README.md

---
title: OCRapi
emoji: 🐠
colorFrom: gray
colorTo: indigo
sdk: gradio
sdk_version: 5.49.1
app_file: app.py
pinned: false
---

## PDF OCR Space (PaddleOCR + PyMuPDF)

Gradio Space that extracts text from uploaded PDFs. Each page is rendered with PyMuPDF and recognized by PaddleOCR.

### Features
- Upload a PDF and extract text
- Adjustable DPI and optional page limit
- Multi-language OCR (via PaddleOCR language packs)
- JSON output including bboxes and confidences per page

### App Structure
- `app.py`: Gradio UI and prediction logic
- `requirements.txt`: Python dependencies
- `runtime.txt`: Python runtime for Hugging Face Spaces

### Deploy on Hugging Face Spaces
1. Create a new Space (SDK: Gradio, Python).
2. Upload all files in this repo: `app.py`, `requirements.txt`, `runtime.txt`, `README.md`.
3. First build will download OCR models; subsequent runs are cached.

### Run Locally
```bash
pip install -r requirements.txt
python app.py
```
Then open `http://127.0.0.1:7860`.

### API Usage

Using `gradio_client` in Python:
```python
from gradio_client import Client

client = Client("<your-username>/<your-space-name>")
result = client.predict(
    pdf_file=("file", "./sample.pdf"),
    dpi=170,
    max_pages=None,
    lang="en",
    api_name="predict"
)

text, json_payload = result
print(text)
print(json_payload)
```

Using Spaces Inference API (curl):
```bash
curl -s -X POST \
  -F "data=@sample.pdf" \
  -F "data=170" \
  -F "data=" \
  -F "data=en" \
  https://<your-username>-<your-space-name>.hf.space/run/predict
```

Notes:
- Increase DPI for small text, but it will be slower.
- Choose the appropriate language model; defaults to `en`.

### License
MIT




Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference