Find duplicate photos
The same picture at three sizes has three checksums and one appearance.
A checksum finds files that are byte-identical, which duplicate photos almost never are. The same picture saved as JPG and PNG, or at full size and again as a thumbnail, is four different checksums and one photograph. This compares how images look.
How it compares
- Each image is reduced to a tiny greyscale grid.
- Each cell is recorded as lighter or darker than the average.
- That pattern survives resizing, re-encoding and format changes.
- Images with near-identical patterns are grouped together.
What it catches that a checksum misses
- The same photo saved as both JPG and PNG.
- A full-size photo and its thumbnail.
- A photo re-saved by a messaging app at lower quality.
- The same image exported twice at different quality settings.
Deciding what to keep
- Each group is shown in full, with the largest marked as the one worth keeping.
- Nothing is deleted, moved or altered — the tool reports and stops there.
- What happens next is yours to do, in your own file manager.
When it gets it wrong
- A loose tolerance will group two photographs taken seconds apart.
- A tight one will miss a heavily re-compressed copy of the same picture.
- Both are visible in the groups, which is exactly why it shows them rather than acting.
Questions
How do I find duplicate photos that are not identical files?
Compare appearance rather than bytes. A perceptual hash reduces each image to a small pattern of light and dark, which survives resizing and re-encoding.
Does it delete anything?
No. It groups duplicates and suggests which copy to keep, the largest one. Deleting is always your decision, made in your own file manager.
Is this the same as a checksum?
No, and that is the point. A checksum changes completely if one pixel changes, so it never finds a resized or re-saved copy of the same photo.