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我试图按照 Pytorch网站上的教程来实现更快的 R-CNN，但我无法发现可能导致错误的原因

UnboundLocalError: Caught UnboundLocalError in DataLoader worker process 0.
Original Traceback (most recent call last):
  File "/usr/local/lib/python3.7/dist-packages/torch/utils/data/_utils/worker.py", line 287, in _worker_loop
    data = fetcher.fetch(index)
  File "/usr/local/lib/python3.7/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/python3.7/dist-packages/torch/utils/data/_utils/fetch.py", line 44, in <listcomp>
    data = [self.dataset[idx] for idx in possibly_batched_index]
  File "<ipython-input-32-971899994cb2>", line 66, in __getitem__
UnboundLocalError: local variable 'img' referenced before assignment

当我尝试执行该部分时会发生这种情况：

from engine import train_one_epoch, evaluate
import utils
model = torchvision.models.detection.fasterrcnn_resnet50_fpn(pretrained=True)
dataset = PennFudanDataset('PennFudanPed', get_transform(train=True))
data_loader = torch.utils.data.DataLoader(dataset, batch_size=2, shuffle=True, num_workers=4,collate_fn=utils.collate_fn)

# For Training
images,targets = next(iter(data_loader))
images = list(image for image in images)
targets = [{k: v for k, v in t.items()} for t in targets]
output = model(images,targets)   # Returns losses and detections
# For inference

model.eval()
x = [torch.rand(3, 300, 400), torch.rand(3, 500, 400)]
predictions = model(x)           # Returns predictions

我一直在使用 Google collab 进行这些测试。带有数据的文件在我的内容文件夹中。我怎么解决这个问题？

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