Ross ROSS = Recommend OSS · open-source software intelligence for agents

chn-lee-yumi/MaterialSearch

Semantic search. Search local photos and videos through natural language. AI语义搜索本地素材。以图搜图、查找本地素材、根据文字描述匹配画面、视频帧搜索、根据画面描述搜索视频。 observed · 2026-08-28

github.com/chn-lee-yumi/MaterialSearch · homepage · HTML · GPL-3.0 (copyleft) observed · 2026-08-28

Health v2 · maintenance only

73/100

  • Activity 83
  • Release rhythm 51
  • Longevity 90
How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.

  • gap_med: 92
  • age_days: 1266
  • days_rel: 167
  • days_push: 102
  • n_releases_24m: 2

Full methodology

Adoption not part of the score

1949 stars · 217 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

MaterialSearch is a self-hosted semantic search tool that indexes local photos and videos using a CLIP multimodal model, letting users find media via natural-language text or by example images. It runs fully offline with a browser-based front-end and a Python core available as a pip package.

Use cases

  • find local photos by describing them in text
  • reverse image search across my local photo library
  • search videos by describing the scene
  • find which video a screenshot came from
  • locate video clips matching a text description
  • index my NAS photo and video collection for semantic search

When to choose

  • you have a large local media library and no organized tags or filenames
  • you need fully offline, privacy-preserving media search
  • you want both text-to-image and image-to-video reverse search
  • you want a Docker or Windows bundle deployment on a PC or NAS

When to avoid

  • you need cloud-scale or multi-user hosted search
  • you require OCR or text-in-image search rather than visual semantics
  • you need a fully open-source API implementation (the API layer is not open-source)
  • you cannot run GPU or reasonably fast CPU inference for indexing

Facets

application · maturity active

search-engine image-processing video-processing machine-learning http-server image-processing artificial-intelligence self-hosted media windows self-hosted python semantic-search clip reverse-image-search local-photos video-frame-search privacy-first multimodal video search linux docker web-server

2 sources

Member repositories

RepositoryRoleHealth v2
chn-lee-yumi/MaterialSearchmain73

For agents

markdown · JSON · MCP: product_card(name="chn-lee-yumi/MaterialSearch")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem