Status: done training, creating docker and client webserver
The model detect the abnormalities in chest-Xray image by Detectron2 - Pytorch.
- Create virtual environment.
conda create -n chestxrayv2 python=3.7
conda activate chestxrayv2
- clone this repository.
- Install required packages.
pip install -r requirements.txt
- Setup Detectron2.
See installation instructions. Or see my instructions.
See the document for understanding how we process the chest-Xray dataset from VinBigdata.
- Download the standard and additional data after processing.
bash download_data_standard_add.sh
You can run file streamlit_.py for exploring the dataset in eda/ or nms-wbf-visualize/ .
Note: Need to configure config/streamlit_eda.yaml file.
You can download our model with 5 classes
- Download pretrain model with best mAP50 after 5000 epochs.
python experiments-records/download_5_classes_model.py
python train.py
You need configure traininig in config/train.yaml.
python eval.py
You need configure evaluating in config/inference.yaml.
streamlit run streamlit_inference.py
You need configure evaluating in config/inference.yaml.