深度学习三维重建-3DMM

   # 获取随即裁剪的参数    rect = torchvision.transforms.RandomCrop.get_params(feature,(height,width))    # 按照刚设定的值，裁剪特征    feature = torchvision.transforms.functional.crop(feature, *rect)    # 按照刚设定的值，裁剪标签    label = torchvision.transforms.functional.crop(label, *rect)    return feature, label imgs = []# n=5# 随机裁剪5个观察结果for _ in range(n):    imgs += voc_rand_crop(train_features[0], train_labels[0], 200, 300)imgs = [img.permute(1, 2, 0) for img in imgs]# 因为他输出的是feature,label，所需需要隔一个跳一个