type='Collect3D',# Pipeline that decides which keys in the data should be passed to the detector, refer to mmdet3d.datasets.pipelines.formating for more details
type='Collect3D',# Pipeline that decides which keys in the data should be passed to the detector, refer to mmdet3d.datasets.pipelines.formatting for more details
dict(type='Collect3D',# Pipeline that decides which keys in the data should be passed to the detector, refer to mmdet3d.datasets.pipelines.formating for more details
dict(type='Collect3D',# Pipeline that decides which keys in the data should be passed to the detector, refer to mmdet3d.datasets.pipelines.formatting for more details
keys=['points'])
]
eval_pipeline=[# Pipeline used for evaluation or visualization, refer to mmdet3d.datasets.pipelines for more details
...
...
@@ -250,13 +250,13 @@ eval_pipeline = [ # Pipeline used for evaluation or visualization, refer to mmd
load_dim=6,# The dimension of the loaded points
use_dim=[0,1,2]),# Which dimensions of the points to be used
dict(
type='DefaultFormatBundle3D',# Default format bundle to gather data in the pipeline, refer to mmdet3d.datasets.pipelines.formating for more details
type='DefaultFormatBundle3D',# Default format bundle to gather data in the pipeline, refer to mmdet3d.datasets.pipelines.formatting for more details
dict(type='Collect3D',# Pipeline that decides which keys in the data should be passed to the detector, refer to mmdet3d.datasets.pipelines.formating for more details
dict(type='Collect3D',# Pipeline that decides which keys in the data should be passed to the detector, refer to mmdet3d.datasets.pipelines.formatting for more details