Metadata-Version: 2.1
Name: pyplatex
Version: 0.0.3
Summary: A scalable and versatile ANPR package leveraging YOLO for detection and multiple OCR options to accurately recognize license plates.
Home-page: https://github.com/nuhmanpk/pyplatex
Author: Nuhman Pk
Author-email: nuhmanpk7@gmail.com
License: MIT
Project-URL: Documentation, https://github.com/nuhmanpk/pyplatex/blob/main/README.md
Project-URL: Funding, https://github.com/sponsors/nuhmanpk
Project-URL: Source, https://github.com/nuhmanpk/pyplatex/
Project-URL: Tracker, https://github.com/nuhmanpk/pyplatex/issues
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3.9
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE

# PyPlateX
High-Performance Scalable ANPR Package: Ready-to-Use, Simple, and Efficient License Plate Recognition

Unlock top-tier accuracy and scalability with our cutting-edge ANPR solution **in 3 line of code**. Designed for seamless integration and ease of use, it delivers robust performance and reliability for all your license plate recognition needs.


[![Downloads](https://static.pepy.tech/personalized-badge/pyplatex?period=total&units=abbreviation&left_color=grey&right_color=yellow&left_text=Total-Downloads)](https://pepy.tech/project/pyplatex)
[![Supported Versions](https://img.shields.io/pypi/pyversions/pyplatex.svg)](https://pypi.org/project/pyplatex)
![GitHub](https://img.shields.io/github/license/nuhmanpk/pyplatex)
![PyPI](https://img.shields.io/pypi/v/pyplatex)
![PyPI - Downloads](https://img.shields.io/pypi/dm/pyplatex)
[![Downloads](https://static.pepy.tech/personalized-badge/pyplatex?period=week&units=international_system&left_color=grey&right_color=brightgreen&left_text=Downloads/Week)](https://pepy.tech/project/pyplatex)
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## Simple ready to use ANPR 

**Note: The ANPR.detect function is asynchronous, so ensure you use the await keyword when calling it within an async function.**

### Install from pypi.org

```sh
pip install pyplatex
```

```py
from pyplatex import ANPR
anpr = ANPR()
det = await anpr.detect('./demo/plate-1.jpg')
print(det)
```
or

```py

from pyplatex import ANPR
import asyncio

async def main():
    anpr = ANPR()
    plates = await anpr.detect('./demo/plate-1.jpg')
    print(plates)

# Run the async main function
asyncio.run(main())

```
the output would be like

<img src='./demo/plate-1.jpg' width=500px height=350px />

```
    {
        'is_plate': True, 
        'is_plate_confidence': 0.78, 
        'plate_number': 'MUN389', 
        'plate_number_confidence': 1.0
    }
```


### Dev TODO:
- [x] Release a Inital Version
- [x] Add a plate detection model
- [x] Read and detect Plates
- [x] Format output
- [x] Integrate Cv2filters
- [x] Change Cofidence to a round number
- [x] Add a ocr Model
- [x] Release a Initial Version
- [ ] Add a option to accept image as Tensor / numpy array
- [ ] Add auto filters tag
<!-- [ ] -->

**This is a pre-release version; there might be some bugs. If you encounter any issues or performance-related problems, please report them [here](https://github.com/nuhmanpk/pyplatex/issues). If you'd like to contribute to this project, you can create a pull request [here](https://github.com/nuhmanpk/pyplatex/pulls).**

**Warning: Use this pre-release with caution as it may still have unresolved issues.**

Happy Coding 🚀 ...


