title = """# 🙋🏻‍♂️Welcome to Tonic's🫴🏻📸GOT-OCR
---
"""

description = """
The **GOT-OCR model** is a cutting-edge OCR system with **580M parameters**, designed to process a wide range of "characters." Equipped with a **high-compression encoder** and a **long-context decoder**, it excels in both scene and document-style images. The model supports **multi-page** and **dynamic resolution OCR**, enhancing its versatility.

### Key Features

- **Plain Text OCR**: Extracts text from images.
- **Formatted Text OCR**: Retains the original formatting, including tables and formulas.
- **Fine-grained OCR**: Offers box-based and color-based OCR for precision in specific regions.
- **Multi-crop OCR**: Handles multiple cropped sections within an image.

## Supported Content Types

- Plain text
- Math/molecular formulas
- Tables and charts
- Sheet music
- Geometric shapes

## How to Use

1. Select a task from the dropdown menu.
2. Upload an image.
3. (Optional) Adjust parameters based on the selected task.
4. Click **Process** to view the results.
"""
joinus = """---
### Join us :

🌟TeamTonic🌟 is always making cool demos! Join our active builder's 🛠️community 👻 [![Join us on Discord](https://img.shields.io/discord/1109943800132010065?label=Discord&logo=discord&style=flat-square)](https://discord.gg/qdfnvSPcqP) On 🤗Huggingface:[MultiTransformer](https://huggingface.co/MultiTransformer) On 🌐Github: [Tonic-AI](https://github.com/tonic-ai) & contribute to🌟 [Build Tonic](https://git.tonic-ai.com/contribute)🤗Big thanks to Yuvi Sharma and all the folks at huggingface for the community grant 🤗
"""
modelinfor = """---

### Model Information

- **Model Name**: GOT-OCR 2.0
- **Hugging Face Repository**: [ucaslcl/GOT-OCR2_0](https://huggingface.co/ucaslcl/GOT-OCR2_0)
- **Environment**: CUDA 11.8 + PyTorch 2.0.1
"""

tasks = [
    "Plain Text OCR",
    "Format Text OCR",
    "Fine-grained OCR (Box)",
    "Fine-grained OCR (Color)",
    "Multi-crop OCR",
    "Render Formatted OCR"
]

ocr_types = ["ocr", "format"]
ocr_colors = ["red", "green", "blue"]