# DeepSeek-OCR-WebUI

> Self-hosted, open-source OCR web app and REST API that converts images and PDFs to Markdown using the DeepSeek-OCR-2 model, with 7 modes and batch processing.

- **Category:** OCR
- **Licence:** MIT
- **Latest version:** v4.1
- **Open source:** oss
- **Languages:** Typescript, Python, HTML
- **Platforms:** Docker, Docker Compose, Linux, macOS
- **Tags:** Markdown, Mcp, Pytorch, Vue3, PDF, Ocr, Deepseek, Responsive Design, Batch Processing, Python, Fastapi, Computer vision, Web Ui, Modern Ui, Vllm, Apple silicon, Image recognition, Vision Model, Document Parsing, GPU Inference, Image To Text, Chart Parsing

## Description

DeepSeek-OCR-WebUI wraps the DeepSeek-OCR-2 vision model in a browser-based document recognition app with a REST API. Uploaded images and PDFs can be processed in seven modes: document-to-Markdown, general OCR, plain text, chart and formula parsing, image description, find-and-locate with bounding-box annotation, and a custom prompt mode. The Vue 3 interface adds a page sidebar with thumbnails and reordering, a real-time processing queue, health monitoring, and a four-language UI (English, Simplified and Traditional Chinese, Japanese). The FastAPI backend exposes /ocr, /ocr-pdf, /pdf-to-images and /health endpoints, and a bundled Model Context Protocol server lets AI assistants call the OCR service. To self-host, run the all-in-one Docker image (GPU recommended; the model is pre-downloaded inside the image) or install natively on Linux or Apple Silicon Macs with conda/pip and start.sh. CPU-only Docker is supported but described as very slow; the docs list a minimum of a 16GB+ VRAM NVIDIA GPU, 16GB RAM, 50GB disk and CUDA 11.8+.

## Links

- [Homepage](https://github.com/neosun100/deepseek-ocr-webui)
- [Website](https://github.com/neosun100/DeepSeek-OCR-WebUI)
- [Docker](neosun/deepseek-ocr)
- [GitHub repository](https://github.com/neosun100/DeepSeek-OCR-WebUI)

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Source: https://selfhost.directory/project/deepseek-ocr-webui