https://github.com/qengineering/rfcn_ncnn

Rfcn for ncnn framework
https://github.com/qengineering/rfcn_ncnn

cpp deep-learning deep-neural-networks ncnn ncnn-framework raspberry raspberry-pi-3 raspberry-pi-4 rfcn

Last synced: 8 days ago
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Rfcn for ncnn framework

• Host: GitHub
• URL: https://github.com/qengineering/rfcn_ncnn
• Owner: Qengineering
• License: bsd-3-clause
• Created: 2019-09-22T16:57:33.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2021-12-27T09:58:06.000Z (about 3 years ago)
• Last Synced: 2024-11-27T11:36:20.889Z (2 months ago)
• Topics: cpp, deep-learning, deep-neural-networks, ncnn, ncnn-framework, raspberry, raspberry-pi-3, raspberry-pi-4, rfcn
• Language: C++
• Size: 56.6 KB
• Stars: 4
• Watchers: 3
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Rfcn for the ncnn framework

![output image]( https://qengineering.eu/images/Rfcn_trafic.jpg )

## Rfcn with the ncnn framework. 


[![License](https://img.shields.io/badge/License-BSD%203--Clause-blue.svg)](https://opensource.org/licenses/BSD-3-Clause)



Paper: https://arxiv.org/pdf/1605.06409.pdf



Special made for a bare Raspberry Pi 4 see [Q-engineering deep learning examples](https://qengineering.eu/deep-learning-examples-on-raspberry-32-64-os.html)

------------

Training set: VOC2007+VOC2012 


Size: 224x224 


Prediction time: 2484 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](https://qengineering.eu/install-raspberry-64-os.html) 


- The Tencent ncnn framework installed. [Install ncnn](https://qengineering.eu/install-ncnn-on-raspberry-pi-4.html) 


- OpenCV 64 bit installed. [Install OpenCV 4.5](https://qengineering.eu/install-opencv-4.5-on-raspberry-64-os.html) 


- 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/Rfcn_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: 
 

Traffic.jpg 


rfcn.bin (download this file from: https://drive.google.com/open?id=1_MO5ipSymIxlBAF2elD3AOJyboIdiKEa )


rfcn.param 


Rfcn.cpb 


rfcn.cpp 


 


Run Rfcn.cpb with Code::Blocks.  More info or
 

if you want to connect a camera to the app, follow the instructions at [Hands-On](https://qengineering.eu/deep-learning-examples-on-raspberry-32-64-os.html#HandsOn).

------------

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