MinerU/magic_pdf/pipeline.bak

# coding=utf8
import sys
import time
from urllib.parse import quote

from magic_pdf.libs.commons import (
    read_file,
    join_path,
    parse_bucket_key,
    formatted_time,
    s3_image_save_path,
)
from magic_pdf.libs.drop_reason import DropReason
from magic_pdf.libs.json_compressor import JsonCompressor
from magic_pdf.dict2md.mkcontent import mk_universal_format
from magic_pdf.pdf_parse_by_txt import parse_pdf_by_txt
from magic_pdf.filter.pdf_classify_by_type import classify
from magic_pdf.filter.pdf_meta_scan import pdf_meta_scan
from loguru import logger

from magic_pdf.pdf_parse_for_train import parse_pdf_for_train
from magic_pdf.spark.base import exception_handler, get_data_source
from magic_pdf.train_utils.convert_to_train_format import convert_to_train_format
from magic_pdf.spark.s3 import get_s3_config



def meta_scan(jso: dict, doc_layout_check=True) -> dict:
    s3_pdf_path = jso.get("file_location")
    s3_config = get_s3_config(s3_pdf_path)
    if doc_layout_check:
        if (
            "doc_layout_result" not in jso
        ):  # 检测json中是存在模型数据，如果没有则需要跳过该pdf
            jso["_need_drop"] = True
            jso["_drop_reason"] = DropReason.MISS_DOC_LAYOUT_RESULT
            return jso
    try:
        data_source = get_data_source(jso)
        file_id = jso.get("file_id")
        book_name = f"{data_source}/{file_id}"

        # 首页存在超量drawing问题
        # special_pdf_list = ['zlib/zlib_21822650']
        # if book_name in special_pdf_list:
        #     jso['need_drop'] = True
        #     jso['drop_reason'] = DropReason.SPECIAL_PDF
        #     return jso

        start_time = time.time()  # 记录开始时间
        logger.info(
            f"book_name is:{book_name},start_time is:{formatted_time(start_time)}",
            file=sys.stderr,
        )
        file_content = read_file(s3_pdf_path, s3_config)
        read_file_time = int(time.time() - start_time)  # 计算执行时间

        start_time = time.time()  # 记录开始时间
        res = pdf_meta_scan(s3_pdf_path, file_content)
        if res.get(
            "_need_drop", False
        ):  # 如果返回的字典里有need_drop，则提取drop_reason并跳过本次解析
            jso["_need_drop"] = True
            jso["_drop_reason"] = res["_drop_reason"]
        else:  # 正常返回
            jso["pdf_meta"] = res
            jso["content"] = ""
            jso["remark"] = ""
            jso["data_url"] = ""
        end_time = time.time()  # 记录结束时间
        meta_scan_time = int(end_time - start_time)  # 计算执行时间
        logger.info(
            f"book_name is:{book_name},end_time is:{formatted_time(end_time)},read_file_time is:{read_file_time},meta_scan_time is:{meta_scan_time}",
            file=sys.stderr,
        )
        jso["read_file_time"] = read_file_time
        jso["meta_scan_time"] = meta_scan_time
    except Exception as e:
        jso = exception_handler(jso, e)
    return jso


def classify_by_type(jso: dict, debug_mode=False) -> dict:
    # 检测debug开关
    if debug_mode:
        pass
    else:  # 如果debug没开，则检测是否有needdrop字段
        if jso.get("_need_drop", False):
            return jso
    # 开始正式逻辑
    try:
        pdf_meta = jso.get("pdf_meta")
        data_source = get_data_source(jso)
        file_id = jso.get("file_id")
        book_name = f"{data_source}/{file_id}"
        total_page = pdf_meta["total_page"]
        page_width = pdf_meta["page_width_pts"]
        page_height = pdf_meta["page_height_pts"]
        img_sz_list = pdf_meta["image_info_per_page"]
        img_num_list = pdf_meta["imgs_per_page"]
        text_len_list = pdf_meta["text_len_per_page"]
        text_layout_list = pdf_meta["text_layout_per_page"]
        text_language = pdf_meta["text_language"]
        # allow_language = ['zh', 'en']  # 允许的语言,目前只允许简中和英文的

