{"data":{"full_name":"google/diffseg","name":"diffseg","description":"DiffSeg is an unsupervised zero-shot segmentation method using attention information from a stable-diffusion model. This repo implements the main DiffSeg algorithm and additionally includes an experimental feature to add semantic labels to the masks based on a generated caption.","stars":330.0,"forks":25.0,"language":"Jupyter Notebook","license":"MIT","archived":1.0,"subcategory":"computational-imaging-diffusion","last_pushed_at":"2024-07-09T19:01:19+00:00","pypi_package":null,"npm_package":null,"downloads_monthly":0.0,"dependency_count":0.0,"commits_30d":null,"reverse_dep_count":0.0,"maintenance_score":0.0,"adoption_score":10.0,"maturity_score":16.0,"community_score":14.0,"quality_score":40.0,"quality_tier":"emerging","risk_flags":"['archived', 'stale_6m', 'no_package', 'no_dependents']"},"meta":{"timestamp":"2026-04-08T07:11:18.937347+00:00"}}