KeyError: Caught KeyError in DataLoader worker process 0 when training imvoxelnet on ScanNet Dataset
Cindy0725 opened this issue · comments
Hi, I am trying to reproduce the result on ScanNet. I built the docker file and run the image. I followed your instruction on GitHub to process ScanNet. In the container, I run "python tools/train.py configs/imvoxelnet/imvoxelnet_scannet.py", but got the following error:
Is this due to the processing of ScanNet dataset? I followed exactly the instruction , I checked the "scannet_infos_train.pkl" and for each scene, I have the following annotation:
Looking forward to your kind reply. Thank you very much!
Hi, I tried to debug the code, and I found that the error comes from
According to Custom3DDataset class, self.data_infos is dictionary type loaded from pickle file, the iterated calling process is:
self.data_infos = self.load_annotations(self.ann_file) -> mmcv.load() -> PickleHandler() -> load_from_fileobj -> pickle.load(ann_file, **kwargs) And when calling get_item() function in Custom3DDataset class, the iterated calling is:
Custom3DDataset.__get_item__() -> Custom3DDataset.preprare_train_data(self, index) -> ScanNetMultiViewDataset.get_data_info() -> self.data_infos[index] (line17 of scannet_monocular_dataset.py where error occurs)
It seems that it throws error since self.data_infos is in dictionary type and can't be accessed by [index]. I think there is something wrong with the annotation file, e.g. "scannet_infos_train.pkl" or "scannet_infos_val.pkl"
I am wondering if I preprocess the ScanNet wrongly, could you please help check your ScanNet annotation file and data format?
Thank you very much! Looking forward to your kind reply.
Have you preprocessed scannet with this repo or with master branch of mmdetection3d? It should be this repo, as preprocessing has changed in mmdetection3d since our release.
Hi, sorry for this stupid mistake... I thought the files should be the same since they have the same name and structure... I have reprocessed the data according to this repo, and the error disappears. But the docker image can't be run on 6000ada or 4090 since the cuda101 + pytorch 1.6 don't support sm89 of 6000ada. I will try to install newer version of torch + cuda and try to modify the code. Thank you very much for your kind reply! Have a nice day.