基于FaceNet的深度学习人脸识别.zip

import torch from torch.utils.data import DataLoader from torchvision import datasets from torchvision import transforms def main(): batch_size = 32 cifar_train = datasets.CIFAR10('cifar', True, transform=transforms.Compose([ transforms.Resize((32, 32)), transforms.ToTensor() ]), download=True) cifar_train = DataLoader(cifar_train, batch_size=batch_size, shuffle=True) cifar_text = datasets.CIFAR10('cifar', False, transform=transforms.Compose([ transforms.Resize((32, 32)), transforms.ToTensor() ]), download=True) cifar_text = DataLoader(cifar_text, batch_size=batch_size, shuffle=True) x, label = iter(cifar_train).next() print('x:', x.shape, 'label:', label.shape) if __import__ == '_main_': main()