Face-Mask-Detection-Jetson-Nano

A fast face mask recognition running at 44-5 FPS on a Jetson Nano.

This is a fast C++ implementation of two deep learning models found in the public domain.

The first is face detector of Linzaer running on a ncnn framework.
https://github.com/Linzaer/Ultra-Light-Fast-Generic-Face-Detector-1MB.

The second is the Paddle Lite mask detection which classifies the found faces.
https://github.com/PaddlePaddle/Paddle-Lite/tree/develop/lite/demo/cxx/mask_detection.

The frame rate depends on the number of detected faces and can be calculated as follows:
FPS = 1.0/(0.022 + 0.008 x #Faces) when overclocked to 2014 MHz.

Paper: https://arxiv.org/abs/1905.00641.pdf
Size: 320x320

Special made for a Jetson Nano see Q-engineering deep learning examples

New version 2.0.

A new and superior version with only TensorFlow Lite for a Jetson Nano see GitHub

Dependencies.

April 4 2021: Adapted for ncnn version 20210322 or later

To run the application, you have to:

The Paddle Lite framework installed. Install Paddle
The Tencent ncnn framework installed. Install ncnn
Code::Blocks installed. ($ sudo apt-get install codeblocks)

Running the app.

To extract and run the network in Code::Blocks
$ mkdir MyDir
$ cd MyDir
$ wget https://github.com/Qengineering/Face-Mask-Detection-Jetson-Nano/archive/refs/heads/main.zip
$ unzip -j master.zip
Remove master.zip and README.md as they are no longer needed.
$ rm master.zip
$ rm README.md

Your MyDir folder must now look like this:
Face_1.jpg
Face_2.jpg
Face_3.jpg
Face_Mask_Video.mp4
mask_detector_opt2.nb
MaskUltra.cpb
mask_ultra.cpp
UltraFace.cpp
UltraFace.hpp
RFB-320.bin
RFB-320.param
slim_320.bin
slim_320.param

Notes.

The directories in the Code::Blocks project file will probably need to be adapted to the naming convention you are using.
The camera input used is a simple OpenCV webcam. The GStreamer is not used in this example for symplicity reasons.

The RFB-320 model recognizes slightly more faces than slim_320 at the expense of a little bit of speed. It is up to you.
Note that the compilation of the Paddle Lite framework in your application may take a while.

See the Raspberry Pi video at https://youtu.be/LDPXgJv3wAk

Lots of undefined errors while building

Hi,
Im getting lots of undefined errors while building this :-
g++ -Wall -fexceptions -pthread -O3 -I/usr/include/opencv4 -I/usr/local/include/paddle-lite -I/usr/local/include/ncnn -c /home/ns/Face-Mask-Detection-Jetson-Nano/mask_ultra.cpp -o obj/Release/mask_ultra.o
...........

g++ -L/usr/local/lib/ -L/usr/lib/ -o bin/Release/MaskUltra obj/Release/mask_ultra.o obj/Release/UltraFace.o   -pthread -fopenmp -s  /usr/local/lib/paddle-lite/libpaddle_api_light_bundled.a /usr/local/lib/ncnn/libncnn.a /usr/lib/aarch64-linux-gnu/libvulkan.so /usr/local/lib/ncnn/libglslang.a /usr/local/lib/ncnn/libOGLCompiler.a /usr/local/lib/ncnn/libOSDependent.a /usr/local/lib/ncnn/libSPIRV.a

obj/Release/mask_ultra.o: In function `cv::Mat::~Mat()':
mask_ultra.cpp:(.text._ZN2cv3MatD2Ev[_ZN2cv3MatD5Ev]+0x84): undefined reference to `cv::fastFree(void*)'
mask_ultra.cpp:(.text._ZN2cv3MatD2Ev[_ZN2cv3MatD5Ev]+0x94): undefined reference to `cv::Mat::deallocate()'
obj/Release/mask_ultra.o: In function `main':
mask_ultra.cpp:(.text.startup+0x10b8): undefined reference to `cv::String::allocate(unsigned long)'
mask_ultra.cpp:(.text.startup+0x10e8): undefined reference to `cv::VideoCapture::VideoCapture(cv::String const&)'
mask_ultra.cpp:(.text.startup+0x10f0): undefined reference to `cv::String::deallocate()'
mask_ultra.cpp:(.text.startup+0x10f8): undefined reference to `cv::VideoCapture::isOpened() const'
mask_ultra.cpp:(.text.startup+0x1128): undefined reference to `cv::VideoCapture::~VideoCapture()'
mask_ultra.cpp:(.text.startup+0x1200): undefined reference to `cv::VideoCapture::operator>>(cv::Mat&)'
mask_ultra.cpp:(.text.startup+0x1274): undefined reference to `cv::destroyAllWindows()'
mask_ultra.cpp:(.text.startup+0x1494): undefined reference to `cv::fastFree(void*)'
mask_ultra.cpp:(.text.startup+0x15ac): undefined reference to `cv::format(char const*, ...)'
mask_ultra.cpp:(.text.startup+0x15fc): undefined reference to `cv::putText(cv::_InputOutputArray const&, cv::String const&, cv::Point_<int>, int, double, cv::Scalar_<double>, int, int, bool)'
mask_ultra.cpp:(.text.startup+0x1604): undefined reference to `cv::String::deallocate()'
mask_ultra.cpp:(.text.startup+0x1614): undefined reference to `cv::String::allocate(unsigned long)'
mask_ultra.cpp:(.text.startup+0x1658): undefined reference to `cv::imshow(cv::String const&, cv::_InputArray const&)'
mask_ultra.cpp:(.text.startup+0x1660): undefined reference to `cv::String::deallocate()'
mask_ultra.cpp:(.text.startup+0x1668): undefined reference to `cv::waitKey(int)'
mask_ultra.cpp:(.text.startup+0x16cc): undefined reference to `cv::Mat::Mat(cv::Mat const&, cv::Rect_<int> const&)'
mask_ultra.cpp:(.text.startup+0x1714): undefined reference to `cv::resize(cv::_InputArray const&, cv::_OutputArray const&, cv::Size_<int>, double, double, int)'
mask_ultra.cpp:(.text.startup+0x1744): undefined reference to `cv::Mat::convertTo(cv::_OutputArray const&, int, double, double) const'
mask_ultra.cpp:(.text.startup+0x1800): undefined reference to `cv::rectangle(cv::Mat&, cv::Rect_<int>, cv::Scalar_<double> const&, int, int, int)'
mask_ultra.cpp:(.text.startup+0x1874): undefined reference to `cv::fastFree(void*)'
mask_ultra.cpp:(.text.startup+0x18e8): undefined reference to `cv::fastFree(void*)'
mask_ultra.cpp:(.text.startup+0x1904): undefined reference to `cv::Mat::deallocate()'
mask_ultra.cpp:(.text.startup+0x1910): undefined reference to `cv::Mat::deallocate()'
mask_ultra.cpp:(.text.startup+0x1998): undefined reference to `cv::Mat::deallocate()'
mask_ultra.cpp:(.text.startup+0x19f4): undefined reference to `cv::String::deallocate()'
mask_ultra.cpp:(.text.startup+0x1a10): undefined reference to `cv::VideoCapture::~VideoCapture()'
mask_ultra.cpp:(.text.startup+0x1a98): undefined reference to `cv::String::deallocate()'
mask_ultra.cpp:(.text.startup+0x1ac0): undefined reference to `cv::String::deallocate()'
collect2: error: ld returned 1 exit status
Process terminated with status 1 (0 minute(s), 11 second(s))
31 error(s), 2 warning(s) (0 minute(s), 11 second(s))

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