        # if text_language not in allow_language:  # 如果语言不在允许的语言中，则drop
        #     jso['need_drop'] = True
        #     jso['drop_reason'] = DropReason.NOT_ALLOW_LANGUAGE
        #     return jso
        pdf_path = pdf_meta["pdf_path"]
        is_encrypted = pdf_meta["is_encrypted"]
        is_needs_password = pdf_meta["is_needs_password"]
        if (
            is_encrypted or is_needs_password
        ):  # 加密的，需要密码的，没有页面的，都不处理
            jso["_need_drop"] = True
            jso["_drop_reason"] = DropReason.ENCRYPTED
        else:
            start_time = time.time()  # 记录开始时间
            is_text_pdf, results = classify(
                pdf_path,
                total_page,
                page_width,
                page_height,
                img_sz_list,
                text_len_list,
                img_num_list,
                text_layout_list,
            )
            classify_time = int(time.time() - start_time)  # 计算执行时间
            if is_text_pdf:
                pdf_meta["is_text_pdf"] = is_text_pdf
                jso["_pdf_type"] = "TXT"
                jso["pdf_meta"] = pdf_meta
                jso["classify_time"] = classify_time
                # print(json.dumps(pdf_meta, ensure_ascii=False))

                allow_language = ["zh", "en"]  # 允许的语言,目前只允许简中和英文的
                if (
                    text_language not in allow_language
                ):  # 如果语言不在允许的语言中，则drop
                    jso["_need_drop"] = True
                    jso["_drop_reason"] = DropReason.NOT_ALLOW_LANGUAGE
                    return jso
            else:
                # 先不drop
                pdf_meta["is_text_pdf"] = is_text_pdf
                jso["_pdf_type"] = "OCR"
                jso["pdf_meta"] = pdf_meta
                jso["classify_time"] = classify_time
                # jso["_need_drop"] = True
                # jso["_drop_reason"] = DropReason.NOT_IS_TEXT_PDF
                extra_info = {"classify_rules": []}
                for condition, result in results.items():
                    if not result:
                        extra_info["classify_rules"].append(condition)
                jso["extra_info"] = extra_info

    except Exception as e:
        jso = exception_handler(jso, e)
    return jso


def drop_needdrop_pdf(jso: dict) -> dict:
    if jso.get("_need_drop", False):
        logger.info(
            f"book_name is:{get_data_source(jso)}/{jso['file_id']} need drop",
            file=sys.stderr,
        )
        jso["dropped"] = True
    return jso


def pdf_intermediate_dict_to_markdown(jso: dict, debug_mode=False) -> dict:

    if debug_mode:
        pass
    else:  # 如果debug没开，则检测是否有needdrop字段
        if jso.get("_need_drop", False):
            book_name = join_path(get_data_source(jso), jso["file_id"])
            logger.info(f"book_name is:{book_name} need drop", file=sys.stderr)
            jso["dropped"] = True
            return jso
    try:
        pdf_intermediate_dict = jso["pdf_intermediate_dict"]
        # 将 pdf_intermediate_dict 解压
        pdf_intermediate_dict = JsonCompressor.decompress_json(pdf_intermediate_dict)
        # markdown_content = mk_nlp_markdown(pdf_intermediate_dict)
        jso["content_list"] = mk_universal_format(pdf_intermediate_dict)
        # jso["content"] = markdown_content
        logger.info(f"book_name is:{get_data_source(jso)}/{jso['file_id']}")
        # 把无用的信息清空
        jso["doc_layout_result"] = ""
        jso["pdf_intermediate_dict"] = ""
        jso["pdf_meta"] = ""
    except Exception as e:
        jso = exception_handler(jso, e)
    return jso


def parse_pdf(jso: dict, start_page_id=0, debug_mode=False) -> dict:
    # 检测debug开关
    if debug_mode:
        pass
    else:  # 如果debug没开，则检测是否有needdrop字段
        if jso.get("_need_drop", False):
            return jso
    # 开始正式逻辑
    s3_pdf_path = jso.get("file_location")
    s3_config = get_s3_config(s3_pdf_path)
    pdf_bytes = read_file(s3_pdf_path, s3_config)
    model_output_json_list = jso.get("doc_layout_result")
    data_source = get_data_source(jso)
    file_id = jso.get("file_id")
    book_name = f"{data_source}/{file_id}"

    junk_img_bojids = jso["pdf_meta"]["junk_img_bojids"]

    # 增加检测 max_svgs 数量的检测逻辑，如果 max_svgs 超过3000则drop
    svgs_per_page_list = jso["pdf_meta"]["svgs_per_page"]
    max_svgs = max(svgs_per_page_list)
    if max_svgs > 3000:
        jso["_need_drop"] = True
        jso["_drop_reason"] = DropReason.HIGH_COMPUTATIONAL_lOAD_BY_SVGS
    else:
        try:
            save_path = s3_image_save_path
            image_s3_config = get_s3_config(save_path)
            start_time = time.time()  # 记录开始时间
            # 先打印一下book_name和解析开始的时间
            logger.info(
                f"book_name is:{book_name},start_time is:{formatted_time(start_time)}",
                file=sys.stderr,
            )
            pdf_info_dict = parse_pdf_by_txt(
                pdf_bytes,
                model_output_json_list,
                save_path,
                book_name,
                pdf_model_profile=None,
                image_s3_config=image_s3_config,
                start_page_id=start_page_id,
                junk_img_bojids=junk_img_bojids,
                debug_mode=debug_mode,
            )
            if pdf_info_dict.get(
                "_need_drop", False
            ):  # 如果返回的字典里有need_drop，则提取drop_reason并跳过本次解析
                jso["_need_drop"] = True
                jso["_drop_reason"] = pdf_info_dict["_drop_reason"]
            else:  # 正常返回，将 pdf_info_dict 压缩并存储
                pdf_info_dict = JsonCompressor.compress_json(pdf_info_dict)
                jso["pdf_intermediate_dict"] = pdf_info_dict
            end_time = time.time()  # 记录完成时间
            parse_time = int(end_time - start_time)  # 计算执行时间
            # 解析完成后打印一下book_name和耗时
            logger.info(
                f"book_name is:{book_name},end_time is:{formatted_time(end_time)},cost_time is:{parse_time}",
                file=sys.stderr,
            )
            jso["parse_time"] = parse_time
        except Exception as e:
            jso = exception_handler(jso, e)
    return jso


def parse_pdf_for_model_train(jso: dict, start_page_id=0, debug_mode=False) -> dict:
    # 检测debug开关
    if debug_mode:
        pass
    else:  # 如果debug没开，则检测是否有needdrop字段
        if jso.get("_need_drop", False):
            return jso
    # 开始正式逻辑
    s3_pdf_path = jso.get("file_location")
    s3_config = get_s3_config(s3_pdf_path)
    model_output_json_list = jso.get("doc_layout_result")
    data_source = get_data_source(jso)
    file_id = jso.get("file_id")
    book_name = f"{data_source}/{file_id}"

    # 1.23.22已修复
    # if debug_mode:
    #     pass
    # else:
    #     if book_name == "zlib/zlib_21929367":
    #         jso['need_drop'] = True
    #         jso['drop_reason'] = DropReason.SPECIAL_PDF
    #         return jso

    junk_img_bojids = jso["pdf_meta"]["junk_img_bojids"]
    # total_page = jso['pdf_meta']['total_page']

    # 增加检测 max_svgs 数量的检测逻辑，如果 max_svgs 超过3000则drop
    svgs_per_page_list = jso["pdf_meta"]["svgs_per_page"]
    max_svgs = max(svgs_per_page_list)
    if max_svgs > 3000:
        jso["_need_drop"] = True
        jso["_drop_reason"] = DropReason.HIGH_COMPUTATIONAL_lOAD_BY_SVGS
    # elif total_page > 1000:
    #     jso['need_drop'] = True
    #     jso['drop_reason'] = DropReason.HIGH_COMPUTATIONAL_lOAD_BY_TOTAL_PAGES
    else:
        try:
            save_path = s3_image_save_path
            image_s3_config = get_s3_config(save_path)
            start_time = time.time()  # 记录开始时间
            # 先打印一下book_name和解析开始的时间
            logger.info(
                f"book_name is:{book_name},start_time is:{formatted_time(start_time)}",
                file=sys.stderr,
            )
            pdf_info_dict = parse_pdf_for_train(
                s3_pdf_path,
                s3_config,
                model_output_json_list,
                save_path,
                book_name,
                pdf_model_profile=None,
                image_s3_config=image_s3_config,
                start_page_id=start_page_id,
                junk_img_bojids=junk_img_bojids,
                debug_mode=debug_mode,
            )
            if pdf_info_dict.get(
                "_need_drop", False
            ):  # 如果返回的字典里有need_drop，则提取drop_reason并跳过本次解析
                jso["_need_drop"] = True
                jso["_drop_reason"] = pdf_info_dict["_drop_reason"]
            else:  # 正常返回，将 pdf_info_dict 压缩并存储
                jso["parsed_results"] = convert_to_train_format(pdf_info_dict)
                pdf_info_dict = JsonCompressor.compress_json(pdf_info_dict)
                jso["pdf_intermediate_dict"] = pdf_info_dict
            end_time = time.time()  # 记录完成时间
            parse_time = int(end_time - start_time)  # 计算执行时间
            # 解析完成后打印一下book_name和耗时
            logger.info(
                f"book_name is:{book_name},end_time is:{formatted_time(end_time)},cost_time is:{parse_time}",
                file=sys.stderr,
            )
            jso["parse_time"] = parse_time
        except Exception as e:
            jso = exception_handler(jso, e)
    return jso


"""
统一处理逻辑
1.先调用parse_pdf对文本类pdf进行处理
2.再调用ocr_dropped_parse_pdf,对之前drop的pdf进行处理
"""

# def uni_parse_pdf(jso: dict, start_page_id=0, debug_mode=False) -> dict:
#     jso = parse_pdf(jso, start_page_id=start_page_id, debug_mode=debug_mode)
#     jso = ocr_dropped_parse_pdf(jso, start_page_id=start_page_id, debug_mode=debug_mode)
#     return jso


if __name__ == "__main__":
    pass