小编jan*_*lle的帖子

我想为 n-shot 学习准备 omniglot 数据集。因此我需要来自 10 个类别（字母表）的 5 个样本

重现代码

import tensorflow as tf
import tensorflow_datasets as tfds
import numpy as np

builder = tfds.builder("omniglot")
# assert builder.info.splits['train'].num_examples == 60000
builder.download_and_prepare()
# Load data from disk as tf.data.Datasets
datasets = builder.as_dataset()
dataset, test_dataset = datasets['train'], datasets['test']


def resize(example):
    image = example['image']
    image = tf.image.resize(image, [28, 28])
    image = tf.image.rgb_to_grayscale(image, )
    image = image / 255
    one_hot_label = np.zeros((51, 10))
    return image, one_hot_label, example['alphabet']


def stack(image, label, alphabet):
    return (image, label), …