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OpenDriveLab / TCP

[NeurIPS 2022] Trajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet Strong Baseline.
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AssertionError: Expected image to have shape (height, width, [channels]), got shape (). #61

Closed donkehuang closed 1 month ago

donkehuang commented 6 months ago

When i run the training progress with python TCP/train.py, it works util the "Saving latest checkpoint". When Saving latest checkpoint, it occurs the error that AssertionError: Caught AssertionError in DataLoader worker process 7. Original Traceback (most recent call last): File "/home/donke/anaconda3/envs/TCP/lib/python3.7/site-packages/torch/utils/data/_utils/worker.py", line 287, in _worker_loop data = fetcher.fetch(index) File "/home/donke/anaconda3/envs/TCP/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 49, in fetch data = [self.dataset[idx] for idx in possibly_batched_index] File "/home/donke/anaconda3/envs/TCP/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 49, in <listcomp> data = [self.dataset[idx] for idx in possibly_batched_index] File "/home/donke/TCP/TCP/data.py", line 90, in __getitem__ Image.open(self.root+self.front_img[index][0])))) File "/home/donke/anaconda3/envs/TCP/lib/python3.7/site-packages/imgaug/augmenters/meta.py", line 769, in augment_image "got shape %s." % (image.shape,)) AssertionError: Expected image to have shape (height, width, [channels]), got shape (). what should i do, thanks

qqcole2000 commented 1 month ago

Hello, I have encountered the same problem,have you resolved it?

donkehuang commented 1 month ago

Hello, I have encountered the same problem,have you resolved it?

I have solve this problem which is caused by an image with incorrect format. To solve this bug, you can skip the image with incorrect format or just delete the image in dataset. The specific index of the image is hard for me to remember, but i hope the code for skipping the image may help you. In data.py:88,correct the code like this: if self.img_aug: try: temp = np.array(Image.open(self.root+self.front_img[index][0])) data['front_img'] = self._im_transform(augmenter(self._batch_read_number).augment_image(temp)) except: temp = np.array(Image.open(self.root+self.front_img[0][0])) data['front_img'] = self._im_transform(augmenter(self._batch_read_number).augment_image(temp)) else: try: temp = np.array(Image.open(self.root+self.front_img[index][0])) data['front_img'] = self._im_transform(temp) except: temp = np.array(Image.open(self.root+self.front_img[0][0])) data['front_img'] = self._im_transform(temp)

qqcole2000 commented 1 month ago

Thanks for your reply, it helps me a lot.