Darknet with NNPACK
NNPACK was used to optimize AlexeyAB/darknet without using a GPU. It is useful for embedded devices using ARM CPUs.
Build from Raspberry Pi 4
Log in to Raspberry Pi using SSH.
Install PeachPy and confu
sudo pip install --upgrade git+https://github.com/Maratyszcza/PeachPy
sudo pip install --upgrade git+https://github.com/Maratyszcza/confu
Install Ninja
git clone https://github.com/ninja-build/ninja.git
cd ninja
git checkout release
./configure.py --bootstrap
export NINJA_PATH=$PWD
Install clang
sudo apt-get install clang
Install NNPACK-darknet
git clone https://github.com/digitalbrain79/NNPACK-darknet.git
cd NNPACK-darknet
confu setup
python ./configure.py --backend auto
$NINJA_PATH/ninja
sudo cp -a lib/* /usr/lib/
sudo cp include/nnpack.h /usr/include/
sudo cp deps/pthreadpool/include/pthreadpool.h /usr/include/
Build darknet-nnpack
git clone https://github.com/digitalbrain79/darknet-nnpack.git
cd darknet-nnpack
make
Test
COCO trained weights files can be downloaded from the AlexeyAB/darknet.
COCO
./darknet detector test cfg/coco.data [cfg file] [weights file] [image path]
Pascal VOC
./darknet detector test cfg/voc.data [cfg file] [weights file] [image path]
Results
COCO
cfg | Build Options | mAP | Prediction Time (seconds) |
---|---|---|---|
yolov3-tiny.cfg | NNPACK=1 | 33.1 | 1.1 |
yolov3-tiny.cfg | NNPACK=0 | 14.5 | |
yolov3-tiny-prn.cfg | NNPACK=1 | 33.1 | 0.86 |
yolov3-tiny-prn.cfg | NNPACK=0 | 9.3 |
Pascal VOC
cfg | Build Options | mAP | Prediction Time (seconds) | Weights file |
---|---|---|---|---|
yolov3-tiny-voc.cfg | NNPACK=1 | 65.9 | 1.0 | yolov3-tiny-voc.weights |
yolov3-tiny-voc.cfg | NNPACK=0 | 14.0 | ||
yolov3-tiny-prn-voc.cfg | NNPACK=1 | 65.2 | 0.77 | yolov3-tiny-prn-voc.weights |
yolov3-tiny-prn-voc.cfg | NNPACK=0 | 8.9 | ||
Gaussian_yolov3-tiny-voc.cfg | NNPACK=1 | 65.7 | 1.0 | Gaussian_yolov3-tiny-voc.weights |