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feat(lidar_centerpoint): remove files those are no longer supported n…
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…or used (#6497)

* feat(lidar_centerpoint): remove files those are no longer supported nor used

Signed-off-by: kminoda <[email protected]>

* remove unnecessary file

Signed-off-by: kminoda <[email protected]>

---------

Signed-off-by: kminoda <[email protected]>
Co-authored-by: Kenzo Lobos Tsunekawa <[email protected]>
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kminoda and knzo25 authored Mar 11, 2024
1 parent ef751f6 commit 25bd77e
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19 changes: 0 additions & 19 deletions perception/lidar_centerpoint/CMakeLists.txt
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Expand Up @@ -135,25 +135,6 @@ if(TRT_AVAIL AND CUDA_AVAIL AND CUDNN_AVAIL)
EXECUTABLE lidar_centerpoint_node
)

## single inference node ##
ament_auto_add_library(single_inference_lidar_centerpoint_component SHARED
src/single_inference_node.cpp
)

target_link_libraries(single_inference_lidar_centerpoint_component
centerpoint_lib
)

rclcpp_components_register_node(single_inference_lidar_centerpoint_component
PLUGIN "centerpoint::SingleInferenceLidarCenterPointNode"
EXECUTABLE single_inference_lidar_centerpoint_node
)

install(PROGRAMS
scripts/lidar_centerpoint_visualizer.py
DESTINATION lib/${PROJECT_NAME}
)

ament_export_dependencies(ament_cmake_python)

ament_auto_package(
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12 changes: 0 additions & 12 deletions perception/lidar_centerpoint/README.md
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Expand Up @@ -68,18 +68,6 @@ You can download the onnx format of trained models by clicking on the links belo
`Centerpoint` was trained in `nuScenes` (~28k lidar frames) [8] and TIER IV's internal database (~11k lidar frames) for 60 epochs.
`Centerpoint tiny` was trained in `Argoverse 2` (~110k lidar frames) [9] and TIER IV's internal database (~11k lidar frames) for 20 epochs.

## Standalone inference and visualization

In addition to its use as a standard ROS node, `lidar_centerpoint` can also be used to perform inferences in an isolated manner.
To do so, execute the following launcher, where `pcd_path` is the path of the pointcloud to be used for inference.

```bash
ros2 launch lidar_centerpoint single_inference_lidar_centerpoint.launch.xml pcd_path:=test_pointcloud.pcd detections_path:=test_detections.ply
```

`lidar_centerpoint` generates a `ply` file in the provided `detections_path`, which contains the detections as triangle meshes.
These detections can be visualized by most 3D tools, but we also integrate a visualization UI using `Open3D` which is launched alongside `lidar_centerpoint`.

### Changelog

#### v1 (2022/07/06)
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