When defined datasets for grayscale image,always occured 0

def default_loader(path):
return Image.open(path)
class myImageFloder(data.Dataset):
def init(self, root, label, transform=None, target_transform=None, loader=default_loader):
fh = open(label)
c = 0
imgs = []
class_names = []
for line in fh.readlines():
if c == 0:
class_names = [n.strip() for n in line.rstrip().split(’ ')]
else:
cls = line.split()
fn = cls.pop(0)
if os.path.isfile(os.path.join(root, fn)):
imgs.append((fn, tuple([float(v) for v in cls])))
c = c + 1
self.root = root
self.imgs = imgs
self.classes = class_names
self.transform = transform
self.target_transform = target_transform
self.loader = loader

def __getitem__(self, index):
    fn, label = self.imgs[index]
    img = self.loader(os.path.join(self.root, fn))
    if self.transform is not None:
        img = self.transform(img)
    return img, torch.Tensor(label)

def __len__(self):
    return len(self.imgs)

def getName(self):
    return self.classes

def tesmyImageFloder():
dataloader = myImageFloder(’/home/zw/ztfd_data/mnist02/test’,
‘/home/zw/ztfd_data/mnist02/test.txt’)
print(‘dataloader.getName’, dataloader.getName())
for index, (img, label) in enumerate(dataloader):
img.show()
print(‘label’, label)
if name == “main”:
# trainImageFloder()
tesmyImageFloder()
tesLoader=torch.utils.data.DataLoader(myImageFloder(root = “/home/zw/ztfd_data/mnist02/test”,
label = “/home/zw/ztfd_data/mnist02/test.txt”,
transform = mytransform),
batch_size= 64, shuffle= False, num_workers= 2)
for i, data in enumerate(tesLoader, 0):
print(data[i][0])
print(len(tesLoader))
111
what means?why?PLEASE!!!