Skip to content

Latest commit

 

History

History
40 lines (32 loc) · 839 Bytes

README.md

File metadata and controls

40 lines (32 loc) · 839 Bytes

Steel_Defect_Detection

competetion named "Steel Defect Detection" on kaggle please download dataset from the above

Data Visualizatoin

if you want to check total number of training data and visualize some of them

python3 ./datavis.py

Training

you can choose following models and loss functions, please type following keywords in ()

models : -m (default = unet)

  • UNet (unet)
  • ResNet-based Unet (resnetx: x is num layers of ResNet)
  • ResUNet-a (resunet-a)
-m <MODEL NAME>

loss functions : -l (default = BCE)

  • BCE (BCE)
  • Dice (Dice)
  • DiceBCE (DiceBCE)
  • IoU (IoU)
  • Focal (Focal)
  • Tanimoto (Tanimoto)
-l <FUNCTION NAME>

Then, you can train model like this

$ cd src
$ python3 ./main.py -m <MODEL NAME> -l <FUNCTION NAME>