{"adoption": {"forks": 659, "observed_at": "2026-08-28T04:10:02.503775+00:00", "stars": 7703}, "canonical_url": "https://ross.abutalabs.com/products/inpaint-anything", "card": {"archived": false, "artifact_type": "library", "description": "Inpaint anything using Segment Anything and inpainting models.", "domain": ["image-processing", "computer-vision", "artificial-intelligence", "robotics"], "enriched": true, "function": ["image-processing", "machine-learning", "computer-vision", "video-processing"], "health_score": 79, "homepage": null, "language": "Jupyter Notebook", "license": "Apache-2.0", "license_family": "permissive", "maturity": "active", "member_repos": ["geekyutao/Inpaint-Anything"], "name": "geekyutao/Inpaint-Anything", "platform": ["python", "cross-platform"], "pushed_at": "2026-08-22T04:47:40+00:00", "repo": "geekyutao/Inpaint-Anything", "stars": 7703, "tags": ["inpainting", "segment-anything", "stable-diffusion", "lama", "object-removal", "image-editing", "video-inpainting", "3d-scenes", "sdxl", "egocentric-video", "gpu"], "topics": [], "urls": [], "use_cases": ["remove unwanted objects from photos by clicking on them", "fill a masked region with content described by a text prompt", "replace the background of an object in an image", "inpaint missing regions across video frames", "erase human hands from egocentric video for robot learning datasets", "inpaint textures in 3D scenes"], "what_it_is": "Inpaint Anything combines Segment Anything (SAM) with inpainting models like LaMa and Stable Diffusion to remove, fill, or replace objects in images, videos, and 3D scenes via a simple click. A newer beta branch modernizes the stack with SAM 3, SDXL, and ProPainter, adding text-prompted object selection and hand-removal tooling for robotics data pipelines.", "when_to_avoid": ["you need a polished GUI product rather than Python scripts and notebooks", "you lack a GPU or cannot meet CUDA/PyTorch requirements of the newer models", "you need the NeRF-based 3D pipeline verified end-to-end (still unverified in the beta branch)"], "when_to_choose": ["you need click-based or text-based object removal/filling in images or videos", "you want to combine SAM segmentation with LaMa or Stable Diffusion inpainting", "you are preparing egocentric robot-learning data and need hand removal with masks"]}, "data_as_of": "2026-08-30T08:39:29.467469+00:00", "members": [{"path": "/products/inpaint-anything", "repo": "geekyutao/Inpaint-Anything", "role": "main", "score": 65}], "provenance": {"archived": {"kind": "observed", "observed_at": "2026-08-28T04:10:02.503775+00:00", "source": "github"}, "artifact_type": {"confidence": null, "enriched_at": "2026-08-29T17:35:27.192514+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "74194e59ab8bfc8d88a65f428f08c99f63b0e60de9f0500a398b7862b9e61ae5", "fetched_at": "2026-08-28T04:10:02.503775+00:00", "kind": "readme", "missing": false, "url": "https://github.com/geekyutao/Inpaint-Anything"}], "taxonomy_version": 1}, "description": {"kind": "observed", "observed_at": "2026-08-28T04:10:02.503775+00:00", "source": "github"}, "domain": {"confidence": null, "enriched_at": "2026-08-29T17:35:27.192514+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "74194e59ab8bfc8d88a65f428f08c99f63b0e60de9f0500a398b7862b9e61ae5", "fetched_at": "2026-08-28T04:10:02.503775+00:00", "kind": "readme", "missing": false, "url": "https://github.com/geekyutao/Inpaint-Anything"}], "taxonomy_version": 1}, "enriched": {"inputs": [], "kind": "computed", "method": "enrichment_status"}, "function": {"confidence": null, "enriched_at": "2026-08-29T17:35:27.192514+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "74194e59ab8bfc8d88a65f428f08c99f63b0e60de9f0500a398b7862b9e61ae5", "fetched_at": "2026-08-28T04:10:02.503775+00:00", "kind": "readme", "missing": false, "url": "https://github.com/geekyutao/Inpaint-Anything"}], "taxonomy_version": 1}, "health_score": {"inputs": ["days_since_push", "days_since_release", "archived"], "kind": "computed", "method": "health_v1"}, "homepage": {"kind": "observed", "observed_at": "2026-08-28T04:10:02.503775+00:00", "source": "github"}, "language": {"kind": "observed", "observed_at": "2026-08-28T04:10:02.503775+00:00", "source": "github"}, "license": {"kind": "observed", "observed_at": "2026-08-28T04:10:02.503775+00:00", "source": "github"}, "license_family": {"inputs": ["license"], "kind": "computed", "method": "license_family"}, "maturity": {"confidence": null, "enriched_at": "2026-08-29T17:35:27.192514+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "74194e59ab8bfc8d88a65f428f08c99f63b0e60de9f0500a398b7862b9e61ae5", "fetched_at": "2026-08-28T04:10:02.503775+00:00", "kind": "readme", "missing": false, "url": "https://github.com/geekyutao/Inpaint-Anything"}], "taxonomy_version": 1}, "member_repos": {"kind": "observed", "observed_at": "2026-08-28T04:10:02.503775+00:00", "source": "github"}, "name": {"kind": "observed", "observed_at": "2026-08-28T04:10:02.503775+00:00", "source": "github"}, "platform": {"confidence": null, "enriched_at": "2026-08-29T17:35:27.192514+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "74194e59ab8bfc8d88a65f428f08c99f63b0e60de9f0500a398b7862b9e61ae5", "fetched_at": "2026-08-28T04:10:02.503775+00:00", "kind": "readme", "missing": false, "url": "https://github.com/geekyutao/Inpaint-Anything"}], "taxonomy_version": 1}, "pushed_at": {"kind": "observed", "observed_at": "2026-08-28T04:10:02.503775+00:00", "source": "github"}, "repo": {"kind": "observed", "observed_at": "2026-08-28T04:10:02.503775+00:00", "source": "github"}, "stars": {"kind": "observed", "observed_at": "2026-08-28T04:10:02.503775+00:00", "source": "github"}, "tags": {"confidence": null, "enriched_at": "2026-08-29T17:35:27.192514+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "74194e59ab8bfc8d88a65f428f08c99f63b0e60de9f0500a398b7862b9e61ae5", "fetched_at": "2026-08-28T04:10:02.503775+00:00", "kind": "readme", "missing": false, "url": "https://github.com/geekyutao/Inpaint-Anything"}], "taxonomy_version": 1}, "topics": {"kind": "observed", "observed_at": "2026-08-28T04:10:02.503775+00:00", "source": "github"}, "urls": {"kind": "observed", "observed_at": "2026-08-28T04:10:02.503775+00:00", "source": "github"}, "use_cases": {"confidence": null, "enriched_at": "2026-08-29T17:35:27.192514+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "74194e59ab8bfc8d88a65f428f08c99f63b0e60de9f0500a398b7862b9e61ae5", "fetched_at": "2026-08-28T04:10:02.503775+00:00", "kind": "readme", "missing": false, "url": "https://github.com/geekyutao/Inpaint-Anything"}], "taxonomy_version": 1}, "what_it_is": {"confidence": null, "enriched_at": "2026-08-29T17:35:27.192514+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "74194e59ab8bfc8d88a65f428f08c99f63b0e60de9f0500a398b7862b9e61ae5", "fetched_at": "2026-08-28T04:10:02.503775+00:00", "kind": "readme", "missing": false, "url": "https://github.com/geekyutao/Inpaint-Anything"}], "taxonomy_version": 1}, "when_to_avoid": {"confidence": null, "enriched_at": "2026-08-29T17:35:27.192514+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "74194e59ab8bfc8d88a65f428f08c99f63b0e60de9f0500a398b7862b9e61ae5", "fetched_at": "2026-08-28T04:10:02.503775+00:00", "kind": "readme", "missing": false, "url": "https://github.com/geekyutao/Inpaint-Anything"}], "taxonomy_version": 1}, "when_to_choose": {"confidence": null, "enriched_at": "2026-08-29T17:35:27.192514+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "74194e59ab8bfc8d88a65f428f08c99f63b0e60de9f0500a398b7862b9e61ae5", "fetched_at": "2026-08-28T04:10:02.503775+00:00", "kind": "readme", "missing": false, "url": "https://github.com/geekyutao/Inpaint-Anything"}], "taxonomy_version": 1}}, "score": {"components": {"activity": 99, "longevity": 88, "rhythm": 8}, "computed_at": "2026-09-02T17:46:02.011165+00:00", "flags": [], "formula": "round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)", "inputs": {"age_days": 1242, "days_push": 11, "days_rel": null, "gap_med": null, "n_releases_24m": 0}, "score": 65, "version": 2}, "staleness": {"enrichment_outdated": false, "low_confidence": false, "scrape_days": 9, "stale_scrape": false}}