dHash and IDHash gem powered by ruby-vips
The dHash is the algorithm of image fingerprinting that can be used to measure the similarity of two images.
The IDHash is the new algorithm that has some improvements over dHash -- I'll describe it further.
You can read about the dHash and perceptual hashing in the article "Kind of Like That" at "The Hacker Factor Blog" (21 January 2013). The idea is that you resize the original image to 8x9 and then convert it to 8x8 array of bits -- each tells if the corresponding segment of the image is brighter or darker than the one on the right (or left). Then you apply the Hamming distance to such arrays to measure how much they are different.
There were several Ruby implementations on Github already but they all depended on ImageMagick. My implementation takes an advantage of speed of the libvips (the
ruby-vips gem) -- it fingerprints images much faster. For even more speed the fingerprint comparison function is implemented as native C extension.
IDHash (the Important Difference Hash)
The main improvement over the dHash is what makes it insensitive to the resizing algorithm and possible errors due to color scheme conversion.
- The "Importance" is an array of extra 64 bits that tells the comparing function which half of 64 bits is important (when the difference between neighbors was enough significant) and which is not. So not every bit in a fingerprint is being compared but only half of them.
- It subtracts not only horizontally but also vertically -- that adds 128 more bits.
- Instead of resizing to 8x9 it resizes to 8x8 and puts the image on a torus so it subtracts the very left column from the very right one and the top from the bottom.
So due to implementation and algorithm according to a benchmark the gem has the highest speed and quality compared to other gems (lower numbers are better):
Fingerprint Compare 1/FMI^2 Phamilie 3.943 0.630 4.000 Dhash 4.969 1.097 1.375 DHash 0.434 1.089 1.556 IDHash 0.396 0.126 1.250
Here are two photos (by Brian Lauer):
and visualization of IDHash (
rake compare_images -- image1.jpg image2.jpg):
Here in each of 64 cells, there are two circles that color the difference between that cell and the neighbor one. If the difference is low the Importance bit is set to zero and the circle is invisible. So there are 128 pairs of corresponding circles and when you take one, if at least one circle is visible and is of different color the line is to be drawn. Here you see 15 lines and so the distance between fingerprints will be equal to 15 (that is pretty low and can be interpreted as "images look similar"). Also, you see here that floor on this photo matters -- classic dHash won't see that it's darker than wall because it's comparing only horizontal neighbors and if one photo had no floor the distance function won't notice that. Also, it sees the Important difference between the very right and left columns because the wall has a slow but visible gradient.
- Neither dHash nor IDHash can't automatically detect very shifted crops and rotated images but you can make a wrapper that would call the comparison function iteratively.
- These algorithms are color blind because of converting an image to grayscale. If you take a photo of something in your yard the sun will create lights and shadows, but if you compare photos of something green painted on a blue wall there is a possibility the machine would see nothing painted at all. The
dhashgem had such image in specs and that made them pretty useless (this was supposed to be a face):
- If you have a pile of 1000000 images comparing them with each other would take a month or two. To improve the process in case of dHash that uses Hamming distance you may want to read these threads on Stackexchange network:
- How to find the closest pairs of a string of binary bins in Ruby without O^2 issues?
- Find all pairs of values that are close under Hamming distance
- Finding the closest pair between two sets of points on the hypercube
- Would PCA work for boolean data types?
- Using pHash to search agaist a huge image database, what is the best approach?
- How do I speed up this BIT_COUNT query for hamming distance?
- Hamming distance on binary strings in SQL
- How to find the closest pairs of a string of binary bins in Ruby without O^2 issues?
brew install vips
If you have troubles, see https://jcupitt.github.io/libvips/install.html
gem install dhash-vips
If you have troubles with the
gem ruby-vips dependency, see https://github.com/libvips/ruby-vips
require "dhash-vips" hash1 = ::. "photo1.jpg" hash2 = ::. "photo2.jpg" distance = ::. hash1, hash2 if distance < 10 puts "Images are very similar" elsif distance < 20 puts "Images are slightly similar" else puts "Images are different" end
require "dhash-vips" hash1 = ::. "photo1.jpg" hash2 = ::. "photo2.jpg" distance = ::. hash1, hash2 if distance < 15 puts "Images are very similar" elsif distance < 25 puts "Images are slightly similar" else puts "Images are different" end
Notes and benchmarks
25constants are found empirically and just work enough well for 8-byte hashes. To find these thresholds you can run a rake task with hardcoded test cases (pairs of photos from the same photosession are not the same but are considered to be enough 'similar' for the purpose of this benchmark):
$ rake compare_quality
Dhash Phamilie DHashVips::DHash DHashVips::IDHash DHashVips::IDHash(4) The same image: 0..0 0..0 0..0 0..0 0..0
'Jordan Voth case': 2 2 4 0 0 Similar images: 1..15 14..34 2..23 6..22 53..166 Different images: 10..54 22..42 10..50 17..65 120..233 1/FMI^2 = 1.375 4.0 1.556 1.25 1.306 FP, FN = [3, 0] [0, 6] [1, 2] [2, 0] [1, 1]
FMIline here is the "quality of algorithm", i.e. the best achievable function from the "Fowlkes–Mallows index" value if you take the "similar" and "different" test pairs and try to draw the threshold line. Smaller number is better. The last line shows number of false positives (
FP) and false negatives (
FN) in case of the best achieved FMI. Here I've added the
phamiliegem that is DCT based (not a kind of dhash).
