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https://github.com/vmchale/phash
Perceptual hashing command-line tool
https://github.com/vmchale/phash
command-line-tool deduplication duplication-detection duplication-finder haskell perceptual-hash phash
Last synced: about 2 months ago
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Perceptual hashing command-line tool
- Host: GitHub
- URL: https://github.com/vmchale/phash
- Owner: vmchale
- License: bsd-3-clause
- Created: 2019-06-23T18:01:05.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2024-04-12T18:37:05.000Z (9 months ago)
- Last Synced: 2024-04-13T02:31:23.611Z (9 months ago)
- Topics: command-line-tool, deduplication, duplication-detection, duplication-finder, haskell, perceptual-hash, phash
- Language: Haskell
- Size: 3.51 MB
- Stars: 15
- Watchers: 4
- Forks: 1
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
Awesome Lists containing this project
README
# phash
This is a Haskell [library](http://hackage.haskell.org/package/perceptual-hash)
to detect (potential) duplicate images.
It also contains a command-line tool.
- [Use](#use)
- [Installation](#installation)
- [Pre-Built Release](#pre-built-release)
- [Source](#source)
- [Library](#library)
- [Performance](#performance)
- [Foreign Library](#foreign-library)
- [ATS Bindings](#ats-bindings)
## Use
Use it on one or more directories:
```
phash ~/Pictures ~/Downloads
~/Pictures/frog.jpeg, ~/Downloads/frog.png
```
## Installation
### Pre-Built Release
For many platforms, you can find binaries [here](https://www.permanent.org/p/archive/0236-0000/0236-0019/410841).
### Source
Download [cabal-install](https://www.haskell.org/cabal/download.html) and
[GHC](https://www.haskell.org/ghc/download.html). Then:
```
cabal install perceptual-hash --constraint='hip +disable-chart'
```
## Library
You can find library documentation on
[Hackage](https://hackage.haskell.org/package/perceptual-hash).
### Performance
This library has performs better on WebP, AVIF images and worse on JPEG images compared to the pHash library.
```
benchmarking fileHash/cat.png
time 21.50 ms (21.23 ms .. 21.70 ms)
1.000 R² (0.999 R² .. 1.000 R²)
mean 21.54 ms (21.39 ms .. 21.88 ms)
std dev 525.3 μs (224.2 μs .. 946.8 μs)
benchmarking fileHash/frog.jpeg
time 21.33 ms (20.57 ms .. 22.01 ms)
0.997 R² (0.996 R² .. 0.999 R²)
mean 19.84 ms (19.53 ms .. 20.24 ms)
std dev 822.7 μs (654.3 μs .. 1.070 ms)
variance introduced by outliers: 13% (moderately inflated)
benchmarking fileHash/frog.png
time 12.31 ms (11.88 ms .. 12.66 ms)
0.997 R² (0.994 R² .. 0.999 R²)
mean 12.46 ms (12.34 ms .. 12.58 ms)
std dev 314.3 μs (256.0 μs .. 385.0 μs)
benchmarking fileHash/liz-taylor.webp
time 69.02 ms (68.00 ms .. 70.23 ms)
0.999 R² (0.997 R² .. 1.000 R²)
mean 71.69 ms (70.28 ms .. 74.98 ms)
std dev 3.688 ms (1.345 ms .. 6.107 ms)
variance introduced by outliers: 16% (moderately inflated)
benchmarking fileHash/liz-taylor.png
time 72.32 ms (70.35 ms .. 74.49 ms)
0.998 R² (0.996 R² .. 1.000 R²)
mean 73.83 ms (72.60 ms .. 75.38 ms)
std dev 2.414 ms (1.655 ms .. 3.614 ms)
benchmarking fileHash/fashion.png
time 142.0 ms (131.6 ms .. 153.4 ms)
0.997 R² (0.991 R² .. 1.000 R²)
mean 145.8 ms (142.0 ms .. 153.9 ms)
std dev 7.690 ms (2.694 ms .. 11.43 ms)
variance introduced by outliers: 13% (moderately inflated)
benchmarking fileHash/fashion.avif
time 172.2 ms (161.5 ms .. 187.6 ms)
0.996 R² (0.991 R² .. 1.000 R²)
mean 175.1 ms (169.3 ms .. 185.3 ms)
std dev 12.16 ms (5.052 ms .. 18.42 ms)
variance introduced by outliers: 13% (moderately inflated)
benchmarking foreignHash/cat.png
time 21.06 ms (20.88 ms .. 21.19 ms)
1.000 R² (0.999 R² .. 1.000 R²)
mean 20.94 ms (20.80 ms .. 21.06 ms)
std dev 320.2 μs (225.5 μs .. 418.3 μs)
benchmarking foreignHash/frog.jpeg
time 9.255 ms (9.168 ms .. 9.378 ms)
0.999 R² (0.999 R² .. 1.000 R²)
mean 9.234 ms (9.201 ms .. 9.273 ms)
std dev 94.68 μs (79.14 μs .. 120.7 μs)
benchmarking foreignHash/frog.png
time 10.37 ms (10.28 ms .. 10.47 ms)
0.999 R² (0.999 R² .. 1.000 R²)
mean 10.42 ms (10.37 ms .. 10.48 ms)
std dev 135.4 μs (106.5 μs .. 184.9 μs)
benchmarking foreignHash/liz-taylor.webp
time 368.7 ms (352.4 ms .. 391.1 ms)
1.000 R² (0.999 R² .. 1.000 R²)
mean 362.3 ms (357.6 ms .. 366.4 ms)
std dev 5.133 ms (1.154 ms .. 6.530 ms)
variance introduced by outliers: 19% (moderately inflated)
benchmarking foreignHash/liz-taylor.png
time 71.58 ms (71.12 ms .. 72.03 ms)
1.000 R² (1.000 R² .. 1.000 R²)
mean 71.84 ms (71.66 ms .. 72.24 ms)
std dev 502.0 μs (339.8 μs .. 710.2 μs)
benchmarking foreignHash/fashion.png
time 162.1 ms (160.6 ms .. 162.8 ms)
1.000 R² (1.000 R² .. 1.000 R²)
mean 163.4 ms (162.9 ms .. 164.3 ms)
std dev 990.0 μs (544.6 μs .. 1.476 ms)
variance introduced by outliers: 12% (moderately inflated)
benchmarking foreignHash/fashion.avif
time 705.5 ms (669.6 ms .. 757.2 ms)
0.999 R² (0.998 R² .. 1.000 R²)
mean 716.4 ms (710.3 ms .. 728.3 ms)
std dev 11.54 ms (1.129 ms .. 13.84 ms)
variance introduced by outliers: 19% (moderately inflated)
```
### Foreign Library
This package contains a foreign library and a [header
file](https://hackage.haskell.org/package/perceptual-hash/src/include/hs_phash.h)
#### ATS Bindings
Because of the foreign library, `hs_phash` can be used in ATS as well. ATS users
of the library may be interested in [hs-bind](https://github.com/vmchale/hs-bind).