semvec/pypi-packages huggingface dataset:
mb-capcha-ocr 0.1.5
An pytorch ocr base library for MBBank lib
License: MIT

# OCR Model Training and Prediction

This project is designed to train and use an Optical Character Recognition (OCR) model for recognizing characters in
CAPTCHA images.

## Project Structure

- `mb_capcha_ocr/`: Contains the core OCR model and prediction logic.
- `train_model/`: Contains the training script for the OCR model.

## Installation and Setup for Training

1. Clone the repository:
    ```sh
    git clone https://github.com/thedtvn/mbbank-capcha-ocr
    cd mbbank-capcha-ocr
    cd train_model
    ```

2. Create and activate a virtual environment:
    ```sh
    python -m venv .venv
    source .venv/bin/activate  # On Windows use `.venv\Scripts\activate`
    ```

3. Install the required dependencies:
    ```sh
    pip install -r train_requirements.txt
    ```

## Training the Model

1. Place your training and testing images in the `dataset/` directory. The images should be named in the format
   `{label}.(png|jpg|jpeg)`.

2. Run the training script:
    ```sh
    python train.py
    ```

3. The trained model will be saved as `model.onnx` in the directory.

## Using the Model for Prediction

```python
from PIL import Image
from mb_capcha_ocr import OcrModel

model = OcrModel()  # model_path optional if using custom model
img = Image.open("path_to_image.png")
predicted_text = model.predict(img)
print(predicted_text)
```

## Files

- `train_model/train.py`: Script to train the OCR model.
- `mb_capcha_ocr/predict.py`: Script to predict text from an image using the trained OCR model.
- `requirements.txt`: List of dependencies required for the project.

## Dependencies

- Python 3.x
- numpy
- onnxruntime
- Pillow

## Dependencies Training

- Python 3.x
- torch
- torchvision
- matplotlib
- Pillow
- onnx

## License

This project is licensed under the MIT License. See the `LICENSE` file for more details.

## Credits

Best thanks to [CookieGMVN](https://github.com/cookieGMVN) for providing
the dataset [V1](https://www.kaggle.com/datasets/cookiegmvn/mbbank-captcha-images) [V2](https://www.kaggle.com/datasets/cookiegmvn/mbbank-captcha-v2).
polymatheia 1.1.0
A python library to support digital archive metadata use
License: MIT
Requires Python: <3.13,>=3.11

**Important!** This library is in an extended end-of-life phase. Some of its dependencies are not compatible with Python 3.13, so it is being phased out.

# Polymatheia

![Validation Status](https://github.com/scmmmh/polymatheia/workflows/Validation/badge.svg) ![Build Status](https://github.com/scmmmh/polymatheia/workflows/Tests/badge.svg) [![Documentation Status](https://readthedocs.org/projects/polymatheia/badge/?version=latest)](https://polymatheia.readthedocs.io/en/latest/?badge=latest) [![PyPI version](https://badge.fury.io/py/polymatheia.svg)](https://badge.fury.io/py/polymatheia)

Polymatheia is a python library to support working with digital archive metadata. Its aim is not necessarily to cover
all ways of working with digital archive metadata, but to make it (comparatively) easy to undertake most types of
tasks and analysis.

*Homepage*: https://polymatheia.readthedocs.io

*Repository*: https://github.com/scmmmh/polymatheia

*Package*: https://pypi.org/project/polymatheia

*License*: MIT
afreeca 0.5.8
AfreecaTV API Wrapper
License: MIT
Requires Python: >=3.9

# Afreeca

AfreecaTV API Wrapper

## Install

```bash
pip install afreeca
```

## Usage

```python
import asyncio
from afreeca import AfreecaTV, Chat, UserCredential

async def callback(chat: Chat):
    print(f"{chat.nickname}: {chat.message}")

async def main():
    cred = await UserCredential.login("ID", "PW")
    afreeca = AfreecaTV(credential=cred)

    chat = await afreeca.create_chat("BJ")

    chat.add_callback(callback)

    await chat.start()


asyncio.run(main())
```

## Reference

https://github.com/ha1fstack/aftv-ws
mseep-mysql-mcp-server-pro 0.0.7
Support for SSE, STDIO in MySQL MCP server, includes CRUD, database anomaly analysis capabilities .支持SSE，STDIO；不仅止于mysql的增删改查功能； 还包含了数据库异常分析能力；且便于开发者们进行个性化的工具扩展
License: MIT
Requires Python: >=3.11

# Package managed by MseeP.ai