pdf-craft vs e2m
PDF and media-to-Markdown projects compared
pdf-craft and e2m are Python projects that turn source material into Markdown. pdf-craft focuses on OCR and publication workflows for scanned PDFs, while e2m handles a wider range of documents, web pages, and audio through configurable parsers.
pdf-craft: Convert Scanned PDFs with DeepSeek OCR
PDF Craft is a Python library and online service for turning scanned books, research papers, and technical documents into editable Markdown or reader-friendly EPUB. Built around DeepSeek OCR, it also supports translation and translated PDF output.
e2m: Convert Documents and Media into Markdown
E2M is a Python library for parsing documents, web pages, and audio into Markdown through configurable parser and converter components. It is aimed at developers preparing varied source material for RAG, training data, or downstream text workflows.
| pdf-craft | e2m | |
|---|---|---|
| Language | Python | Jupyter Notebook |
| License | MIT | Apache-2.0 |
| Stars | 6.4k | 1.3k |
| Forks | 466 | 76 |
| Last analyzed | Oct 18, 2026 | Oct 3, 2026 |
Key differences
- pdf-craft targets scanned PDFs, with OCR workflows for Markdown, EPUB, translation, and translated PDF output; e2m parses PDFs alongside office files, EPUBs, web pages, and audio.
- pdf-craft emphasizes books and academic or technical documents, including metadata and tables of contents for EPUBs; e2m emphasizes configurable extraction for RAG, training data, and downstream text workflows.
- pdf-craft supports remote OCR or local execution, with local OCR requiring suitable NVIDIA and CUDA setup; e2m offers format-specific parser engines, some of which may require separate tools, models, or credentials.
- pdf-craft is identified as Python and MIT-licensed; e2m is identified as Jupyter Notebook, and its repository metadata says Apache-2.0 while its README says MIT.
- The supplied project facts list 6.3k stars and 460 forks for pdf-craft, compared with 1.3k stars and 76 forks for e2m.
Choose pdf-craft if you…
- need to turn scanned books or technical documents into Markdown or EPUB.
- want OCR, translation, or translated PDF workflows for scanned material.
- need synchronous or asynchronous Python APIs and reusable `.pcex` extraction results.
Choose e2m if you…
- need to parse varied sources such as office files, URLs, presentations, and audio into Markdown.
- want to select parser engines and configure integrated parsers and converters through YAML.
- are preparing mixed content for RAG, model training, or fine-tuning workflows.
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This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.