NNPACK was used to optimize AlexeyAB/darknet without using a GPU. It is useful for embedded devices using ARM CPUs.
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
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]
| 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 |
| 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 |
Download OS image from here
sudo dd bs=4M if=darknet-nnpack.img of=/dev/sdX conv=fsyn
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