88 lines
3.6 KiB
Python
88 lines
3.6 KiB
Python
from PIL import Image
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import imagehash
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import os
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import numpy as np
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import csv
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def writeCSV(i1, i2):
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with open("duplicates.csv", "a") as file:
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writer = csv.writer(file, delimiter=',')
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writer.writerow([i1, i2])
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class DuplicateRemover:
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extensions = ['png', 'jpg', 'jpeg', 'gif', 'webp']
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def __init__(self,dirname,hash_size = 8):
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self.dirname = dirname
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self.hash_size = hash_size
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def find_duplicates(self, verbose=True, exportCSV=True):
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"""
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Find and Delete Duplicates
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"""
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#fnames = os.listdir(self.dirname)
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hashes = {}
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duplicates = []
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if verbose:
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print("Finding Duplicates Now!\n")
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for path, subdirs, fnames in os.walk(self.dirname):
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for image in fnames:
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if list(image.lower().split('.'))[-1] in self.extensions:
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try:
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with Image.open(os.path.join(path,image)) as img:
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temp_hash = imagehash.average_hash(img, self.hash_size)
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if temp_hash in hashes:
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if verbose:
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print("Duplicate {} \nfound for Image {}!\n".format(os.path.join(path,image),os.path.join(path,hashes[temp_hash])))
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if exportCSV:
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writeCSV(os.path.join(path,image), os.path.join(path,hashes[temp_hash]))
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duplicates.append(os.path.join(path,image))
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else:
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hashes[temp_hash] = os.path.join(path,image)
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except Exception as error:
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print("Error: The following error occured:\n",os.path.join(path,image),"\n",error,"\n")
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if len(duplicates) != 0:
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if verbose:
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a = input("Do you want to delete these {} Images? Press Y or N: ".format(len(duplicates)))
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else:
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a = 'y'
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space_saved = 0
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if(a.strip().lower() == "y"):
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for duplicate in duplicates:
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space_saved += os.path.getsize(duplicate)
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os.remove(duplicate)
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if verbose:
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print("{} Deleted Succesfully!".format(duplicate))
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if verbose:
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print("\n\nYou saved {} mb of Space!".format(round(space_saved/1000000),2))
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else:
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if verbose:
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print("Thank you for Using Duplicate Remover")
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else:
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if verbose:
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print("No Duplicates Found :(")
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def find_similar(self,location,similarity=80,verbose=True):
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fnames = os.listdir(self.dirname)
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threshold = 1 - similarity/100
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diff_limit = int(threshold*(self.hash_size**2))
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with Image.open(location) as img:
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hash1 = imagehash.average_hash(img, self.hash_size).hash
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if verbose:
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print("Finding Similar Images to {} Now!\n".format(location))
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for image in fnames:
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if list(image.lower().split('.'))[-1] in self.extensions:
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with Image.open(os.path.join(self.dirname,image)) as img:
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hash2 = imagehash.average_hash(img, self.hash_size).hash
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if np.count_nonzero(hash1 != hash2) <= diff_limit:
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if verbose:
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print("{} image found {}% similar to {}".format(image,similarity,location))
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