#!/opt/local/Library/Frameworks/Python.framework/Versions/3.13/bin/python3.13
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)
