Support image similarity
Open
Nobody has claimed this yet.
- Dominant language
- Go
- Stars
- 51
- Forks
- 6
- PR merge metrics
- No merged PRs in 30d
Description
From http://manpages.ubuntu.com/manpages/bionic/man1/findimagedupes.1p.html#examples
findimagedupes compares a list of files for visual similarity.
To calculate an image fingerprint:
1) Read image.
2) Resample to 160x160 to standardize size.
3) Grayscale by reducing saturation.
4) Blur a lot to get rid of noise.
5) Normalize to spread out intensity as much as possible.
6) Equalize to make image as contrasty as possible.
7) Resample again down to 16x16.
8) Reduce to 1bpp.
9) The fingerprint is this raw image data.
To compare two images for similarity:
1) Take fingerprint pairs and xor them.
2) Compute the percentage of 1 bits in the result.
3) If percentage exceeds threshold, declare files to be similar.
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
The issue names no files, tests, or entry points. Start by locating the Go CLI's deduplication flow and image-handling code, then compare its current capabilities with the listed fingerprint and similarity steps. Done means image inputs can be compared for visual similarity using a defined threshold.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- go
- Domain
- cli, computer-vision
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100