Need to find visual/perceptual duplicate and near-duplicate photos across formats in a massive professional archive, but existing tools either crash on large collections or only detect exact byte-for-byte matches.
Existing tools fail because they either crash when scanning tens of thousands of images, can't handle cross-format perceptual duplicates (e.g., RAW + JPEG, different resolutions, slight edits), or lack efficient bulk-review workflows.
Workarounds Described
- Digging through hundreds of near-identical images manually
- Trying multiple apps that crash or fail to find cross-format duplicates
Implied Software Gaps
- Perceptual duplicate detection that works across different file formats and slight edits
- Large-archive scanning without crashing
- Efficient bulk review and deletion workflow for thousands of near-duplicates
ArchiveSweep
A high-performance duplicate photo manager designed for professionals handling massive, multi-format archives. It uses perceptual hashing and AI to detect near-duplicates across RAW, JPEG, and other formats, even with size or edit variations, and provides a non-destructive review workflow. Built for speed and stability, it handles 100k+ image libraries without crashing.
- Visual/perceptual duplicate detection using AI models and perceptual hashing, not just byte comparison
- Cross-format matching (RAW, JPEG, PNG, TIFF, etc.) with adjustable similarity threshold
- Bulk review interface with side-by-side comparison, smart auto-marking, and batch deletion/move actions
- Resumable, crash-proof scanning engine that checkpoints progress and works on 100k+ image libraries
- Metadata-aware grouping (by capture time, camera model, burst sequence) to reduce false positives
Existing Solutions Mentioned
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