx)
        return res


def main():
    # for cmd
    args = parse_args(mMain=True)
    image_dir = args.image_dir
    if is_link(image_dir):
        download_with_progressbar(image_dir, "tmp.jpg")
        image_file_list = ["tmp.jpg"]
    else:
        image_file_list = get_image_file_list(args.image_dir)
    if len(image_file_list) == 0:
        logger.error("no images find in {}".format(args.image_dir))
        return
    if args.type == "ocr":
        engine = PaddleOCR(**(args.__dict__))
    elif args.type == "structure":
        engine = PPStructure(**(args.__dict__))
    else:
        raise NotImplementedError

    for img_path in image_file_list:
        img_name = os.path.basename(img_path).split(".")[0]
        logger.info("{}{}{}".format("*" * 10, img_path, "*" * 10))
        if args.type == "ocr":
            result = engine.ocr(
                img_path,
                det=args.det,
                rec=args.rec,
                cls=args.use_angle_cls,
                bin=args.binarize,
                inv=args.invert,
                alpha_color=args.alphacolor,
            )
            if result is not None:
                lines = []
                for res in result:
                    for line in res:
                        logger.info(line)
                        lines.append(pprint.pformat(line) + "\n")
                if args.savefile:
                    if os.path.exists(args.output) is False:
                        os.mkdir(args.output)
                    outfile = args.output + "/" + img_name + ".txt"
                    with open(outfile, "w", encoding="utf-8") as f:
                        f.writelines(lines)

        elif args.type == "structure":
            img, flag_gif, flag_pdf = check_and_read(img_path)
            if not flag_gif and not flag_pdf:
                img = cv2.imread(img_path)

            if args.recovery and args.use_pdf2docx_api and flag_pdf:
                try_import("pdf2docx")
                from pdf2docx.converter import Converter

                docx_file = os.path.join(args.output, "{}.docx".format(img_name))
                cv = Converter(img_path)
                cv.convert(docx_file)
                cv.close()
                logger.info("docx save to {}".format(docx_file))
                continue

            if not flag_pdf:
                if img is None:
                    logger.error("error in loading image:{}".format(img_path))
                    continue
                img_paths = [[img_path, img]]
            else:
                img_paths = []
                for index, pdf_img in enumerate(img):
                    os.makedirs(os.path.join(args.output, img_name), exist_ok=True)
                    pdf_img_path = os.path.join(
                        args.output, img_name, img_name + "_" + str(index) + ".jpg"
                    )
                    cv2.imwrite(pdf_img_path, pdf_img)
                    img_paths.append([pdf_img_path, pdf_img])

            all_res = []
            for index, (new_img_path, img) in enumerate(img_paths):
                logger.info("processing {}/{} page:".format(index + 1, len(img_paths)))
                result = engine(img, img_idx=index)
                save_structure_res(result, args.output, img_name, index)

                if args.recovery and result != []:
                    from copy import deepcopy
                    from ppstructure.recovery.recovery_to_doc import sorted_layout_boxes

                    h, w, _ = img.shape
                    result_cp = deepcopy(result)
                    result_sorted = sorted_layout_boxes(result_cp, w)
                    all_res += result_sorted

            if args.recovery and all_res != []:
                try:
                    from ppstructure.recovery.recovery_to_doc import convert_info_docx

                    convert_info_docx(img, all_res, args.output, img_name)
                except Exception as ex:
                    logger.error(
                        "error in layout recovery image:{}, err msg: {}".format(
                            img_name, ex
                        )
                    )
                    continue

            for item in all_res:
                item.pop("img")
                item.pop("res")
                logger.info(item)
            logger.info("result save to {}".format(args.output))