pytorch利用Dataset读取数据报错问题及解决
作者:josenxiao
报错点
如下:
Traceback (most recent call last):
File "read_data.py", line 100, in <module>
for i , (image,seg) in enumerate(train_loader):
File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/dataloader.py", line 819, in __next__
return self._process_data(data)
File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/dataloader.py", line 846, in _process_data
data.reraise()
File "/usr/local/lib/python3.6/dist-packages/torch/_utils.py", line 369, in reraise
raise self.exc_type(msg)
TypeError: Caught TypeError in DataLoader worker process 0.
Original Traceback (most recent call last):
File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/_utils/worker.py", line 178, in _worker_loop
data = fetcher.fetch(index)
File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/_utils/fetch.py", line 44, in <listcomp>
data = [self.dataset[idx] for idx in possibly_batched_index]
File "read_data.py", line 91, in __getitem__
])(img)
File "/usr/local/lib/python3.6/dist-packages/torchvision/transforms/transforms.py", line 61, in __call__
img = t(img)
File "/usr/local/lib/python3.6/dist-packages/torchvision/transforms/transforms.py", line 238, in __call__
return F.center_crop(img, self.size)
File "/usr/local/lib/python3.6/dist-packages/torchvision/transforms/functional.py", line 374, in center_crop
w, h = img.size
TypeError: 'int' object is not iterable
原来我其实没有注意Datset与PIL下面的Image的关系:
def __getitem__(self, index): img = cv2.imread(self.image_name[index],cv2.COLOR_BGR2RGB) #img = np.transpose(img,(2,1,0)) img = cv2.resize(img,(self.size,self.size)) seg = cv2.imread(self.image_seg[index],cv2.COLOR_BGR2RGB) seg = cv2.resize(seg,(self.size,self.size) ) seg = convert_from_color_segmentation(seg) #seg = torch.from_numpy(seg) if self.transform is not None: img = self.transform(img) return img , seg
报错中清晰提及这个问题
我突然反应过来,是自己的读取数据错误了:
应该为:
def __getitem__(self, index): #img = cv2.imread(self.image_name[index],cv2.COLOR_BGR2RGB) img = Image.open(self.image_name[index]) #img = np.transpose(img,(2,1,0)) #img = cv2.resize(img,(self.size,self.size)) seg = cv2.imread(self.image_seg[index],cv2.COLOR_BGR2RGB) seg = cv2.resize(seg,(self.size,self.size) ) seg = convert_from_color_segmentation(seg) #seg = torch.from_numpy(seg) if self.transform is not None: img = self.transform(img) return img , seg
测试打印数据
完美解决
transform = transforms.Compose([transforms.Resize((300,300)),transforms.RandomCrop((224,224)),transforms.ToTensor(),transforms.Normalize([0.485,0.456,0.406],[0.229,0.224,0.225])]) #transform = transforms.Compose([ # transforms.CenterCrop((278,278)),transforms.Resize((224,224)),transforms.ToTensor() # ]) train_data = GetParasetData(size=224,train=True,transform=transform) train_loader = DataLoader(train_data,batch_size=64,shuffle=True,num_workers=2) for i , (image,seg) in enumerate(train_loader): print(image.shape,seg.shape)
总结
以上为个人经验,希望能给大家一个参考,也希望大家多多支持脚本之家。