@@ -26,9 +26,8 @@ class TransfusionConfig
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public:
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TransfusionConfig (
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const std::vector<int64_t > & voxels_num, const std::vector<double > & point_cloud_range,
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- const std::vector<double > & voxel_size, const int num_proposals,
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- const float circle_nms_dist_threshold, const std::vector<double > & yaw_norm_thresholds,
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- const float score_threshold)
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+ const std::vector<double > & voxel_size, const float circle_nms_dist_threshold,
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+ const std::vector<double > & yaw_norm_thresholds, const float score_threshold)
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{
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if (voxels_num.size () == 3 ) {
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max_voxels_ = voxels_num[2 ];
@@ -62,9 +61,6 @@ class TransfusionConfig
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voxel_y_size_ = static_cast <float >(voxel_size[1 ]);
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voxel_z_size_ = static_cast <float >(voxel_size[2 ]);
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}
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- if (num_proposals > 0 ) {
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- num_proposals_ = num_proposals;
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- }
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if (score_threshold > 0.0 ) {
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score_threshold_ = score_threshold;
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}
@@ -80,9 +76,6 @@ class TransfusionConfig
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grid_x_size_ = static_cast <std::size_t >((max_x_range_ - min_x_range_) / voxel_x_size_);
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grid_y_size_ = static_cast <std::size_t >((max_y_range_ - min_y_range_) / voxel_y_size_);
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grid_z_size_ = static_cast <std::size_t >((max_z_range_ - min_z_range_) / voxel_z_size_);
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-
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- feature_x_size_ = grid_x_size_ / out_size_factor_;
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- feature_y_size_ = grid_y_size_ / out_size_factor_;
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}
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// /// INPUT PARAMETERS /////
@@ -114,7 +107,7 @@ class TransfusionConfig
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const std::size_t out_size_factor_{4 };
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const std::size_t max_num_points_per_pillar_{points_per_voxel_};
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const std::size_t num_point_values_{4 };
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- std::size_t num_proposals_{200 };
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+ const std::size_t num_proposals_{200 };
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// the number of feature maps for pillar scatter
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const std::size_t num_feature_scatter_{pillar_feature_size_};
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// the score threshold for classification
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