How to use the imagehash.colorhash function in ImageHash

"Elapsed time": str(DT.datetime.now() - start_datetime).rsplit('.', maxsplit=1)[0],
            })

            if progress.wasCanceled():
                break

            print(i, '/', number_image_by_hashes, other_file_name)
            if other_file_name == file_name:
                continue

            other_hash_value = hashes[hash_algo]

            # TODO: Monkey patch. https://github.com/JohannesBuchner/imagehash/issues/112
            if hash_algo == 'colorhash':
                from PIL import Image
                other_hash_value = imagehash.colorhash(Image.open(other_file_name))

            score = hash_value - other_hash_value
            print(f'Score: {score:2}. Similar images: {file_name!r} and {other_file_name!r}. '
                  f'{hash_value} vs {other_hash_value}')

            # TODO: выяснить максимальные значения для каждого из алгоритмом
            #           думаю, можно ориентироваться на длину хеша
            #           можно в sql посмотреть или в self.image_by_hashes[file_name]
            if score > max_score:
                continue

            # print(f'Score: {score:2}. Similar images: {file_name!r} and {other_file_name!r}. '
            #       f'{hash_value} vs {other_hash_value}')

            results.append(other_file_name)

def run(self) -> None:
        img_by_hash = dict()
        for file_name, hashes in self.image_by_hashes.items():
            hash_value = hashes[self.hash_algo]

            # TODO: Monkey patch. https://github.com/JohannesBuchner/imagehash/issues/112
            if self.hash_algo == 'colorhash':
                from PIL import Image
                hash_value = imagehash.colorhash(Image.open(file_name))

            img_by_hash[file_name] = hash_value

        file_name_by_similars = defaultdict(list)
        for img_1, img_2 in itertools.product(img_by_hash.items(), repeat=2):
            if img_1 == img_2:
                continue

            file_name_1, hash_img_1 = img_1
            file_name_2, hash_img_2 = img_2

            score = hash_img_1 - hash_img_2
            if score > self.max_score:
                continue

            file_name_by_similars[file_name_1].append((file_name_2, score))

def start_search_for_similar(self):
        file_name = self.list_indexed_images_widget.currentFileName()
        if not file_name:
            return

        hash_algo = self.search_for_similar_settings.cb_algo.currentText()
        max_score = self.search_for_similar_settings.sb_max_score.value()

        hash_value = self.image_by_hashes[file_name][hash_algo]

        # TODO: Monkey patch. https://github.com/JohannesBuchner/imagehash/issues/112
        if hash_algo == 'colorhash':
            from PIL import Image
            hash_value = imagehash.colorhash(Image.open(file_name))

        print(f'start_search_for_similar: hash_algo={hash_algo}, max_score={max_score}, '
              f'file_name={file_name}, hash_value={hash_value}')

        number_image_by_hashes = len(self.image_by_hashes)

        # Для составления списка файлов, что нужно обработать
        progress = FieldsProgressDialog(0, number_image_by_hashes, "Search for similar...", parent=self)
        progress.show()

        time_start = default_timer()
        start_datetime = DT.datetime.now()
        results = []

        for i, (other_file_name, hashes) in enumerate(self.image_by_hashes.items(), 1):
            QApplication.processEvents()