flatten (, hash_string ) for hash_string in hash_group ] for hash_group in hashes ]) duplicates = perception. tqdm ) # Flatten the hashes into a list of (filepath, hash) tuples. compute_parallel ( filepaths = filepaths, progress = tqdm. glob ( 'thorn-perceptual-video-deduplication-example/*.gif' ) # Returns a list of dicts with a "filepath" and "hash" key. glob ( 'thorn-perceptual-video-deduplication-example/*.m4v' ) \ SimpleSceneDetection ( max_scene_length = 5 ) # Set a threshold for matching frames within videos and across videos. extractall ( '.' ) # By default, this will use TMK L1 with PHashU8. ZipFile ( 'thorn-perceptual-video-deduplication-example.zip' ) as f : f. urlretrieve ( "", "thorn-perceptual-video-deduplication-example.zip" ) with zipfile. Import urllib.request import zipfile import glob import tqdm import perception.hashers # Download some example videos. We could just delete # the first entry in each pair or manually verify the pairs to ensure they # are, in fact duplicates. extend ( current_duplicate_pairs ) # Now we can do whatever we want with the duplicates. deduplicate ( files = current_filepaths, hashers = comparison_hashers, isometric = True, progress = tqdm. comparison_hashers = duplicate_pairs = for current_group in groups : current_filepaths = current_duplicate_pairs = tools. filepath_group = ) for filepath in files ] groups = list ( set ()) # We consider any pair of images with a PHash distance of < 0.2 as # as a duplicate. extractall () files = glob ( '256_ObjectCategories/**/*.jpg' ) # To reduce the number of pairwise comparisons, # we can deduplicate within each image category # (i.e., we don't need to compare images of # butterflies with images of chess boards). open ( '256_ObjectCategories.tar' ) as tfile : tfile. urlretrieve ( "", "256_ObjectCategories.tar" ) with tarfile. Import os import tarfile from glob import glob import urllib.request import tqdm from perception import hashers, tools urllib. Thorn-perceptual-deduplication-example/315.jpg Thorn-perceptual-deduplication-example/315a.jpg If for whatever reason you’re keeping all your photos on a Mac, PhotoSweeper is an excellent alternative. Thorn-perceptual-deduplication-example/309a.jpg Unfortunately, AllDup is only available for Windows. Thorn-perceptual-deduplication-example/309.jpg Thorn-perceptual-deduplication-example/309b.jpg DataFrame ( duplicate_pairs ), showindex = False, headers =, tablefmt = 'rst' )) # Now we can do whatever we want with the duplicates. deduplicate ( files = filepaths, hashers = ) print ( tabulate. glob ( 'thorn-perceptual-deduplication-example/*.jpg' ) duplicate_pairs = tools. ZipFile ( 'thorn-perceptual-deduplication-example.zip' ) as f : f. urlretrieve ( "", "thorn-perceptual-deduplication-example.zip" ) with zipfile. Import os import glob import zipfile import urllib.request import tabulate import pandas as pd from perception import tools, hashers urllib.
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