我试着用Pythorch训练一个网络。该数据集包括许多jpg和xml文件中的注释(标签和边界框)。我编写了一个用于提取注释的基本数据加载器。在
class dataLoader(dataset):
def __init__(self, path, root, img_trfm=None, resize=None):
self.filename = get_file_name(path)
self.data = self.filename
self.root = root
self.resize = resize
self.img_resize = transforms.Resize((resize, resize))
self.img_trfm = img_trfm
self.data_len = len(self.data)
def __getitem__(self, index):
filename = (self.filename[index])
objects, num_objs = get_targets(filename+'.xml')
img_name = objects[-1]
img = Image.open(self.root+img_name+'.jpg')
img_trfm = self.img_trfm(img)
#adds a dictionary for name of classes to
#corresponding integers
for i in range(num_objs-1):
objects[i]['bndbox'] = torch.Tensor(objects[i]['bndbox'])
objects[i]['id'] = get_class_id(objects[i]['label'])
return img_trfm, objects[:-1]
def __len__(self):
return self.data_len
输出是单个图像和图像中每个对象的字典列表:
^{pr2}$我还编写了一个基本的培训函数,用于仅使用标签id对网络进行培训:
for epoch in range(1):
running_loss = 0.0
for data in trainloader:
images, objects = data
for k in objects:
label = k['id']
#label = label.type(torch.FloatTensor)
print(label)
optimizer.zero_grad()
outputs = net(images)
loss = criterion(outputs, label)
loss.backward()
print(loss)
optimizer.step()
它似乎在起作用,因为我得到了损失价值:
tensor(0.46, grad_fn=<NllLossBackward>)
tensor(0.46, grad_fn=<NllLossBackward>)
tensor(2.13, grad_fn=<NllLossBackward>)
tensor(0.45, grad_fn=<NllLossBackward>)
tensor(0.44, grad_fn=<NllLossBackward>)
tensor(1.57, grad_fn=<NllLossBackward>)
tensor(0.43, grad_fn=<NllLossBackward>)
tensor(0.43, grad_fn=<NllLossBackward>)
tensor(2.30, grad_fn=<NllLossBackward>)
tensor(0.42, grad_fn=<NllLossBackward>)
tensor(0.42, grad_fn=<NllLossBackward>)
tensor(1.66, grad_fn=<NllLossBackward>)
tensor(0.42, grad_fn=<NllLossBackward>)
tensor(0.42, grad_fn=<NllLossBackward>)
tensor(2.12, grad_fn=<NllLossBackward>)
tensor(0.42, grad_fn=<NllLossBackward>)
tensor(0.42, grad_fn=<NllLossBackward>)
......
但是,在这些损失值之后,我一直收到以下错误消息:
File "/miniconda3/envs/env_PyTorch/lib/python3.7/xml/etree/ElementTree.py", line 598, in parse
self._root = parser._parse_whole(source)
File "<string>", line unknown
ParseError: no element found: line 1, column
如有任何建议,将不胜感激。在
目前没有回答
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