
MacPaw Gemini 2
PhotoSweeper
dupeGuru
Czkawka
Duplicate Photos Fixer
Image Comparer
SoftOrbits Duplicate Photo Finder
Duplicate and blurry photos, found locally. Nothing else.

Compute various size metrics for a Git repository, flagging those that might cause problems - github/git-sizer

Which is more popular?
Based on our record, git-sizer seems to be more popular. It has been mentioned 1 time since March 2021.
Website, pricing, platforms and company facts side by side.
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| Website | skimrr.com | github.com |
| Pricing | — | |
| Platforms | — | |
| Company | Startup from France · 2026 | — |
| Listed in |
In their own words, as submitted to SaaSHub.


Skimrr finds duplicate photos and blurry shots in a folder — entirely on your computer. What it does Duplicates: exact copies matched by hash, plus near-duplicates (cropped, recompressed, lightly edited) matched by what the picture actually looks like. Similarity threshold adjustable live. Blur:...
No description of git-sizer yet.
What each product offers, as listed by its team.


Possible disadvantages
An editorial look at what each product does well and who it suits.


No analysis of Skimrr yet.
Overall verdict
Why this product is good
Recommended for
Walkthroughs and reviews on video.
How to Delete Duplicate & Blurry Photos FAST (2026)
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How often each product is chosen within a category, 0–100% relative to the other.


As answered by people managing Skimrr and git-sizer.
Skimrr's answer
It grew out of a very ordinary problem: the photo folder nobody opens, years of imports nobody sorted, full of duplicates and near-misses nobody's confident enough to delete by hand. (There's a longer writeup on this: https://medium.com/@admin_53263/the-folder-nobody-opens-1b897eb33eed)
Skimrr's answer
Most duplicate-finder tools either ask you to upload photos to a cloud service, rely purely on hashing (missing edited near-duplicates or flagging unrelated similar shots), or use a one-size-fits-all blur cutoff that misfires constantly. Skimrr keeps everything on your machine, adds a local vision-model sanity check most competitors skip entirely, and never deletes anything without a review grid and an undo-able trash.
Skimrr's answer
Every proposed duplicate group is checked by an on-device vision model before it's shown, not just matched by hash, so near-duplicates (cropped, recompressed, lightly edited) get caught without a flood of false positives. The blur score is calibrated per-folder rather than using a fixed threshold, so a soft-focus portrait or a busy, detailed scene doesn't get misjudged. Everything runs 100% locally in Rust, with no account, no cloud, no telemetry, and nothing is ever deleted outright: files go to a reversible local trash first.
Skimrr's answer
Tauri 2 and Rust for the desktop app and the core scanning, hashing, and clustering engine; a local MobileNetV2 ONNX model run through Candle (a pure-Rust ML framework, keeping the whole app free of Python or native ML dependencies) for duplicate verification; and React with TypeScript and i18next for the six-language UI.
Skimrr's answer
People sitting on large personal photo libraries built up over years, with multiple phones, cameras, and import sessions, who want to reclaim disk space without handing their personal photos to a cloud service. Photography enthusiasts, people who regularly import from SD cards, and anyone privacy-conscious about where their photos go.
Share your experience with using Skimrr and git-sizer. For example, how are they different and which one is better?
Recommendations tracked on public social media and blogs since March 2021.


Tracking Skimrr since Aug 2026.
Also there’s a cool project from GitHub you can use to help understand the size of git’s objects in your git repo https://github.com/github/git-sizer. This might help you determine what the best cloning strategy could be. Source: almost 5 years ago
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