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feat(lidar_centerpoint, pointpainting)!: move max_voxel_count from _ml_package.param.yaml #9578

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feat(lidar_centerpoint, pointpainting)!: move max_voxel_count from _ml_package.param.yaml #9578

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a038a17
feat(lidar_centerpoint, pointpainting): move max_voxel_count from _ml…
kminoda Dec 5, 2024
ad4819a
style(pre-commit): autofix
pre-commit-ci[bot] Dec 5, 2024
d218733
update schema
kminoda Dec 5, 2024
f75f6b9
Merge branch 'main' into feat/centerpoint/move_max_voxel_count
kminoda Jan 10, 2025
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1 change: 1 addition & 0 deletions perception/autoware_image_projection_based_fusion/config/pointpainting.param.yaml
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Expand Up @@ -19,3 +19,4 @@
omp_params:
# omp params
num_threads: 1
max_voxel_size: 40000
1 change: 0 additions & 1 deletion perception/autoware_image_projection_based_fusion/config/pointpainting_ml_package.param.yaml
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Expand Up @@ -4,7 +4,6 @@
class_names: ["CAR", "TRUCK", "BUS", "BICYCLE", "PEDESTRIAN"]
paint_class_names: ["CAR", "BICYCLE", "PEDESTRIAN"]
point_feature_size: 7 # x, y, z, time-lag and car, pedestrian, bicycle
max_voxel_size: 40000
point_cloud_range: [-121.6, -76.8, -3.0, 121.6, 76.8, 5.0]
voxel_size: [0.32, 0.32, 8.0]
downsample_factor: 1
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5 changes: 5 additions & 0 deletions perception/autoware_image_projection_based_fusion/schema/pointpainting.schema.json
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Expand Up @@ -88,6 +88,11 @@
"minimum": 1
}
}
},
"max_voxel_size": {
"type": "integer",
"description": "A maximum size of voxel grid.",
"default": 40000
}
},
"required": []
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5 changes: 0 additions & 5 deletions ...eption/autoware_image_projection_based_fusion/schema/pointpainting_ml_package.schema.json
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Expand Up @@ -27,11 +27,6 @@
"description": "A number of channels of point feature layer.",
"default": 7
},
"max_voxel_size": {
"type": "integer",
"description": "A maximum size of voxel grid.",
"default": 40000
},
"point_cloud_range": {
"type": "array",
"description": "An array of distance ranges of each class, this must have same length with `class_names`.",
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2 changes: 1 addition & 1 deletion perception/autoware_image_projection_based_fusion/src/pointpainting_fusion/node.cpp
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Expand Up @@ -143,7 +143,7 @@
const std::size_t point_feature_size = static_cast<std::size_t>(
this->declare_parameter<std::int64_t>("model_params.point_feature_size"));
const std::size_t max_voxel_size =
static_cast<std::size_t>(this->declare_parameter<std::int64_t>("model_params.max_voxel_size"));
static_cast<std::size_t>(this->declare_parameter<std::int64_t>("max_voxel_size"));

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Added line #L146 was not covered by tests
pointcloud_range = this->declare_parameter<std::vector<double>>("model_params.point_cloud_range");
const auto voxel_size = this->declare_parameter<std::vector<double>>("model_params.voxel_size");
const std::size_t downsample_factor = static_cast<std::size_t>(
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2 changes: 1 addition & 1 deletion perception/autoware_lidar_centerpoint/README.md
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Expand Up @@ -36,7 +36,6 @@ Note that these parameters are associated with ONNX file, predefined during the
| -------------------------------------- | ------------ | ------------------------------------------------ | --------------------------------------------------------------------- |
| `model_params.class_names` | list[string] | ["CAR", "TRUCK", "BUS", "BICYCLE", "PEDESTRIAN"] | list of class names for model outputs |
| `model_params.point_feature_size` | int | `4` | number of features per point in the point cloud |
| `model_params.max_voxel_size` | int | `40000` | maximum number of voxels |
| `model_params.point_cloud_range` | list[double] | [-76.8, -76.8, -4.0, 76.8, 76.8, 6.0] | detection range [min_x, min_y, min_z, max_x, max_y, max_z] [m] |
| `model_params.voxel_size` | list[double] | [0.32, 0.32, 10.0] | size of each voxel [x, y, z] [m] |
| `model_params.downsample_factor` | int | `1` | downsample factor for coordinates |
Expand All @@ -61,6 +60,7 @@ Note that these parameters are associated with ONNX file, predefined during the
| `post_process_params.has_twist` | boolean | false | Indicates whether the model outputs twist value. |
| `densification_params.world_frame_id` | string | `map` | the world frame id to fuse multi-frame pointcloud |
| `densification_params.num_past_frames` | int | `1` | the number of past frames to fuse with the current frame |
| `max_voxel_size` | int | `40000` | maximum number of voxels |

