d2dbd440d89d22b4b75f30ddeb4c4ebd3882ecfa,tools/sort.py,Sort,sort_face_dissim,#Sort#,208

Before Change

        logger.info("Sorting by face dissimilarity...")

        img_list = [[img, self.vgg_face.predict(cv2.imread(img)), 0]
                    for img in
                    tqdm(self.find_images(input_dir),
                         desc="Loading",
                         file=sys.stdout)]

        img_list_len = len(img_list)
        for i in tqdm(range(0, img_list_len), desc="Sorting", file=sys.stdout):
            score_total = 0
            for j in range(0, img_list_len):
                if i == j:
                    continue
                score_total += self.vgg_face.find_cosine_similiarity(
                    img_list[i][1],
                    img_list[j][1])

            img_list[i][2] = score_total

        logger.info("Sorting...")
        img_list = sorted(img_list, key=operator.itemgetter(2), reverse=True)
        return img_list

After Change

        logger.info("Sorting by face dissimilarity...")
        images = np.array(self.find_images(input_dir))
        preds = np.array([self.vgg_face.predict(cv2.imread(img))
                          for img in tqdm(images, desc="loading", file=sys.stdout)])
        logger.info("Sorting. Depending on ths size of your dataset, this may take a while...")
        indices = self.vgg_face.sorted_similarity(preds, method="complete")
        img_list = images[indices]

Instances