14 pre_cfg.
x_min = -1.0f;
16 pre_cfg.
y_min = -1.0f;
18 pre_cfg.
z_min = -1.0f;
28 const int num_pillars = 4;
29 const int num_classes = 2;
30 float focal_logits[num_pillars] = {2.0f, -2.0f, 2.0f, -2.0f};
31 std::vector<float> size_posterior(
static_cast<std::size_t
>(num_pillars * num_classes * 3), 1.0f);
32 float class_logits[num_pillars * num_classes] = {0.1f, 0.9f, 0.1f, 0.9f, 0.1f, 0.9f, 0.1f, 0.9f};
33 std::vector<float> reg_logits(
static_cast<std::size_t
>(num_pillars * num_classes * 7), 0.0f);
49 const std::size_t expected_boxes = 2;
50 assert(boxes.size() == expected_boxes);
bool IsPointValid(float x, float y, float z) const
PillarGrid BuildPillarGrid(const std::array< int, 2 > &pillar_map_size, const std::array< std::array< float, 2 >, 3 > &pillar_map_range, int first_up_stride, int stride)
std::vector< BoundingBox > DecodePbod(const PbodOutputsView &outputs, const PillarGrid &grid, const PbodPostprocessConfig &config)
const float * focal_logits
Shape [num_pillars].
int num_classes
Number of semantic classes.
int reg_dim
Regression values per pillar and class.
int num_pillars
Number of spatial pillars.
const float * class_logits
Shape [num_pillars, num_classes].
const float * size_posterior
Shape [num_pillars, num_classes * 3].
const float * reg_logits
Shape [num_pillars, num_classes * reg_dim].
std::vector< float > score_thresholds
Per-class thresholds, or one shared threshold.
std::vector< std::string > class_names
Class name in model-output order.
float x_max
Maximum accepted X coordinate.
float value_threshold
Divisor for value-threshold normalization.
float y_min
Minimum accepted Y coordinate.
float z_min
Minimum accepted Z coordinate.
float x_min
Minimum accepted X coordinate.
float z_max
Maximum accepted Z coordinate.
float y_max
Maximum accepted Y coordinate.
PointFeatureNormalizationType normalization_type
Feature transform.