remove_dhash.py

#!/usr/bin/python3
# -*- coding: utf-8 -*-

from tkinter.filedialog import askdirectory
from tkinter import Tk
from tqdm import tqdm
import sys
import cv2
import os

def dhash(image, hashSize=8):
    resized_img = cv2.resize(image, (hashSize + 1, hashSize))
    diff = resized_img[:, 1:] > resized_img[:, :-1]
    return sum([2 ** i for (i, v) in enumerate(diff.flatten()) if v])

def dhash_path(path, hashSize=8):
    if path.endswith(".webm") or path.endswith(".mp4") or path.endswith(".gif"):
        return None
    image = cv2.imread(path)
    if image is None:
        return None
    image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    return dhash(image, hashSize=hashSize)

def keep_widest_img(data):
    widest_file = max(data, key=lambda i: i[0])
    for item in data:
        if item[1] == widest_file[1]:
            continue
        else:
            os.remove(item[1])

def keep_highest_name(data):
    num_filenames = [(item[1].split('/')[-1].split(',')[0], item[1]) for item in data]
    highest_filename = max(num_filenames, key=lambda i: int(i[0]))
    widest_file = max(data, key=lambda i: int(i[0]))
    img = cv2.imread(widest_file[1])
    for item in data:
        os.remove(item[1])
    a = cv2.imwrite(highest_filename[1], img)

if __name__ == '__main__':
    args = sys.argv[1:]
    directory = ""
    if len(args) == 0:
        Tk().withdraw()
        directory = askdirectory()
    else:
        directory = os.path.abspath(args[0])
    custom = True

    pic_hashes = {}

    print("Calculating dhashes")
    for rel_path in tqdm(os.listdir(directory)):
        path = directory + "/" + rel_path
        image_hash = dhash_path(path)
        if image_hash is None:
            continue
        elif image_hash in pic_hashes:
            pic_hashes[image_hash].append(path)
        else:
            pic_hashes[image_hash] = [path]

    dupe_list = []
    for key in pic_hashes.keys():
        if len(pic_hashes[key]) > 1:
            dupe_list.append(pic_hashes[key])
    
    if len(dupe_list) == 0:
        print("No Duplicates Found")
        sys.exit()

    count = 0
    for i in dupe_list:
        for j in i:
            count += 1
    count -= len(dupe_list)

    print("\nDeleting " + str(count) + " dupes")
    for dupes in tqdm(dupe_list):
        data = [(cv2.imread(path).shape[1], path) for path in dupes]
        if custom:
            keep_highest_name(data)
        else:
            keep_widest_img(data)