MTCNN NCNN Implementation

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the application can be run on X86 and ARM platform with Neon optimization.

How to build

clone the repo

git clone --recursive https://github.com/infinivision/mtcnn_ncnn.git

build ncnn

• ncnn as submodule for the main repo
• to support mtcnn. I update the ncnn code. the repo addr
• for the build and install please refer to the ncnn wiki page

copy the ncnn lib and include headers to the main repo folder

# by default the ncnn was installed in ncnn/build/install folder
mkdir -p lib/ncnn
mkdir -p include/ncnn
cp 3rdparty/ncnn/build/install/lib/libncnn.a lib/ncnn/
cp 3rdparty/ncnn/build/install/include/* include/ncnn/

build the mtcnn main repo

mkdir -p build
cd build
cmake ..
make

how to run

test picture

cd bin
./test_picture ../models/ncnn/ ../images/1.jpg

test video

cd bin
./test_video ../models/ncnn 0

benchmark

Test data

we use the WIDER FACE validate dataset as the test data

run benchmark

cd bin
./benchmark ../models/ncnn ../images

Test Result

Platform	CPU Cores	Memory	total images	detected	min time(ms)	max time(ms)	avg time(ms)
MacOS Sierra	8	16GB	3226	2073	8.068	287.446	47.03
firefly 3399	6	2GB	3226	2084	25.541	4437.42	351.578
firefly 3399(Neon)	6	2GB	3226	2084	10.578	1325.09	157.908