我正在尝试使用 PyTorch 制作一个简单的图像分类器。这是我将数据加载到数据集和 dataLoader 中的方式：
batch_size = 64
validation_split = 0.2
data_dir = PROJECT_PATH+"/categorized_products"
transform = transforms.Compose([transforms.Grayscale(), CustomToTensor()])
dataset = ImageFolder(data_dir, transform=transform)
indices = list(range(len(dataset)))
train_indices = indices[:int(len(indices)*0.8)]
test_indices = indices[int(len(indices)*0.8):]
train_sampler = SubsetRandomSampler(train_indices)
test_sampler = SubsetRandomSampler(test_indices)
train_loader = torch.utils.data.DataLoader(dataset, batch_size=batch_size, sampler=train_sampler, num_workers=16)
test_loader = torch.utils.data.DataLoader(dataset, batch_size=batch_size, sampler=test_sampler, num_workers=16)
我想分别打印出训练和测试数据中每个班级的图像数量，如下所示：
在火车数据中：
在测试数据中：
我试过这个：
from collections import Counter
print(dict(Counter(sample_tup[1] for sample_tup in dataset.imgs)))
但我收到了这个错误：
AttributeError: 'MyDataset' object has no attribute 'img'