AssertionError: Samples in split doesn't match samples in predictions

[jiumozhi123]

Hi, I try to have a inference by fusion_voxel0075_R50.pth(from Baidu cloud storage) and transfusion_nusc_voxel_L.py(base line) When I run "python tools/test.py configs/transfusion_nusc_voxel_L.py checkpoints/fusion_voxel0075_R50.pth --eval bbox", the following error occur: What I need to do for implement of this inference

[SxJyJay]

It seems that your validation set is not complete. Please double-check whether you download the complete nuscenes validation set. Besides, the checkpoint "fusion_voxel0075_R50.pth" merges pretrained transfusion-L and ResNet-50. Thus, you should load pure pre-trained transfusion-L checkpoint for LiDAR-only evaluation. We provide "fusion_voxel0075_R50.pth" to help users directly train the 2-nd MSMDFusion stage without being bothered with the 1-st LiDAR-only backbone pretraining.

[SxJyJay]

Maybe you can refer to this page

[jiumozhi123]

It seems that your validation set is not complete. Please double-check whether you download the complete nuscenes validation set. Besides, the checkpoint "fusion_voxel0075_R50.pth" merges pretrained transfusion-L and ResNet-50. Thus, you should load pure pre-trained transfusion-L checkpoint for LiDAR-only evaluation. We provide "fusion_voxel0075_R50.pth" to help users directly train the 2-nd MSMDFusion stage without being bothered with the 1-st LiDAR-only backbone pretraining.

I'm sure that my nuscenes datasets is complete. Is it convenient for you to provide pre-trained transfusion-L checkpoint file? I hope to get the performance for base-line network in MSMDFusion. By the way, The nuscenes datasets which I inference include the "foreground_mixed_6nn_width_depth" folder for samples and sweeps. Is it have any influence for lidar-only inference? Thanks a lot!

[SxJyJay]

I cannot find the pre-trained TransFusion-L checkpoint file. You can extract the lidar part in fusioin_voxel0075_R50.pth. "FOREGROUND_MIXED_6NN_WITH_DEPTH" doesn't influence lidar-only inference.

[jiumozhi123]

I find out the reason of error in inference task. Code "cfg.data.test.ann_file = 'data/nuscenes/nuscenes_infos_train.pkl'" in line 117 should be deprecated in "https://github.com/SxJyJay/MSMDFusion/blob/main/tools/test.py".

[SxJyJay]

I find out the reason of error in inference task. Code "cfg.data.test.ann_file = 'data/nuscenes/nuscenes_infos_train.pkl'" in line 117 should be deprecated in "https://github.com/SxJyJay/MSMDFusion/blob/main/tools/test.py".

Thanks for you pointing out this! I will fix this bug.

[Libraaer]

Hi, I try to have a inference by fusion_voxel0075_R50.pth(from Baidu cloud storage) and transfusion_nusc_voxel_L.py(base line) When I run "python tools/test.py configs/transfusion_nusc_voxel_L.py checkpoints/fusion_voxel0075_R50.pth --eval bbox", the following error occur: What I need to do for implement of this inference

Hello, have you trained this model? I'm using A800 here but still not enough to train. If you've trained, can you give me an answer to the reason for my lack of memory here, thank you