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我有一个只有 2 个类的数据集，我试图按照https://github.com/davidsandberg/facenet/wiki/Triplet-loss-training使用 train_tripletloss.py 训练数据集

请帮我解决它...

发生错误的部分代码如下所示：

def sample_people(dataset, people_per_batch, images_per_person):
    nrof_images = people_per_batch * images_per_person

    # Sample classes from the dataset
    nrof_classes = len(dataset)
    class_indices = np.arange(nrof_classes)
    np.random.shuffle(class_indices)

    i = 0
    image_paths = []
    num_per_class = []
    sampled_class_indices = []
    # Sample images from these classes until we have enough
    while len(image_paths)<nrof_images:
        class_index = class_indices[i]
        nrof_images_in_class = len(dataset[class_index])
        image_indices = np.arange(nrof_images_in_class)
        np.random.shuffle(image_indices)
        nrof_images_from_class = min(nrof_images_in_class, images_per_person, nrof_images-len(image_paths))
        idx = image_indices[0:nrof_images_from_class]
        image_paths_for_class = [dataset[class_index].image_paths[j] for j in idx]
        sampled_class_indices += [class_index]*nrof_images_from_class
        image_paths += image_paths_for_class
        num_per_class.append(nrof_images_from_class)
        i+=1

    return image_paths, num_per_class

我认为错误发生在class_index = class_indices[i]

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