We also provide scripts to visualize the dataset without inference. You can use tools/misc/browse_dataset.py to show loaded data and ground-truth online and save them on the disk. Currently we support single-modality 3D detection and 3D segmentation on all the datasets, multi-modality 3D detection on KITTI and SUN RGB-D, as well as monocular 3D detection on nuScenes. To browse the KITTI dataset, you can run the following command:

Notice: Once specifying --output-dir, the images of views specified by users will be saved when pressing _ESC_ in open3d window. If you want to zoom out/in the point clouds to inspect more details, you could specify --show-interval=0 in the command.

To verify the data consistency and the effect of data augmentation, you can also add --aug flag to visualize the data after data augmentation using the command as below:

If you also want to show 2D images with 3D bounding boxes projected onto them, you need to find a config that supports multi-modality data loading, and then change the --task args to multi-modality_det. An example is showed below:

You can simply browse different datasets using different configs, e.g. visualizing the ScanNet dataset in 3D semantic segmentation task:

And browsing the nuScenes dataset in monocular 3D detection task: