Show HN: I made a Mac app to search my images and videos locally with ML

Original Article ↗ Hacker News Discussion ↗

App concept & core capabilities

  • Desktop app to semantically search local images and videos using ML embeddings (CLIP).
  • Works fully offline; developer states media never leaves the machine.
  • Videos are sampled into frames (about 1 frame/sec), resized (e.g., 256×256), embedded into 512‑dim float32 vectors for search.
  • Current focus is on semantic/visual search rather than exact text or filename search.

Local ML, privacy, and performance

  • Multiple comments appreciate that it is 100% local, one‑time purchase software.
  • Some worry about model size and resulting large app footprint.
  • Indexing reportedly takes “a few minutes” depending on library size; optimization is ongoing.
  • Users request very explicit guarantees that nothing is sent over the network.

Platform, tech stack, and “Mac app” debate

  • App is built with Electron. This sparks a heated debate:
    • Some argue Electron apps are still “Mac apps” (they run on macOS, easy cross‑platform).
    • Others say Electron apps feel alien on macOS and don’t meet Apple’s HIG expectations.
  • Cross‑platform potential is viewed positively; Windows and Linux versions are in progress.

Overlap with existing tools

  • Comparisons to Spotlight, Photos, Screenie, Immich, and other tools.
  • Spotlight in newer macOS versions has some visual and OCR search, but:
    • It’s seen as limited in “concept”/semantic search and inconsistent in practice.
    • Desktop Docs is perceived as more focused on rich semantic media search.
  • Apple Photos already does strong people recognition, but some don’t want iCloud or Photos lock‑in.

Requested features / roadmap

  • Popular asks:
    • Text/PDF indexing, semantic text search.
    • Facial recognition and user‑taggable people (e.g., “grandma and uncle together”).
    • Near‑duplicate detection and smarter photo culling (blur, eyes closed).
    • Metadata‑based queries (camera model, resolution, SD/HD/4K) and richer tagging.
    • NAS support, Umbrel/Nextcloud/ownCloud integration.
  • Developer indicates many of these are “on the roadmap” and may be prioritized by interest.

Pricing, trials, and refunds

  • One‑time price currently around $24.99; previously higher prices caused confusion.
  • License includes future upgrades.
  • No trial version; several users say a time‑limited or image‑limited trial is essential.
  • Non‑refundable policy draws concern; others note chargebacks and goodwill as practical constraints.

UI/UX and marketing feedback

  • Suggestions:
    • Emphasize “local ML” rather than generic “AI” to build trust.
    • Clearer landing page with more screenshots/video demos.
    • Persistent “Buy” button instead of scattering CTAs.
  • Overall sentiment: interesting, useful idea with strong enthusiasm, tempered by concerns about Electron, overlap with Apple’s tools, lack of trial, and feature gaps.