Merge pull request #1276 from icecraft/fix/remove_demo

fix: remove deprecated code

demo/demo.py

-import os
-
-from loguru import logger
-
-from magic_pdf.data.data_reader_writer import FileBasedDataWriter
-from magic_pdf.pipe.UNIPipe import UNIPipe
-
-try:
-    current_script_dir = os.path.dirname(os.path.abspath(__file__))
-    demo_name = 'demo1'
-    pdf_path = os.path.join(current_script_dir, f'{demo_name}.pdf')
-    pdf_bytes = open(pdf_path, 'rb').read()
-    jso_useful_key = {'_pdf_type': '', 'model_list': []}
-    local_image_dir = os.path.join(current_script_dir, 'images')
-    image_dir = str(os.path.basename(local_image_dir))
-    image_writer = FileBasedDataWriter(local_image_dir)
-    pipe = UNIPipe(pdf_bytes, jso_useful_key, image_writer)
-    pipe.pipe_classify()
-    pipe.pipe_analyze()
-    pipe.pipe_parse()
-    md_content = pipe.pipe_mk_markdown(image_dir, drop_mode='none')
-    with open(f'{demo_name}.md', 'w', encoding='utf-8') as f:
-        f.write(md_content)
-except Exception as e:
-    logger.exception(e)

demo/magic_pdf_parse_main.py

-import copy
-import json
-import os
-
-from loguru import logger
-
-from magic_pdf.data.data_reader_writer import FileBasedDataWriter
-from magic_pdf.libs.draw_bbox import draw_layout_bbox, draw_span_bbox
-from magic_pdf.pipe.OCRPipe import OCRPipe
-from magic_pdf.pipe.TXTPipe import TXTPipe
-from magic_pdf.pipe.UNIPipe import UNIPipe
-
-# todo: 设备类型选择 （？）
-
-
-def json_md_dump(
-        pipe,
-        md_writer,
-        pdf_name,
-        content_list,
-        md_content,
-        orig_model_list,
-):
-    # 写入模型结果到 model.json
-
-    md_writer.write_string(
-        f'{pdf_name}_model.json',
-        json.dumps(orig_model_list, ensure_ascii=False, indent=4)
-    )
-
-    # 写入中间结果到 middle.json
-    md_writer.write_string(
-        f'{pdf_name}_middle.json',
-        json.dumps(pipe.pdf_mid_data, ensure_ascii=False, indent=4)
-    )
-
-    # text文本结果写入到 conent_list.json
-    md_writer.write_string(
-        f'{pdf_name}_content_list.json',
-        json.dumps(content_list, ensure_ascii=False, indent=4)
-    )
-
-    # 写入结果到 .md 文件中
-    md_writer.write_string(
-        f'{pdf_name}.md',
-        md_content,
-    )
-
-
-# 可视化
-def draw_visualization_bbox(pdf_info, pdf_bytes, local_md_dir, pdf_file_name):
-    # 画布局框，附带排序结果
-    draw_layout_bbox(pdf_info, pdf_bytes, local_md_dir, pdf_file_name)
-    # 画 span 框
-    draw_span_bbox(pdf_info, pdf_bytes, local_md_dir, pdf_file_name)
-
-
-def pdf_parse_main(
-        pdf_path: str,
-        parse_method: str = 'auto',
-        model_json_path: str = None,
-        is_json_md_dump: bool = True,
-        is_draw_visualization_bbox: bool = True,
-        output_dir: str = None
-):
-    """执行从 pdf 转换到 json、md 的过程，输出 md 和 json 文件到 pdf 文件所在的目录.
-
-    :param pdf_path: .pdf 文件的路径，可以是相对路径，也可以是绝对路径
-    :param parse_method: 解析方法， 共 auto、ocr、txt 三种，默认 auto，如果效果不好，可以尝试 ocr
-    :param model_json_path: 已经存在的模型数据文件，如果为空则使用内置模型，pdf 和 model_json 务必对应
-    :param is_json_md_dump: 是否将解析后的数据写入到 .json 和 .md 文件中，默认 True，会将不同阶段的数据写入到不同的 .json 文件中（共3个.json文件），md内容会保存到 .md 文件中
-    :param is_draw_visualization_bbox: 是否绘制可视化边界框，默认 True，会生成布局框和 span 框的图像
-    :param output_dir: 输出结果的目录地址，会生成一个以 pdf 文件名命名的文件夹并保存所有结果
-    """
-    try:
-        pdf_name = os.path.basename(pdf_path).split('.')[0]
-        pdf_path_parent = os.path.dirname(pdf_path)
-
-        if output_dir:
-            output_path = os.path.join(output_dir, pdf_name)
-        else:
-            output_path = os.path.join(pdf_path_parent, pdf_name)
-
-        output_image_path = os.path.join(output_path, 'images')
-
-        # 获取图片的父路径，为的是以相对路径保存到 .md 和 conent_list.json 文件中
-        image_path_parent = os.path.basename(output_image_path)
-
-        pdf_bytes = open(pdf_path, 'rb').read()  # 读取 pdf 文件的二进制数据
-
-        orig_model_list = []
-
-        if model_json_path:
-            # 读取已经被模型解析后的pdf文件的 json 原始数据，list 类型
-            model_json = json.loads(open(model_json_path, 'r', encoding='utf-8').read())
-            orig_model_list = copy.deepcopy(model_json)
-        else:
-            model_json = []
-
-        # 执行解析步骤
-        image_writer, md_writer = FileBasedDataWriter(output_image_path), FileBasedDataWriter(output_path)
-
-        # 选择解析方式
-        if parse_method == 'auto':
-            jso_useful_key = {'_pdf_type': '', 'model_list': model_json}
-            pipe = UNIPipe(pdf_bytes, jso_useful_key, image_writer)
-        elif parse_method == 'txt':
-            pipe = TXTPipe(pdf_bytes, model_json, image_writer)
-        elif parse_method == 'ocr':
-            pipe = OCRPipe(pdf_bytes, model_json, image_writer)
-        else:
-            logger.error('unknown parse method, only auto, ocr, txt allowed')
-            exit(1)
-
-        # 执行分类
-        pipe.pipe_classify()
-
-        # 如果没有传入模型数据，则使用内置模型解析
-        if len(model_json) == 0:
-            pipe.pipe_analyze()  # 解析
-            orig_model_list = copy.deepcopy(pipe.model_list)
-
-        # 执行解析
-        pipe.pipe_parse()
-
-        # 保存 text 和 md 格式的结果
-        content_list = pipe.pipe_mk_uni_format(image_path_parent, drop_mode='none')
-        md_content = pipe.pipe_mk_markdown(image_path_parent, drop_mode='none')
-
-        if is_json_md_dump:
-            json_md_dump(pipe, md_writer, pdf_name, content_list, md_content, orig_model_list)
-
-        if is_draw_visualization_bbox:
-            draw_visualization_bbox(pipe.pdf_mid_data['pdf_info'], pdf_bytes, output_path, pdf_name)
-
-    except Exception as e:
-        logger.exception(e)
-
-
-# 测试
-if __name__ == '__main__':
-    current_script_dir = os.path.dirname(os.path.abspath(__file__))
-    demo_names = ['demo1', 'demo2', 'small_ocr']
-    for name in demo_names:
-        file_path = os.path.join(current_script_dir, f'{name}.pdf')
-        pdf_parse_main(file_path)