Skip to content

jtlee1/BreadYolo

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

8 Commits
 
 
 
 

Repository files navigation

BreadYolo

Intro

Hi, I am Justin Lee. Here is a guide of how I use Yolo to train an object recognition bot.
First thing to know is you will need a decent GPU installed in your computer because using CPU to train your bot will be extreamly slow.
The GPU I use is GTX1050, so make sure to adjust some steps if you feel like the step is just for my GPU.

Step1

Install NVIDA driver(for using GPU).
If you did have this installed, please skip.
First you will install NVIDA driver following this guide https://medium.com/@zihansyu/ubuntu-16-04-%E5%AE%89%E8%A3%9Dcuda-10-0-cudnn-7-3-8254cb642e70
This guide are mostly good other then it did not tell you to turn off Xservice first.
If you get an error to turn off your Xservice do "ctrl+alt+f1", login, then type in "sudo service lightdm stop".
When you are finish, do "sudo service lightdm start" or "sudo service lightdm restart" to reactivate.

Step2

Install CUDA(for using GPU).
If you did have this installed, please skip.
Basically follow this https://ithelp.ithome.com.tw/articles/10191693?sc=iThelpR
I didn't pass the test it gave me (showing CUDA Device Query (Runtime API) version (CUDART static linking)cudaGetDeviceCount returned 35-> CUDA driver version is insufficient for CUDA runtime versionResult = FAIL) But it still work for me.

Step3

Download darknet from https://pjreddie.com/darknet/
Remember to change GPU=0 to GPU=1 in the make file before you do "make".

Step4

Train your bot
Follow https://chtseng.wordpress.com/2019/01/25/%e7%89%a9%e4%bb%b6%e5%81%b5%e6%b8%ac%e7%9a%84%e6%87%89%e7%94%a8-diy%e9%9b%bb%e8%85%a6%e8%a6%96%e8%a6%bapos%e7%b5%90%e5%b8%b3%e5%8f%b0/?fbclid=IwAR0ZJxCbceHBtvW7EEEeoqV7q_NdtdIKBOI8Fbl_SjVkV41DCgUXcKMDlbc
Make sure you follow all step closely because every detail matters.
I will provide a sample so you know where everything is located.
One thing to point out is the way it provid to train my bot doesn't work for me. I use the command
"./darknet detector train [obj.data] [yolov3-tiny.cfg] [weights]" instead (fill in the path of your own .data .cfg and weight file)
When editing yolov3-tiny-cfg file, need to change the filter on line 171 too.
Another thing to point out is you can change your [weights] section to continue trian from your last trial.

More info

Check out https://chtseng.wordpress.com/2018/09/01/%e5%bb%ba%e7%ab%8b%e8%87%aa%e5%b7%b1%e7%9a%84yolo%e8%be%a8%e8%ad%98%e6%a8%a1%e5%9e%8b-%e4%bb%a5%e6%9f%91%e6%a9%98%e8%be%a8%e8%ad%98%e7%82%ba%e4%be%8b/?fbclid=IwAR2xBxavCZe4sH1c_ZmRIud9Jl0Hotu7fXtjomabznsCZcFVnjuyE0nL1nQ
and
https://chtseng.wordpress.com/2018/10/08/%e5%a6%82%e4%bd%95%e5%bf%ab%e9%80%9f%e5%ae%8c%e6%88%90yolo-v3%e8%a8%93%e7%b7%b4%e8%88%87%e9%a0%90%e6%b8%ac/?fbclid=IwAR2uDno8ychQH4e8xQ6S8fKOf-hmKc-BFEI24USSFq_7TM5WsEqKCIe6VGY
if you want to test out your module without using raspbarry pi.

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors

Languages