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🖥 PDF CRAFT-a python library for converting PDF (primarily scanned books) in Markdown and EPUB using local AI models and LLM to structure the contents
Github

Basic possibilities

- extracting text and layout
Uses the combination of Doclayout-Yolo and its own algorithms for detecting and filtering headlines, columns, footnotes and page numbers

- Local OCR
Recognizes the text on the page via Onnxocr, supports acceleration on GPU (CUDA)

- Determining the order of reading
With the help of LayoutReader, it builds a flow of text in the order in which it is perceived by a person

- Converting in Markdown
Generates .MD with relative links to images (illustrations, tables, formulas) in the Assets folder

Installation and requirements
Python ≥ 3.10 (recommended 3.10.16).

Pip Install PDF-Craft and PIP Install Onnxruntime == 1.21.0 (or Onnxruntime-GPU == 1.21.0 for CUDA).

For an EPUB conveier, you need access to the LLM service (for example, Deepseek).

🟡 Github


#پایتون #Python #library

🆔 @Python4all_pro



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🖥 PDF CRAFT-a python library for converting PDF (primarily scanned books) in Markdown and EPUB using local AI models and LLM to structure the contents
Github

Basic possibilities

- extracting text and layout
Uses the combination of Doclayout-Yolo and its own algorithms for detecting and filtering headlines, columns, footnotes and page numbers

- Local OCR
Recognizes the text on the page via Onnxocr, supports acceleration on GPU (CUDA)

- Determining the order of reading
With the help of LayoutReader, it builds a flow of text in the order in which it is perceived by a person

- Converting in Markdown
Generates .MD with relative links to images (illustrations, tables, formulas) in the Assets folder

Installation and requirements
Python ≥ 3.10 (recommended 3.10.16).

Pip Install PDF-Craft and PIP Install Onnxruntime == 1.21.0 (or Onnxruntime-GPU == 1.21.0 for CUDA).

For an EPUB conveier, you need access to the LLM service (for example, Deepseek).

🟡 Github


#پایتون #Python #library

🆔 @Python4all_pro

BY پایتون ( Machine Learning | Data Science )


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Dump Scam in Leaked Telegram Chat

A leaked Telegram discussion by 50 so-called crypto influencers has exposed the extraordinary steps they take in order to profit on the back off unsuspecting defi investors. According to a leaked screenshot of the chat, an elaborate plan to defraud defi investors using the worthless “$Few” tokens had been hatched. $Few tokens would be airdropped to some of the influencers who in turn promoted these to unsuspecting followers on Twitter.

In many cases, the content resembled that of the marketplaces found on the dark web, a group of hidden websites that are popular among hackers and accessed using specific anonymising software.“We have recently been witnessing a 100 per cent-plus rise in Telegram usage by cybercriminals,” said Tal Samra, cyber threat analyst at Cyberint.The rise in nefarious activity comes as users flocked to the encrypted chat app earlier this year after changes to the privacy policy of Facebook-owned rival WhatsApp prompted many to seek out alternatives.پایتون Machine Learning | Data Science from jp


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