Methods were renamed from
hash_sizeoptional parameter that is 8 by default. The
IDHash#fingerprint's optional parameter is called
powerand works in a bit different way: 3 means 8 and 4 means 16 -- other sizes are not supported because they don't seem to be useful (higher fingerprint resolution makes it vulnerable to image shifts and croppings, also
#distancebecomes much slower). Because IDHash's fingerprint is more complex than DHash's one it's not that straight forward to compare them so under the hood the
#distancemethod have to check the size of fingerprint. If you are sure that fingerprints were made with power=3 then to skip the check you may use the
#distance3method will try to compile and use the Ruby C extension that is around 15 times faster than pure Ruby implementation. Native extension currently works on macOS rbenv Ruby from 2.3.8 to at least 2.7.0-preview2 installed with rbenv
-kflag. So the full benchmark:
load the image and calculate the fingerprint: user system total real Dhash 6.191731 0.230885 6.422616 ( 6.428763) Phamilie 5.361751 0.037524 5.399275 ( 5.402553) DHashVips::DHash 0.858045 0.144820 1.002865 ( 0.924308) DHashVips::IDHash 0.769975 0.071087 0.841062 ( 0.790470) DHashVips::IDHash 4 0.805311 0.077918 0.883229 ( 0.825897)
measure the distance (32*32*2000 times): user system total real Dhash hamming 1.810000 0.000000 1.810000 ( 1.824719) Phamilie distance 1.000000 0.010000 1.010000 ( 1.006127) DHashVips::DHash hamming 1.810000 0.000000 1.810000 ( 1.817415) DHashVips::IDHash distance 1.400000 0.000000 1.400000 ( 1.401333) DHashVips::IDHash distance3_ruby 3.320000 0.010000 3.330000 ( 3.337920) DHashVips::IDHash distance3_c 0.210000 0.000000 0.210000 ( 0.212864) DHashVips::IDHash distance 4 8.300000 0.120000 8.420000 ( 8.499735)
There is now a benchmark that runs both speed and quality tests summing results as a single table:
ruby 2.3.8p459 (2018-10-18 revision 65136) [x86_64-darwin18] vips-8.9.2-Tue Apr 21 09:26:11 UTC 2020 Version: ImageMagick 6.9.11-24 Q16 x86_64 2020-07-18 Intel(R) Core(TM) i5-7360U CPU @ 2.30GHz
Fingerprint Compare 1/FMI^2
Phamilie 3.943 0.630 4.000 Dhash 4.969 1.097 1.375 DHash 0.434 1.089 1.556 IDHash 0.396 0.126 1.250
Also note that to make
#distanceable to assume the fingerprint resolution from the size of Integer that represents it, the change in its structure was needed (left half of bits was swapped with right one), so fingerprints between versions 0.0.4 and 0.0.5 became incompatible, but you probably can convert them manually. Otherwise if we put the version or structure information inside fingerprint it would became slow to (de)serialize and store.
$ ruby -I./lib test.rb
rakecommands do the
bundle installand prepend
bundle execwhen calling.
packages ruby docker hub 3.12 2.7.1 2.5.8 2.6.6 2.7.1 3.11 2.6.6 2.4.10 2.5.8 2.6.6 2.7.1 3.10 2.5.8 2.4.10 2.5.8 2.6.6 2.7.1 3.9 2.5.8 2.4.9 2.5.7 2.6.5 2.7.0p1 3.8 2.5.8 2.3.8 2.4.6 2.5.5 2.6.3 3.7 2.4.6 2.3.8 2.4.5 2.5.3 2.6.0 3.6 2.4.6 2.4.5 2.5rc 3.5 2.3.8 3.4 2.3.7 2.3.7 2.4.4 3.3 2.2.9
The gem has been tested on macOS rbenv versions: 2.3.8, 2.4.9, 2.5.7, 2.6.5, 2.7.0-preview2
To quickly find out what does the dhash-vips Docker image include (TODO: write in this README about the existing Docker images):
docker run --rm <image_name> sh -c "cat /etc/alpine-release; ruby -v; vips -v"
You get this:
Can't install RMagick 2.16.0. Can't find MagickWand.h.
because Imagemagick sucks but we need it to benchmark alternative gems, so:
$ brew install [email protected] $ brew unlink [email protected] $ brew link [email protected] --force
OS X El Captain and rbenv may cause environment issues that would make you do things like:
$ ./ruby `rbenv which rake` compare_matrixes
instead of just
$ rake compare_matrixes
For more information on that: https://github.com/jcupitt/ruby-vips/issues/141
On macOS, when you do
bundle installit may fail to install
dhashgem dependency) saying:
ERROR: Can't install RMagick 4.0.0. Can't find magick/MagickCore.h.
To resolve this do:
$ brew install [email protected] $ LDFLAGS="-L/usr/local/opt/[email protected]/lib" CPPFLAGS="-I/usr/local/opt/[email protected]/include" bundle install
If you get
No package 'MagickCore' foundtry:
$ PKG_CONFIG_PATH="/usr/local/Cellar/[email protected]/6.9.10-74/lib/pkgconfig" bundle install
You might get:
NameError: uninitialized constant Magick::Rec601LumaColorspace Did you mean? Magick::Rec601YCbCrColorspace
if you call
bundle exec ...and so it uses some old installed version of the gem instead of the local one.
rake compare_qualityat least once before executing other rake tasks because it's currently the only one that downloads the test images.
v0.0.0.4is not semver and not real gem version -- it's only for Github Actions testing purposes.
Phamilie works with filenames instead of fingerprints and caches them but not distances.
John Cupitt (libvips and ruby-vips maintainer) helped me a lot.