Face-detection-Landmark-Raspberry-Pi-32-64-bits

A fast face detection with landmarks running on a bare Raspberry Pi 4.

This C ++ application detects faces in a scene. At the same time, the characteristic landmarks are located so that you can use them as input for a face recognition algorithm. (see: Face recognition).

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Benchmark.

RPi 4 64-OS 1950 MHz	RPi 4 64-OS 1500 MHz	Jetson Nano 2015 MHz	Jetson Nano 1479 MHz
20 mS	23 mS	11 mS	14 mS

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Dependencies.

To run the application on a 64 OS, you have to:

• A raspberry Pi 4 with a 64-bit operating system. It can be the Raspberry 64-bit OS, or Ubuntu 18.04 / 20.04. (https://qengineering.eu/install-raspberry-64-os.html)
  
• The Tencent ncnn framework installed. (https://qengineering.eu/install-ncnn-on-raspberry-pi-4.html)
  
• OpenCV 64 bit installed. (https://qengineering.eu/install-opencv-4.3-on-raspberry-64-os.html)
  
• Code::Blocks installed.
  

To run the application on a 32 OS, you need:

• The Tencent ncnn framework installed. (https://qengineering.eu/install-ncnn-on-raspberry-pi-4.html)
  
• OpenCV 32 bit installed. (https://qengineering.eu/install-opencv-4.3-on-raspberry-pi-4.html)
  
• Code::Blocks installed.

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Running the app.

To extract and run the network in Code::Blocks
$ mkdir MyDir
$ cd MyDir
$ wget https://github.com/Qengineering/Face-detection-Landmark-Raspberry-Pi-32-64-bits/archive/refs/heads/main.zip
$ unzip -j master.zip
Remove master.zip, LICENSE and README.md as they are no longer needed.
$ rm master.zip
$ rm README.md

Your MyDir/ncnn folder must now look like this:
9.jpg
11.jpg
Walk2.mp4 (demo video)
FaceLandmark.cpb (code::blocks project file)
main.cpp (main example file)
FaceDetector.cpp (Ultra face class)
FaceDetector.hpp (Ultra face class)
face.bin (ncnn model)
face.param (ncnn topology file)

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WebCam.

If you want to use a camera please alter line 22 in main.cpp to
cv::VideoCapture cap(0); //WebCam
If you want to run a movie please alter line 22 in main.cpp to
cv::VideoCapture cap("Walks2.mp4"); //Movie

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Thanks.

https://github.com/Tencent/ncnn
https://github.com/nihui
https://github.com/Linzaer/Ultra-Light-Fast-Generic-Face-Detector-1MB
https://github.com/biubug6/Face-Detector-1MB-with-landmark/tree/master/Face_Detector_ncnn