TBrain_histapathology_seg

TBrain histapathology segmentation contest.

The training relative resource can be download in 2022 STAS

Pre-setting

Download custom training datasets at 2022 STAS/SEG_Train_Datasets

Download package by execute:

$sh preprocess.sh

Or according to the requirements : ./requirements/Pipfile, download the package by pip.

./trainlist is the list of cross validation training/validation set.

Configuration

Config file for training and inferencing model is in ./cfg.

setting.yaml is the config for experiment name, image root, inference path, use crossvalidation , use soup setting.

wandbcfg.yaml is the config for training model hyperparameter.

Training

After setting config file, start training:

$python training.py

The training ckpt will save in ./result

We provide Data Distributed Parallel and will automatically detect gpu number.

Inference

Modified inference.py for to assign inference experiment ckpt.

Use voting.py and embedding.py to get majority agreement mask.

$python inference.py
$python voting.py
$python embedding.py

Pretrain weight can be download in 2022 STAS/model weight

Or best model ckpt in private score is base_DL_plus_10fd0

cross validation result in public

Name                        f1-score    precision   recall
U+_nc_ef4ap_FTL_10fd4_soup5 0.904259    0.899413    0.909157        V

4, 5
base_DL_plus_10fd0          0.89715     0.888939	0.905514
base_DL_plus_10fd3          0.900433    0.906386    0.894558        V
base_DL_plus_10fd7          0.898166	0.889426    0.907079
base_DL_plus_10fd8          0.901063    0.886515    0.916096        V
0, 3, 5, 7,                 X
U+_nc_ef4ap_sDL_10fd4       0.894808    0.868046    0.923273
U+_nc_ef4ap_sDL_10fd6       0.902042    0.917095    0.887474        V
U+_nc_ef4ap_sDL_10fd8       0.902314    0.902158    0.902471        V

U+_nc_ef4ap_FTL_10fd0       0.895147    0.883711    0.906883
U+_nc_ef4ap_FTL_10fd1       0.886003    0.872314    0.900128
U+_nc_ef4ap_FTL_10fd2       0.892547    0.885231	0.899985
U+_nc_ef4ap_FTL_10fd3_last  0.894663    0.915445    0.874804
U+_nc_ef4ap_FTL_10fd4       0.899646    0.897439    0.901864        V
U+_nc_ef4ap_FTL_10fd5       0.894417	0.888879    0.900025
U+_nc_ef4ap_FTL_10fd6       0.898047    0.882558    0.914091
U+_nc_ef4ap_FTL_10fd7       0.897821    0.886498    0.909436
U+_nc_ef4ap_FTL_10fd8       0.893720    0.891105    0.896352
U+_nc_ef4ap_FTL_10fd9       0.892483    0.884145    0.900980