A library of fast(ish) image similarity algorithms!

Source of images: favorites gallery of prominent artist on dA

• chosen because she has similar visual taste--would be representative of most styles that we are likely to see in people using this extension

• src/fmiq
  • fmiq.py: implements the fast multiresolution querying algorithm (see paper/ directory)
  • fmiq-process.py: parses the output of fmiq on the source images and queries with test images
• src/opencv
  • histogram.cpp: wrapper around four opencv measures, as well as their queries
    • how to build: run make
  • CMakeLists.txt (getting this to build the right Makefile was not easy)
• src/phash
  • phash.c: wrapper around phash library (located in lib). generates perceptual hashes of everything in source image directory
    • compatible with radial hashing, DCT hashing
    • how to build: g++ -c phash.c ; g++ -o phash phash.c main.o => generates executable phash
  • phash-process.c: processes the output of phash.c; scores all test images and assigns relative distances
    • how to build: g++ -c phash-process.c ; g++ -o process phash-process.c main.o => generates executable process
• src/analytics
  • process.py all purpose tool for evaluating the accuracy of the algorithms above
• data/
  • data/opencv
    • all: results of algorithm on 10 different test data sets
    • opencvresults: output of process.py on those files
    • opencv.md: some data consolidation analysis
  • data/phash
    • radial/: results of radial hashing algorithm on 10 different test data sets
    • dct/: results of dct hashing algorithm on 10 different test data sets
    • radishresults: output of process.py on radial/
    • dctresults: results of process.py on dct/
    • phash.md: some data consolidation and analysis
  • data/fmiq
    • all: results of algorithm on 10 different test data sets
    • fmiqresults: output of process.py on those files
    • fimq.md: some data consolidation and analysis
• tests/: directories of test data set after various small digital modifications
  • all folders here created through image manipulation by imagemagickcommand line tool

• openCV
• Boost

• gathered source images
• narrowed down similarity algorithms
• implemented part of multiresolution querying
• set up mySQL database for front-end

• set up pHash (perceptual hash)
  • installed MacPorts, libpng, CImg dependencies
  • ...before downloading source and copying it into the directory
  • wrote wrapper program phash.c
  • testing two hashes: radial and regular
• set up openCV histogram comparison method (a library for C++)
  • set up cMake
  • installed Boost and related libraries for iterating through directories
  • learned basic C++
  • wrote wrapper program histogram.cpp
• finished implementing multiresolution querying (see fmiq)
  • fixed PIL pip install
  • attempted optimizations using pypy (didn't work)
  • each image takes about 7 seconds to analyze
  • straight from paper; rgb to yiq color space conversion
• homogenized source images
  • installed imagemagick through macports
  • converted all files to jpg
  • converted all jpg to rgb color space
  • set up test files, including effects

• set up test images
  • 20 for each effect (see tests folder)
  • aspect ratio: fixed aspect ratio (300x300px)
  • contrast: increased histogram contrast
  • crop: cropped images to squares, up to 1/2 of image cropped off
  • grayscale: converted to grayscale
  • hue: modulate histogram
  • paint: blobby effect
  • resizedown, resizeup: 50% and 200%, respectively
  • rotate: rotate 90 degrees
  • tintred: duochrome
  • txt: todo, overlaid text
• tested for duplicates among source images
• fixing fimq: tried for 30 minutes to install PIl, gave up and installed a virtualenv instead
• completed fimq implementation
• completed fimq processing and porting

• debugged fimq porting
  • this took a ridiculously long time.
  • started data collection!!!
• set up wrapper files for phash: still working on radial though
  • solution to exporting signature data: write to file in a specific format
• now both phash and fimq are ready for data collection

• get Boost working and compile the thing
• debug the program
• wrote a program to process output
• analyzed and wrote evaluations for fmiq and opencv
• collected data for fmiq and opencv
• analyzed data for fmiq and opencv
• wrote most of presentation

• fixed pHash
• conducted pHash evaluations

• implemented radial hashing
• evaluated radial hashing results
• cleaned up and documented code