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+### Introduction
+
+Hello!
+
+Below you can find a outline of how to reproduce my solution for the [UW-Madison GI Tract Image Segmentation | Kaggle](https://www.kaggle.com/competitions/uw-madison-gi-tract-image-segmentation/discussion/337197#1864282)
+
+If you run into any trouble with the setup/code or have any questions please contact me at 273806108@qq.com
+
+
+
+### Contents
+
+```sh
+preprocess.py: data preprocessing codes
+inference.py: inferencing codes
+other: necessary codes for `mmsegmentation` and `monai` toolboxes
+```
+
+
+
+### Hardware
+
+```sh
+Ubuntu 16.04 LTS (512 GB boot disk)
+48 x Intel(R) Xeon(R) Gold 5118 CPU @ 2.30GHz
+126 GB Memory
+4 x NVIDIA Titan RTX
+```
+
+### Software
+
+```sh
+python==3.7.10
+CUDA==10.2
+cudnn==7.6.5
+nvidia-drivers==440.4
+(other refer to ./requirements.txt)
+```
+
+### Data setup
+
+```sh
+# DOWNLOAD DATA
+kaggle competitions download -c uw-madison-gi-tract-image-segmentation
+
+mkdir -p ./data/tract
+mv uw-madison-gi-tract-image-segmentation.zip ./data/tract
+
+cd ./data/tract
+unzip uw-madison-gi-tract-image-segmentation.zip
+cd ../..
+```
+
+
+The expected after unzip should be:
+
+```sh
+./data/tract
+        ├── sample_submission.csv
+        ├── test
+        ├── train
+        ├── train.csv
+```
+Install base requirements, `mmsegmentation` and `monai` toolboxes
+
+```sh
+# INSTALL PYTHON REQUIREMENTS
+pip install -r requirements.txt
+pip install "monai[ignite,skimage,nibabel]==0.8.1"
+pip install mmcv-full==1.3.17 --force-reinstall -f https://download.openmmlab.com/mmcv/dist/cu102/torch1.10.0/index.html
+pip install -v -e .
+```
+
+### Data preprocess
+
+```sh
+python data_preprocess.py
+```
+
+### Training
+
+> NOTE: **make sure internet connection for public pretrained weights downloading**
+
+```sh
+mkdir -p saved_weights/cls saved_weights/seg saved_weights/3d
+
+# DOWNLOAD PRETRAINED WEIGHTS
+mkdir weights
+cd weights
+wget https://dl.fbaipublicfiles.com/convnext/ade20k/convnext_base_22k_224.pth
+wget https://dl.fbaipublicfiles.com/convnext/ade20k/convnext_small_1k_224_ema.pth
+cd ..
+
+# TRAIN CLASSIFICATION MODELS
+id=1
+for config in $(find ./work_configs/tract/final_solution/classification_configs/cls*.py | sort); do
+	./tools/dist_train.sh $config 2
+	last_work_dir=$(ls ./work_dirs/tract/ -rt | tail -n 1)
+	last_weight=$(ls ./work_dirs/tract/$last_work_dir/*.pth -rt | tail -n 1)
+	last_config=$(ls ./work_dirs/tract/$last_work_dir/*.py -rt | tail -n 1)
+	mv ./work_dirs/tract/$last_work_dir/$last_weight ./saved_weights/cls/cls_${id}.pth
+	mv ./work_dirs/tract/$last_work_dir/$last_config ./saved_weights/cls/cls_${id}.py
+	id=$[id+1]
+done
+
+# TRAIN SEGMENTATION MODELS
+id=1
+for config in $(find ./work_configs/tract/final_solution/segmentation_configs/seg*.py | sort); do
+	./tools/dist_train.sh $config 2
+	last_work_dir=$(ls ./work_dirs/tract/ -rt | tail -n 1)
+	last_weight=$(ls ./work_dirs/tract/$last_work_dir/*.pth -rt | tail -n 1)
+	last_config=$(ls ./work_dirs/tract/$last_work_dir/*.py -rt | tail -n 1)
+	mv ./work_dirs/tract/$last_work_dir/$last_weight ./saved_weights/seg/seg_${id}.pth
+	mv ./work_dirs/tract/$last_work_dir/$last_config ./saved_weights/seg/seg_${id}.py
+	id=$[id+1]
+done
+
+# TRAIN 3D MODELS
+cd ./monai
+fold=-1
+for n in (12 20 32); do
+    mkdir -p  ./output/segres${n}_all/all
+    python multilabel_train.py \
+        -c segres${n}_all \
+        -f $fold \
+        > ./output/segres${n}_all/all/output.txt
+        
+    mkdir -p  ./output/segres${n}_all_round2/all
+    python multilabel_train.py \
+        -c segres${n}_all_round2 \
+        -f $fold \
+        -w ./output/segres${n}_all/all/last.pth \
+        > ./output/segres${n}_all_round2/all/output.txt
+    mv ./output/segres${n}_all_round2/all/last.pth ../saved_weights/3d/segres${n}.pth
+done
+cd ..
+```
+
+### Inferencing
+
+```
+python inference.py
+```
+
+
+
+
+