Papers: https://arxiv.org/pdf/1804.06882.pdf

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

Training set: VOC2007
Size: 304x304
Prediction time: 300 mSec (RPi 4)

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 32 or 64-bit installed. Install OpenCV 4.5
  
• Code::Blocks installed. ($ sudo apt-get install codeblocks)

To extract and run the network in Code::Blocks
$ mkdir MyDir
$ cd MyDir
$ wget https://github.com/Qengineering/PeleeNet_SSD/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:
mumbai.jpg
pelee.bin
pelee.param
Pelee.cpb
peleenetssd_seg.cpp

Run Pelee.cpb with Code::Blocks. More info or
if you want to connect a camera to the app, follow the instructions at Hands-On.