Finding duplicate photos on iPhone without uploading a single one

ZoomApps — Mon, 26 Oct 2026 17:22:05 +0000

Most photo cleaners send your library somewhere or lock the useful part behind a weekly subscription. We wanted the opposite for our app, Fast Cleaner: everything runs on the iPhone, and the free tier covers a normal daily cleanup. Here is how the duplicate finder works and what we learned shipping it to 50 languages.

1. One embedding per photo with Apple Vision

VNGenerateImageFeaturePrintRequest returns a feature vector for an image. Two photos of the same scene end up close to each other, even with small changes in framing or exposure.

let request = VNGenerateImageFeaturePrintRequest()
let handler = VNImageRequestHandler(cgImage: thumb, options: [:])
try handler.perform([request])
let print = request.results?.first as? VNFeaturePrintObservation

We request a 160×160 thumbnail from PhotoKit instead of the full image. Vision resamples to its own input size anyway, and the smaller request loads about 30% faster. Embeddings are cached on the device, so the second scan only processes new photos.

2. Compare only what can be similar

Comparing every photo with every other one is O(n²). On a 50,000-photo library that is far too slow. We bucket photos by the month they were taken and compare pairs inside a bucket. Duplicates and burst-like series are almost always taken close in time.

var d: Float = 0
try a.computeDistance(&d, to: b)
if d <= 0.3 { unionFind.union(i, j) }

A distance threshold of 0.3 gave the best balance between "same moment" and "similar but different". Union-find turns the pairs into groups.

3. Pick the best shot, offer the rest

Inside each group a simple weighted score picks the photo to keep:

face capture quality (VNDetectFaceCaptureQualityRequest): 0.35
sharpness, Laplacian variance on luminance: 0.30
resolution, log-scaled: 0.15
open eyes and smile from face landmarks: 0.15
newer date as a tiebreak: 0.05

Photos without faces get a neutral face score, so landscapes are not penalised.

4. Things that bit us

Memory. Batches of 50 images inside autoreleasepool, otherwise large libraries run out of memory.
The simulator lies. In the iOS simulator Vision returned the same vector for every image, so all distances were 0 and every photo landed in one group. We now detect "collapsed" embeddings (different sizes, distance exactly 0) and skip such buckets.
Main thread. Reading the photo library during view rendering caused watchdog kills on big libraries. All PhotoKit reads moved off the main thread.
Deletion safety. Deletions go through PhotoKit, so everything lands in Recently Deleted for 30 days.

Pricing without a weekly plan

Scanning, the report, swipe-to-clean and up to 300 MB of cleanup a day are free. Pro removes the limit and adds video compression: $1.99/month (first month $0.99), $9.99/year or $19.99 once.