# LightNet

**Repository Path**: keinn/LightNet

## Basic Information

- **Project Name**: LightNet
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: dev
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2024-09-02
- **Last Updated**: 2024-09-02

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# <p align="center">LightNet</p>
Implemented in pure pascal LightNet is an artificial intelligence neural network library Inspired by 
[Darknet](https://pjreddie.com/darknet) and [YOLOv7 github](https://github.com/AlexeyAB/darknet) C library, 
this implementation can run most of the darknet including YOLO models nativly and self dependently no external libraries required.

- Currently training & inference runs on CPU , however i have notice that inference runs faster than the Optimized C CPU implementation
- Optionally, using `-dOPENBLAS`  or `-dMKL` ( Custom options in Lazarus-Ide for example ) will enable "libopenblas" or "Intel's Math Kernel Library" which is further optimized for CPU, however, on lazarus no significant improvement was noticed.
- Before running the test make sure that [yolov7.weights](https://sourceforge.net/projects/darknet-yolo.mirror/files/yolov4/) file is placed next to the test project executable.
- Other .weights models should work (check "cfg" folder) 
- More Examples coming soon



### Work pending 
- OpenCL and CUDA implementation
- Test on other platforms (MacOS, Linux)
- Test on Single Board Computers (NVIDIA Jetson, Raspberry PI, etc..)


tests provided for both Lazarus and Delphi

_this project is still at the early stage, if you wish to see more models 
running in pure pascal, please consider donating here_
<p align="center"><a href="https://www.paypal.com/donate/?hosted_button_id=ANXTNK87HYP4Q"><img src="https://www.paypalobjects.com/en_US/i/btn/btn_donate_SM.gif" alt="Buy me coffee"/></a></p>