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# PDF2Markdown | |
**Demo:(left: input image; right: rendered markdown.)** | |
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1. Extract PDF features by these tasks: | |
- Layout Detection: Using the YOLOv8 model for region detection, such as images, tables, titles, text, etc.; | |
- Formula Detection: Using YOLOv8 for detecting formulas, including inline formulas and isolated formulas; | |
- Formula Recognition: Using UniMERNet for formula recognition; | |
- Table Recognition: Using StructEqTable for table recognition; | |
- Optical Character Recognition: Using PaddleOCR for text recognition; | |
2. Convert features to markdown file: | |
Using simple rules to convert the identified result to markdown (*Note: this is a simply convert code and can only support one-column PDFs, see [MinerU](https://github.com/opendatalab/MinerU) for more complex situation*). | |
# Usage | |
``` | |
python project/pdf2markdown/scripts/run_project.py --config project/pdf2markdown/configs/pdf2markdown.yaml | |
``` | |