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#!E:\网络与新媒体\github\pythonlearning\Scripts\python.exe

from __future__ import absolute_import, division, print_function

from PIL import Image

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__': # noqa: C901

import os

import sys

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':

def hashfunc(img):

return 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)