# azFace111

**Repository Path**: sdcfsdsd/azFace111

## Basic Information

- **Project Name**: azFace111
- **Description**: https://github.com/azmathmoosa/azFace
- **Primary Language**: Unknown
- **License**: LGPL-3.0
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2018-12-18
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

## azFace YOLOv2 Face Detector

This is a tiny yolo face detector trained on FDDB+Dlib dataset.  It was trained on a GTX1080 for about 82k iterations.  It runs fast at 112 fps on GTX1080 which is more than enough for realtime usage.

[![Preview](http://img.youtube.com/vi/rX7AxQYrXkk/0.jpg)](https://www.youtube.com/watch?v=rX7AxQYrXkk)


## How To Use

### Windows

Clone the repo
```bash
>git clone https://github.com/azmathmoosa/azFace.git
```
CD into the repo
```
>cd azFace
```
Launch yolo_console_dll.exe followed by path to video/image
```
>yolo_console_dll.exe C:\random\video.mp4
```
Or use the darknet executable
```
>darknet.exe detector demo net_cfg\azface.data net_cfg\tiny-yolo-azface-fddb.cfg weights\tiny-yolo-azface-fddb_82000.weights C:\Dataset\random\crowd.mp4
```

### Linux

1. Clone this repo and the [darknet](https://github.com/AlexeyAB/darknet) repo.
2. Follow the instructions of darknet to build it
3. After building use the provided cfg and weight files like so
```
./darknet detector demo net_cfg/azface.data net_cfg/tiny-yolo-azface-fddb.cfg weights/tiny-yolo-azface-fddb_82000.weights /path/to/my/video.mp4
```

## Make your own Videos

To record a video use this command
```
>darknet.exe detector demo net_cfg\azface.data net_cfg\tiny-yolo-azface-fddb.cfg weights\tiny-yolo-azface-fddb_82000.weights C:\Dataset\random\crowd.mp4 -out_filename test.avi
```

You will need DivX codec installed to record and VLC to play the video.

## License

This work is licensed under LGPLv3.  Please attribute to the author incase you find this work useful.

## About Me

In my spare time I offer consultation services for deep learning projects.  If you need assistance for your projects feel free to reach me at `a z m a t h m o o s a @ g m a i l dot c o m`