### The `build_only` option

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1 change: 1 addition & 0 deletions perception/autoware_lidar_centerpoint/config/centerpoint.param.yaml
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Expand Up @@ -17,3 +17,4 @@
densification_params:
world_frame_id: map
num_past_frames: 1
max_voxel_size: 40000
1 change: 0 additions & 1 deletion perception/autoware_lidar_centerpoint/config/centerpoint_ml_package.param.yaml
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Expand Up @@ -3,7 +3,6 @@
model_params:
class_names: ["CAR", "TRUCK", "BUS", "BICYCLE", "PEDESTRIAN"]
point_feature_size: 4
max_voxel_size: 40000
point_cloud_range: [-76.8, -76.8, -4.0, 76.8, 76.8, 6.0]
voxel_size: [0.32, 0.32, 10.0]
downsample_factor: 1
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1 change: 1 addition & 0 deletions perception/autoware_lidar_centerpoint/config/centerpoint_sigma.param.yaml
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Expand Up @@ -18,3 +18,4 @@
densification_params:
world_frame_id: map
num_past_frames: 1
max_voxel_size: 40000
1 change: 0 additions & 1 deletion perception/autoware_lidar_centerpoint/config/centerpoint_sigma_ml_package.param.yaml
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Expand Up @@ -3,7 +3,6 @@
model_params:
class_names: ["CAR", "TRUCK", "BUS", "BICYCLE", "PEDESTRIAN"]
point_feature_size: 4
max_voxel_size: 40000
point_cloud_range: [-76.8, -76.8, -4.0, 76.8, 76.8, 6.0]
voxel_size: [0.32, 0.32, 10.0]
downsample_factor: 1
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1 change: 1 addition & 0 deletions perception/autoware_lidar_centerpoint/config/centerpoint_tiny.param.yaml
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Expand Up @@ -17,3 +17,4 @@
densification_params:
world_frame_id: map
num_past_frames: 1
max_voxel_size: 40000
1 change: 0 additions & 1 deletion perception/autoware_lidar_centerpoint/config/centerpoint_tiny_ml_package.param.yaml
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Expand Up @@ -3,7 +3,6 @@
model_params:
class_names: ["CAR", "TRUCK", "BUS", "BICYCLE", "PEDESTRIAN"]
point_feature_size: 4
max_voxel_size: 40000
point_cloud_range: [-76.8, -76.8, -4.0, 76.8, 76.8, 6.0]
voxel_size: [0.32, 0.32, 10.0]
downsample_factor: 2
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5 changes: 5 additions & 0 deletions perception/autoware_lidar_centerpoint/schema/centerpoint.schemal.json
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Expand Up @@ -78,6 +78,11 @@
"minimum": 0
}
}
},
"max_voxel_size": {
"type": "integer",
"description": "A maximum size of voxel grid.",
"default": 40000
}
},
"required": ["post_process_params", "densification_params"]
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5 changes: 0 additions & 5 deletions perception/autoware_lidar_centerpoint/schema/centerpoint_ml_package.schema.json
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Expand Up @@ -21,11 +21,6 @@
"description": "A number of channels of point feature layer.",
"default": 4
},
"max_voxel_size": {
"type": "integer",
"description": "A maximum size of voxel grid.",
"default": 40000
},
"point_cloud_range": {
"type": "array",
"description": "An array of distance ranges of each class, this must have same length with `class_names`.",
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5 changes: 0 additions & 5 deletions perception/autoware_lidar_centerpoint/schema/centerpoint_tiny_ml_package.schema.json
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Expand Up @@ -21,11 +21,6 @@
"description": "A number of channels of point feature layer.",
"default": 4
},
"max_voxel_size": {
"type": "integer",
"description": "A maximum size of voxel grid.",
"default": 40000
},
"point_cloud_range": {
"type": "array",
"description": "An array of distance ranges of each class, this must have same length with `class_names`.",
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2 changes: 1 addition & 1 deletion perception/autoware_lidar_centerpoint/src/node.cpp
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Expand Up @@ -62,7 +62,7 @@
this->declare_parameter<std::int64_t>("model_params.point_feature_size"));
has_variance_ = this->declare_parameter<bool>("model_params.has_variance");
const std::size_t max_voxel_size =
static_cast<std::size_t>(this->declare_parameter<std::int64_t>("model_params.max_voxel_size"));
static_cast<std::size_t>(this->declare_parameter<std::int64_t>("max_voxel_size"));

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const auto point_cloud_range =
this->declare_parameter<std::vector<double>>("model_params.point_cloud_range");
const auto voxel_size = this->declare_parameter<std::vector<double>>("model_params.voxel_size");
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