Python PyTorch数据加载器错误:类型为';类型';没有len()
我对编程很陌生,现在知道我的错误来自哪里了 我获得了以下代码来设置数据集以训练分类器:Python PyTorch数据加载器错误:类型为';类型';没有len(),python,pytorch,dataloader,Python,Pytorch,Dataloader,我对编程很陌生,现在知道我的错误来自哪里了 我获得了以下代码来设置数据集以训练分类器: class cows_train(Dataset): def __init__(self, folder_path): self.image_list = glob.glob(folder_path+'/content/cows/train') self.data_len = len(self.image_list) def __getitem__(self
class cows_train(Dataset):
def __init__(self, folder_path):
self.image_list = glob.glob(folder_path+'/content/cows/train')
self.data_len = len(self.image_list)
def __getitem__(self, index):
single_image_path = self.image_list[index]
im_as_im = Image.open(single_image_path)
im_as_np = np.asarray(im_as_im)/255
im_as_np = np.expand_dims(im_as_np, 0)
im_as_ten = torch.from_numpy(im_as_np).float()
class_indicator_location = single_image_path.rfind('/content/cows/train/_annotations.csv')
label = int(single_image_path[class_indicator_location+2:class_indicator_location+3])
return (im_as_ten, label)
def __len__(self):
return self.data_len
对于数据加载器:
transform = transforms.Compose(
[transforms.ToTensor(),
transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))])
batch_size = 4
trainset = cows_train
trainloader = torch.utils.data.DataLoader(dataset = trainset, batch_size=10,
shuffle=True, num_workers=2)
classes = ('cow_left', 'cow_other')
作为输出,我收到:
TypeError Traceback (most recent call last)
<ipython-input-6-54702f98a725> in <module>()
6
7 trainset = cows_train
----> 8 trainloader = torch.utils.data.DataLoader(dataset = trainset, batch_size=10, shuffle=True, num_workers=2)
9
10 testset = cows_test
2 frames
/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py in __init__(self, dataset, batch_size, shuffle, sampler, batch_sampler, num_workers, collate_fn, pin_memory, drop_last, timeout, worker_init_fn, multiprocessing_context, generator, prefetch_factor, persistent_workers)
264 # Cannot statically verify that dataset is Sized
265 # Somewhat related: see NOTE [ Lack of Default `__len__` in Python Abstract Base Classes ]
--> 266 sampler = RandomSampler(dataset, generator=generator) # type: ignore
267 else:
268 sampler = SequentialSampler(dataset)
/usr/local/lib/python3.7/dist-packages/torch/utils/data/sampler.py in __init__(self, data_source, replacement, num_samples, generator)
100 "since a random permute will be performed.")
101
--> 102 if not isinstance(self.num_samples, int) or self.num_samples <= 0:
103 raise ValueError("num_samples should be a positive integer "
104 "value, but got num_samples={}".format(self.num_samples))
/usr/local/lib/python3.7/dist-packages/torch/utils/data/sampler.py in num_samples(self)
108 # dataset size might change at runtime
109 if self._num_samples is None:
--> 110 return len(self.data_source)
111 return self._num_samples
112
TypeError: object of type 'type' has no len()
您没有正确创建数据集对象。目前,您有:
trainset = cows_train
这仅将类别类型分配给列车组
。要创建类的对象,需要使用:
folder_path = '/path/to/dataset/'
trainset = cows_train(folder_path)
您应该发布导致实际错误的代码,否则将很难调试。在这种情况下,您需要发布包含
return len(self.data\u source)
的代码块,该代码块可能是:(?)def num\u samples(self)->int:if self.\u num\u samples为None:return len(self.data\u source)return self.\u num\u samplesCode未显示。请补充原问题
folder_path = '/path/to/dataset/'
trainset = cows_train(folder_path)