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SxJyJay / MSMDFusion

[CVPR 2023] MSMDFusion: Fusing LiDAR and Camera at Multiple Scales with Multi-Depth Seeds for 3D Object Detection
Apache License 2.0
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AssertionError: Samples in split doesn't match samples in predictions #11

Open jiumozhi123 opened 1 year ago

jiumozhi123 commented 1 year ago

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: 截图 2023-04-12 14-53-32 What I need to do for implement of this inference

SxJyJay commented 1 year ago

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 commented 1 year ago

Maybe you can refer to this page

jiumozhi123 commented 1 year ago

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 commented 1 year ago

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 commented 1 year ago

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 commented 1 year ago

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 commented 2 months ago

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: 截图 2023-04-12 14-53-32 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