ShuffleNetV2 for the ncnn framework

ShuffleNetV2 with the ncnn framework.

Paper: https://arxiv.org/pdf/1807.11164.pdf


Special made for a bare Raspberry Pi 4 see Q-engineering deep learning examples

Training set: ImageNet 2012

Size: 224x224

Prediction time: 22 mSec (RPi 4)

Dependencies.

To run the application, you have to:

• A raspberry Pi 4 with a 32 or 64-bit operating system. It can be the Raspberry 64-bit OS, or Ubuntu 18.04 / 20.04. Install 64-bit OS
  
• The Tencent ncnn framework installed. Install ncnn
  
• OpenCV 64 bit installed. Install OpenCV 4.5
  
• Code::Blocks installed. ($ sudo apt-get install codeblocks)

Installing the app.

To extract and run the network in Code::Blocks

$ mkdir MyDir

$ cd MyDir

$ wget https://github.com/Qengineering/ShuffleNetV2-ncnn/archive/refs/heads/master.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:

cat.jpg

vulture.jpg

shufflenet.bin

shufflenet.param

ShuffleNet.cpb

shufflenetv2.cpp

Running the app.

To run the application load the project file ShuffleNet.cbp in Code::Blocks. More info or

if you want to connect a camera to the app, follow the instructions at Hands-On.