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configs/multilabelseg/uwmgi/README.md

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+# Multi-label Semantic Segmentation with UWMGI Dataset 
+
+### Preparation
+* Install PaddlePaddle and relative environments based on the [installation guide](https://www.paddlepaddle.org.cn/en/install/quick?docurl=/documentation/docs/en/install/pip/linux-pip_en.html).
+* Install PaddleSeg based on the [reference](../../../docs/install.md).
+* Download the UWMGI dataset and link to PaddleSeg/data. 
+
+```shell
+wget https://bj.bcebos.com/v1/ai-studio-online/01c05a320b8745ca9985a7e62f12286a8b6f985a36e643eca1fb2b6f29fa21c7?responseContentDisposition=attachment%3B%20filename%3DUWMGI.zip&authorization=bce-auth-v1%2F5cfe9a5e1454405eb2a975c43eace6ec%2F2023-09-10T11%3A24%3A21Z%2F-1%2F%2F37523e8456373c755318dee5d7a109f30681185f60ebef593cffbec8f3cf23f6
+mkdir -p data/
+unzip UWMGI.zip -d data/
+```
+
+```
+PaddleSeg/data
+├── UWMGI
+│   ├── images
+│   │   ├── ......
+│   ├── annotations
+│   │   ├── train.json
+│   │   ├── val.json
+│   │   ├── ......
+```
+
+### Training
+You can start training by assign the ```tools/train.py``` with config files, the config files are under ```PaddleSeg/configs/multilabelseg/uwmgi```. Details about training are under [training guide](../../../docs/train/train.md). You can find the trained models under ```Paddleseg/save_dir/best_model/model.pdparams```
+
+```bash
+# multi-gpu
+export CUDA_VISIBLE_DEVICES=0,1
+python3 -m paddle.distributed.launch tools/train.py \
+    --config configs/multilabelseg/uwmgi/pp_mobileseg_tiny_uwmgi_512x512_80k.yml \
+    --save_dir output/pp_mobileseg_tiny_uwmgi_512x512_80k \
+    --save_interval 1000 \
+    --num_workers 8 \
+    --log_iters 100 \
+    --use_ema \
+    --do_eval \
+    --use_vdl
+
+# single-gpu
+python3 -m tools/train.py \
+    --config configs/multilabelseg/uwmgi/pp_mobileseg_tiny_uwmgi_512x512_80k.yml \
+    --save_dir output/pp_mobileseg_tiny_uwmgi_512x512_80k \
+    --save_interval 1000 \
+    --num_workers 8 \
+    --log_iters 100 \
+    --use_ema \
+    --do_eval \
+    --use_vdl
+```
+
+### Validation
+With the trained model on hand, you can verify the model's accuracy through evaluation. Details about evaluation are under [evaluation guide](../../../docs/evaluation/evaluate.md).
+
+```bash
+# multi-gpu
+export CUDA_VISIBLE_DEVICES=0,1
+python3 -m paddle.distributed.launch tools/val.py \
+    --config configs/multilabelseg/uwmgi/pp_mobileseg_tiny_uwmgi_512x512_80k.yml \
+    --model_path output/pp_mobileseg_tiny_uwmgi_512x512_80k/best_model/model.pdparams
+
+# single-gpu
+python3 tools/val.py \
+    --config configs/multilabelseg/uwmgi/pp_mobileseg_tiny_uwmgi_512x512_80k.yml \
+    --model_path output/pp_mobileseg_tiny_uwmgi_512x512_80k/best_model/model.pdparams
+```
+
+### Inference
+With the trained model on hand, you can use the model to predict and visualize images. Details about inference are under [inference guide](../../../docs/predict/predict.md).
+
+```bash
+python tools/predict.py \
+       --config configs/multilabelseg/uwmgi/pp_mobileseg_tiny_uwmgi_512x512_80k.yml \
+       --model_path output/pp_mobileseg_tiny_uwmgi_512x512_80k/best_model/model.pdparams \
+       --image_path data/UWMGI/images/case147_day14_slice_0095.png \
+       --save_dir output/result \
+       --use_multilabel
+```