find_similar_images.py

#!/usr/bin/env python
from __future__ import (absolute_import, division, print_function)
from PIL import Image
import six

import imagehash

"""
Demo of hashing
"""
def find_similar_images(userpaths, hashfunc = imagehash.average_hash):
    def is_image(filename):
        f = filename.lower()
        return f.endswith(".png") or f.endswith(".jpg") or \
            f.endswith(".jpeg") or f.endswith(".bmp") or \
            f.endswith(".gif") or '.jpg' in f or  f.endswith(".svg")
    
    image_filenames = []
    for userpath in userpaths:
        image_filenames += [os.path.join(userpath, path) for path in os.listdir(userpath) if is_image(path)]
    images = {}
    for img in sorted(image_filenames):
        try:
            hash = hashfunc(Image.open(img))
        except Exception as e:
            print('Problem:', e, 'with', img)
            continue
        if hash in images:
            print(img, '  already exists as', ' '.join(images[hash]))
            if 'dupPictures' in img:
                print('rm -v', img)
        images[hash] = images.get(hash, []) + [img]
    
    #for k, img_list in six.iteritems(images):
    #    if len(img_list) > 1:
    #        print(" ".join(img_list))


if __name__ == '__main__':
    import sys, os
    def usage():
        sys.stderr.write("""SYNOPSIS: %s [ahash|phash|dhash|...] [<directory>]

Identifies similar images in the directory.

Method: 
  ahash:          Average hash
  phash:          Perceptual hash
  dhash:          Difference hash
  whash-haar:     Haar wavelet hash
  whash-db4:      Daubechies wavelet hash
  colorhash:      HSV color hash
  crop-resistant: Crop-resistant hash

(C) Johannes Buchner, 2013-2017
""" % sys.argv[0])
        sys.exit(1)
    
    hashmethod = sys.argv[1] if len(sys.argv) > 1 else usage()
    if hashmethod == 'ahash':
        hashfunc = imagehash.average_hash
    elif hashmethod == 'phash':
        hashfunc = imagehash.phash
    elif hashmethod == 'dhash':
        hashfunc = imagehash.dhash
    elif hashmethod == 'whash-haar':
        hashfunc = imagehash.whash
    elif hashmethod == 'whash-db4':
        hashfunc = lambda img: imagehash.whash(img, mode='db4')
    elif hashmethod == 'colorhash':
        hashfunc = imagehash.colorhash
    elif hashmethod == 'crop-resistant':
        hashfunc = imagehash.crop_resistant_hash
    else:
        usage()
    userpaths = sys.argv[2:] if len(sys.argv) > 2 else "."
    find_similar_images(userpaths=userpaths, hashfunc=hashfunc)