I have setting up a project that should detect iris region ( in eye ) in real time using deep learning , I have cloned yolo segmentation project in github : https://github.com/ArtyZe/yolo_segmentation
I compiled the project using make -j4 , and i'm trying now to training my own dataset using this project
System specifications :
Ubuntu 19.04
Cuda 10.1
Nvidia Geforce 840m
My dataset is organized according to this :
/darknet-yolo-segmentation
|-->images
|-->C12...jpg #JPG image
...
|-->C12...bmp #mask
|-->data
|-->test.list #containes images for test
|-->train.list #containes images for train
|-->obj.data #containes the path of train and test and backup
|-->obj.names #containes the classes ( I have one class " iris " )
The command that i execute:
./darknet segmenter train data/obj.data segment.cfg segment.backup
And I have the two files that you send segment12.backup and segment12.weights When i trained my own datasets I get illogical values of avg ,
Some times avg decrease and increase ( it should decrease ) and rate should be increase after number of iterations Some times i get negatives values for avg values and this is it illogical
https://i.imgur.com/sQTukMF.png
How can i fix this issue ? Thanks
What I have tried:
I tried to training my own dataset using this tool ( yolo-segmentation )