/YoloV5-NPU-Rock-5

YoloV5 NPU for the RK3588 on Rock 5 or Orange Pi 5

Primary LanguageC++BSD 3-Clause "New" or "Revised" LicenseBSD-3-Clause

YoloV5 RK3588 NPU

output image

YoloV5 with RK3588 NPU (Rock 5, Orange Pi 5).

License

Paper: https://towardsdatascience.com/yolo-v5-is-here-b668ce2a4908

Special made for the Rock 5 NPU, see Q-engineering deep learning examples

Benchmark.

Model size objects mAP Jetson Nano RPi 4 1950 Rock 5 Rock 5 NPU
NanoDet 320x320 80 20.6 26.2 FPS 13.0 FPS 36.0 FPS
NanoDet Plus 416x416 80 30.4 18.5 FPS 5.0 FPS 24.9 FPS
YoloFastestV2 352x352 80 24.1 38.4 FPS 18.8 FPS 65.4 FPS
YoloV2 416x416 20 19.2 10.1 FPS 3.0 FPS 20.0 FPS
YoloV3 352x352 tiny 20 16.6 17.7 FPS 4.4 FPS 15.0 FPS
YoloV4 416x416 tiny 80 21.7 16.1 FPS 3.4 FPS 22.4 FPS
YoloV4 608x608 full 80 45.3 1.3 FPS 0.2 FPS 1.5 FPS
YoloV5 640x640 small 80 22.5 5.0 FPS 1.6 FPS 12.5 FPS 40 FPS
YoloV6 640x640 nano 80 35.0 10.5 FPS 2.7 FPS 20.8 FPS
YoloV7 640x640 tiny 80 38.7 8.5 FPS 2.1 FPS 17.9 FPS
YoloV8 640x640 nano 80 37.3 14.5 FPS 3.1 FPS 16.3 FPS
YoloV8 640x640 small 80 44.9 4.5 FPS 1.47 FPS 9.2 FPS
YoloX 416x416 nano 80 25.8 22.6 FPS 7.0 FPS 28.5 FPS
YoloX 416x416 tiny 80 32.8 11.35 FPS 2.8 FPS 18.1 FPS
YoloX 640x640 small 80 40.5 3.65 FPS 0.9 FPS 7.5 FPS

Dependencies.

To run the application, you have to:

  • A Rock 5 or an Orange Pi 5.
  • rknpu2 installed.
  • librga installed.
  • OpenCV 64-bit installed.
  • Code::Blocks installed. ($ sudo apt-get install codeblocks)

Installing the dependencies.

Start with the usual

$ sudo apt-get update 
$ sudo apt-get upgrade
$ sudo apt-get install curl libcurl3
$ sudo apt-get install cmake wget

OpenCV

Follow the Raspberry Pi 4 guide.

RKNPU2

$ git clone --depth=1 https://github.com/rockchip-linux/rknpu2.git
$ cd rknu2/runtime/RK3588/Linux/librknn_api/include
$ sudo cp ./rknn* /usr/local/include
$ cd rknu2/runtime/RK3588/Linux/librknn_api/aarch64
$ sudo cp ./lib* /usr/local/lib

Librga

$ git clone --depth=1 https://github.com/airockchip/librga.git
$ cd librga/include
$ sudo cp ./*.h /usr/local/include
$ cd librga/libs/Linux/gcc-aarch64
$ sudo cp ./lib* /usr/local/lib

Installing the app.

To extract and run the network in Code::Blocks
$ mkdir MyDir
$ cd MyDir
$ git clone https://github.com/Qengineering/YoloV5-NPU-Rock-5.git
Remove master.zip, LICENSE and README.md as they are no longer needed.
$ rm master.zip
$ rm LICENSE
$ rm README.md

Your MyDir folder must now look like this:
parking.jpg
busstop.jpg
YoloV5_NPU.cpb
model folder
src folder
header folder

Running the app.

To run the application load the project file YoloV5.cbp in Code::Blocks. More info or
if you want to connect a camera to the app, follow the instructions at Hands-On.

output image

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