This repository refines bounding boxes formatted for YOLO and utilizes the advanced capabilities of the Segment Anything (SAM) model to enhance the accuracy of these bounding boxes.
My environment uses python 3.9 with cuda 11.3
pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 torchaudio==0.12.1 --extra-index-url https://download.pytorch.org/whl/cu113
pip install git+https://github.com/facebookresearch/segment-anything.git
pip install -r requirements.txt
Click the links below to download the checkpoint for the corresponding model type.
defaultorvit_h: ViT-H SAM model.vit_l: ViT-L SAM model.vit_b: ViT-B SAM model.
python run.py --image_dir datasets/images --label_dir datasets/labels --refined_label_dir datasets/labels_refine --checkpoint sam_vit_h_4b8939.pth --model_type vit_h
streamlit run visualization.py