使用大模型处置惩罚文档时,必要对二进制格式的文档进转剖析提取文字和图片,本文使用 pymupdf 开源库,对 PDF 举行剖析提取文字和图片。
安装依赖
首先安装 pymupdf 依赖
- pymupdf4llm==0.0.17
- pymupdf==1.24.10
- apscheduler==3.10.4
复制代码 PDF 转 Markdown
pymupdf 将 PDF 转换为 markdown,传入 pdf 路径举行处置惩罚。
- def convert_to_md(pdf_path):
- return pymupdf4llm.to_markdown(pdf_path)
复制代码 PDF 中提取图片
传入 PDF 路径,保存图片,并返回路径列表。
- def extract_image(pdf_path):
- doc = pymupdf.open(pdf_path) # open a document
- image_path_list = []
- rad_prefix = ''.join(random.choices(string.ascii_letters, k=5))
- Path(f"images/{rad_prefix}").mkdir(parents=True)
- for page_index in range(len(doc)): # iterate over pdf pages
- page = doc[page_index] # get the page
- image_list = page.get_images()
- # print the number of images found on the page
- if image_list:
- print(f"Found {len(image_list)} images on page {page_index}")
- else:
- print("No images found on page", page_index)
-
- for image_index, img in enumerate(image_list, start=1): # enumerate the image list
- xref = img[0] # get the XREF of the image
- pix = pymupdf.Pixmap(doc, xref) # create a Pixmap
- if pix.n - pix.alpha > 3: # CMYK: convert to RGB first
- pix = pymupdf.Pixmap(pymupdf.csRGB, pix)
-
- image_path = Path("images/%s/page_%s-image_%s.png" % (rad_prefix,page_index, image_index)).absolute()
- image_path_list.append(image_path)
- pix.pil_save(image_path) # save the image as png
- pix = None
- return image_path_list
复制代码 可视化
通过 Gradio 可视化 PDF 转换。
- import gradio as gr
- import pdf
- def covnert_pdf(x):
- print(x)
- md_content = pdf.convert_to_md(x)
- image_list = pdf.extract_image(x)
- return [md_content , image_list]
- with gr.Blocks() as demo:
- gr.Markdown(
- value="# PDF 提取"
- )
- with gr.Tab("Markdown"):
- md = gr.Markdown(
- height=500
- )
- with gr.Tab("Images"):
- gallery = gr.Gallery(columns=4, object_fit="None", height="auto", show_download_button=True)
- with gr.Row():
- go_btn = gr.UploadButton()
- go_btn.upload(covnert_pdf, go_btn, [md, gallery])
- from apscheduler.schedulers.background import BackgroundScheduler
- demo.launch()
复制代码
总结
pymupdf 转 markdown 的结果还是不错的,可以到 Modelscope 的空间举行体验。https://modelscope.cn/studios/model1001/pdf_converter
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