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leony
leony

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I Built a Brush-Based AI Photo Eraser (People, Objects, Text, Watermarks)

I’m leony, an indie maker. I kept wanting a small, focused flow for cleaning a photo: paint over the distraction, let AI rebuild that patch from the surrounding scene, download, done. Full design suites are overkill for that, and generic “generate a new image” tools don’t preserve the rest of the frame the way a local erase-and-fill does.

So I built RemoveGenie — a brush-based AI photo eraser for people, objects, text, watermarks, and stickers.

How the brush + fill works

The product loop is intentionally short:

  1. Upload a JPG, PNG, or WebP (up to 20 MB).
  2. Paint a red mask over what you want gone. Undo, Clear, and a brush-size slider are there when the first pass is messy.
  3. Sign in with Google and submit when the cost/credits look right.
  4. The model reconstructs the masked region from context around it. Covered pixels are generated, not recovered from under the object.
  5. Download a PNG. Large inputs are resized so the longest edge is at most 1536 px — check dimensions before anything print-related.

That “generated, not recovered” line matters. If a tourist’s head covered a storefront sign, you get a plausible wall or window, not the real letters that were behind them.

What I use it for

Same editor, six focused tool pages so the intent is obvious:

  • People — strangers in a coastal portrait, photobombers on a trip shot (remove people from photo).
  • Objects — a cyclist at the edge of a street frame, clutter on a desk (AI object remover).
  • Text — burned-in captions, date stamps, a few short words on an image.
  • Watermarks — only on images you have the right to edit. Removing a mark does not transfer copyright.
  • Stickers / emojis — overlays on screenshots or shared photos.
  • Magic eraser — the same brush/fill loop when you just want “erase this blob.”

Include shadows and reflections in the mask when you can; the model does not reliably invent unmarked ones.

Honest limits (so you don’t burn credits)

  • Login to submit. You can prepare the mask first, but Google sign-in is required to run a removal.
  • 16 credits per removal. New accounts get 16 credits (enough for one try), valid 30 days. Confirmed failed tasks are refunded automatically per the site FAQ.
  • PNG out, resized. Expect a PNG download and the 1536 px long-edge cap — not print-archive fidelity.
  • Area size. It works best when the erase region is under roughly a third of the frame. Huge masks leave the model with too little context and tend to fail or look muddy.
  • Not OCR, not recovery. Text removal does not extract wording for you, and stickers/blurs over faces or copy cannot reveal the real hidden detail — only a plausible fill.
  • Checkout. One-time credit packs are listed on the pricing page; as of early October 2026 buy buttons could show checkout unavailable. Don’t plan a paid run until checkout is live for your account.

Try it

Product home: https://removegenie.com/

Owned repo: https://github.com/wayperlee/removegenie

If you clean travel portraits or marketing stills often, I’d love feedback on edge cases — crowded overlaps, tiny wires on busy backgrounds, and dense UI screenshots are the hardest for me right now.

Top comments (1)

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wolf2016 profile image
wolf Valencia •

Brush-based erasers live or die on whether people trust every pixel you ship, and splitting it into people, objects, text and watermarks makes the use cases obvious.

One thing that came up when I ran removegenie.com through the automated checks I use in my Staff SDET work (it scored 89/100 (B)): the /remove-people-from-photo page links to /blog/how-to-remove-people-from-a-photo, and that URL returns a 404. That's probably your highest-intent landing page, so publishing the post or repointing the link at an existing guide closes the dead end before someone bounces.

Beyond that, the run flagged 7 smaller warnings. Glad to pass the rest along if that's useful.