GETTING_STARTED.md

Getting Started with Matcher

Prepare models

Download the model weights of DINOv2, SAM and Semantic-SAM, and organize them as follows.

models/
    dinov2_vitl14_pretrain.pth
    sam_vit_h_4b8939.pth
    swint_only_sam_many2many.pth

Test One-shot Semantic Segmentation

You can test one-shot semantic segmentation performance of Matcher on COCO-20ⁱ, run:

python main_oss.py  \
    --benchmark coco \
    --nshot 1 \
    --max_sample_iterations 64 \
    --box_nms_thresh 0.65 \
    --sample-range "(1,6)" \
    --topk_scores_threshold 0.0 \
    --use_dense_mask 1 \
    --use_points_or_centers \
    --purity_filter 0.02 \
    --iou_filter 0.85 \
    --multimask_output 1 \
    --sel_stability_score_thresh 0.90 \
    --use_score_filter \
    --alpha 1.0 --beta 0. --exp 0. \
    --num_merging_mask 9  \
    --fold 0 --log-root "output/coco/fold0"

• You can replace --benchmark coco with --benchmark lvis to test LVIS-92ⁱ.
• You can replace --nshot 1 with --nshot 5 and replace --num_merging_mask 9 with --num_merging_mask 5 to test 5-shot performance on COCO-20ⁱ.
• You can find more commands in scripts/ for other datasets.

Gradio Demo

Launch the local demo built with gradio:

python app.py