Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/arrufat/face
Face detection and recognition using dlib
https://github.com/arrufat/face
dlib face-detection face-recognition neural-network
Last synced: about 2 months ago
JSON representation
Face detection and recognition using dlib
- Host: GitHub
- URL: https://github.com/arrufat/face
- Owner: arrufat
- License: apache-2.0
- Created: 2018-12-14T22:19:04.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2019-12-15T01:56:48.000Z (about 5 years ago)
- Last Synced: 2024-07-31T19:23:19.014Z (5 months ago)
- Topics: dlib, face-detection, face-recognition, neural-network
- Language: C++
- Homepage:
- Size: 26.4 KB
- Stars: 1
- Watchers: 4
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-lists - face detection and recognition using dlib
README
# Face detection and recognition using dlib
## Introduction
The main purpose of this repository is to provide an end to end solution for face detection and recognition using the amazing [dlib](http://dlib.net/) library.
## Installation
### Dependencies
The only external dependency of this project is OpenCV >= 3, used only for camera acquistion (or video input).
However, having CUDA and CUDNN will make running the deep learning models for detection more usable.
Dlib will be fetched directly by CMake, so once OpenCV has been installed, the following command should do all the work for you:
``` bash
./build.sh
```
Which will download the needed pretrained models and build the project.
The resulting binary will be found inside of the a newly created directory, named `build`.
## Running
The program works in the following way:
1. Checks for an enrollments directory with the following structure `enrollments/{person1,person2}` and images of each person inside those directories.
2. Builds a dictionary of face descriptors of all faces
3. Opens the Webcam (or video file) and, for each frame, detects, computes face descriptors and compares to dictionary for a match.
All options are customizable, which can be checked by passing the `--help` flag:
```
./build/face --help
Usage: ./build/main [options]
Options:
--enroll-dir Enrollment directory (default: enrollment)
--fps Force the frames per second for the webcam
--help Display this help message.
--input Path to video file to process (defaults to webcam)
--light Use a lighter detection model
--mirror Mirror mode (left-right flip)
--pyramid-levels Pyramid levels for the face detector (default: 1)
--scale-factor Scaling factor for the input image (default: 1.0)
--threshold Face recognition threshold (default: 0.5)
```