Data & Augmentations

Data

Score Board

Model	Data Aug Method	Valid Loss	Valid mIOU(inference)	Score	Kaggle LB
Unet	Default	0.0668	0.4710	0.4999	0.471
Unet	Transparency	0.0636	0.4743	0.4992	0.472
Unet	Thick line	0.0637	0.4722	0.4952	0.494

Clustering

• Allen(주최측) 에서 나누어둔 이미지별 Class : https://www.kaggle.com/c/data-science-bowl-2018/discussion/48130
  • ./metadata/allencls.csv

External Data

Issue #36

• H&E Dataset [USED]

  • https://www.kaggle.com/voglinio/external-h-e-data-with-mask-annotations
  • https://nucleisegmentationbenchmark.weebly.com/

• Harvard Crowd-Sourced Nuclei Annotation Data

  • https://becklab.hms.harvard.edu/software/psb-crowdsourced-nuclei-annotation-data-1
  • /data/public/rw/datasets/dsb2018/origin_ext_train_kmeans
  • /data/public/rw/datasets/dsb2018/origin_ext_valid_kmeans

• TNBC Dataset

  • https://www.kaggle.com/branislav1991/converting-tnbc-external-data-to-dsb2018-format/notebook
  • /data/public/rw/datasets/dsb2018/extra_data_tnbc