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hello, I find some problems about 'val', I found that there was a problem with the code in line 144 'val_dataset.pipeline = cfg.data.train.pipeline', and it needs to be changed to this val_dataset.pipeline = cfg.data.train.dataset.pipeline. right?
The text was updated successfully, but these errors were encountered:
If I want to train 10 classes of detection on the nuscenes dataset, do I just need to change the following two things?
(1)Comment this line: gt_labels_3d[gt_labels_3d > 0] = -1 in mmdet3d/datasets/nuscenes_monocular_dataset.py
(2)Modify this line:num_classes=1==>num_classes=10 in configs/imvoxelnet/imvoxelnet_nuscenes.py
Am I right? O(∩_∩)O
Basically yes, but the performance will be very low. For better performance you may follow Anchor3DHeadparameters for NuScenes including sizes, scales and rotations. And for 3 scales here you also need to save 3 2d feature maps from 3 levels of the neck. We use only 1 scale (and 1 output of the neck) if I remember correctly.
hello, I find some problems about 'val', I found that there was a problem with the code in line 144 'val_dataset.pipeline = cfg.data.train.pipeline', and it needs to be changed to this val_dataset.pipeline = cfg.data.train.dataset.pipeline. right?
The text was updated successfully, but these errors were encountered: