perceptual-hash-0.1.0.2: src/PerceptualHash.hs
{-# LANGUAGE FlexibleContexts #-}
module PerceptualHash ( imgHash
, fileHash
) where
import Control.Applicative (pure)
import Control.Monad.ST (runST)
import Data.Bits (shiftL, (.|.))
import qualified Data.Vector.Unboxed as V
import Data.Word (Word64)
import Graphics.Image (Array, Bilinear (..), Border (Edge),
Image, Pixel (PixelX, PixelY),
VU (..), X, Y, convolve, crop,
makeImage, readImageY, resize,
transpose, (|*|))
import Graphics.Image.Interface (toVector)
import Median (median)
dct32 :: (Floating e, Array arr Y e) => Image arr Y e
dct32 = makeImage (32,32) gen
where gen (i,j) = PixelY $ sqrt(2/n) * cos((fromIntegral ((2*i+1) * j) * pi)/(2*n))
n = 32
idMat :: (Fractional e, Array arr X e) => Image arr X e
idMat = makeImage (7,7)
(\_ -> PixelX (1/49))
meanFilter :: (Fractional e, Array arr X e, Array arr cs e) => Image arr cs e -> Image arr cs e
meanFilter = convolve Edge idMat
{-# SCC meanFilter #-}
size32 :: Array arr cs e => Image arr cs e -> Image arr cs e
size32 = resize Bilinear Edge (32,32)
crop8 :: Array arr cs e => Image arr cs e -> Image arr cs e
crop8 = crop (0,0) (8,8)
medianImmut :: (Ord e, V.Unbox e, Fractional e) => V.Vector e -> e
medianImmut v = runST $
median =<< V.thaw v
{-# SCC medianImmut #-}
dct :: (Floating e, Array arr Y e) => Image arr Y e -> Image arr Y e
dct img = dct32 |*| img |*| transpose dct32
{-# SCC dct #-}
imgHash :: Image VU Y Double -> Word64
imgHash = asWord64 . aboveMed . V.map (\(PixelY x) -> x) . toVector . crop8 . dct . size32 . meanFilter
where asWord64 :: V.Vector Bool -> Word64
asWord64 = V.foldl' (\acc x -> (acc `shiftL` 1) .|. boolToWord64 x) 0
where boolToWord64 :: Bool -> Word64
boolToWord64 False = 0
boolToWord64 True = 1
aboveMed v =
let med = medianImmut v
in V.map (<med) v
fileHash :: FilePath -> IO Word64
fileHash = fmap imgHash . readImageY VU