ReUseX::vision Namespace Reference

Namespaces
namespace	common
namespace	libtorch
namespace	osd
namespace	tensor_rt

Classes
class	BackendFactory
class	Dataloader
struct	IData
class	IDataset
class	IMLBackend
class	IModel

Enumerations
enum class	Backend {   OpenCV , TensorRT , libTorch , DNN ,   ONNXRuntime , OpenVINO , Unknown }
enum class	Model { Yolo , Sam3 }

Functions
auto	annotateRTABMap (const std::filesystem::path &dbPath, const std::filesystem::path &modelPath, bool isCuda) -> int
auto	annotate (const std::filesystem::path &dbPath, const std::filesystem::path &modelPath) -> int
auto	project (const std::filesystem::path &dbPath, CloudConstPtr cloud) -> CloudLPtr
	Project the labels stored in the database on tho the assebled point cloud.
float	generate_scale (cv::Mat &image, const cv::Size &target_size, bool scale_up=false)
float	letterbox (cv::Mat &input_image, cv::Mat &output_image, const cv::Size &target_size)
float	cropbox (cv::Mat &input_image, cv::Mat &output_image, const cv::Size &target_size)
torch::Tensor	xyxy_to_xywh (const torch::Tensor &x)
torch::Tensor	xywh_to_xyxy (const torch::Tensor &x)
torch::Tensor	nms (const torch::Tensor &bboces, const torch::Tensor &scores, float iou_threshold=0.45)
torch::Tensor	non_max_suppression (torch::Tensor &predictions, float confThreshold=0.25, float iouThreshold=0.45, int maxDetections=300)
torch::Tensor	xyxy2xywh (const torch::Tensor &x)
torch::Tensor	xywh2xyxy (const torch::Tensor &x)

Variables
std::vector< std::string >	Yolov8_className
	YOLO v8 class names for object detection.

Enumeration Type Documentation

Backend

enum class ReUseX::vision::Backend

strong

Enumerator
OpenCV
TensorRT
libTorch
DNN
ONNXRuntime
OpenVINO
Unknown

Definition at line 10 of file BackendFactory.hpp.

Model

enum class ReUseX::vision::Model

strong

Enumerator
Yolo
Sam3

Definition at line 8 of file IMLBackend.hpp.

Function Documentation

annotate()

auto ReUseX::vision::annotate	(	const std::filesystem::path &	dbPath,
		const std::filesystem::path &	modelPath ) -> int

annotateRTABMap()

auto ReUseX::vision::annotateRTABMap	(	const std::filesystem::path &	dbPath,
		const std::filesystem::path &	modelPath,
		bool	isCuda ) -> int

cropbox()

float ReUseX::vision::cropbox	(	cv::Mat &	input_image,
		cv::Mat &	output_image,
		const cv::Size &	target_size )

generate_scale()

float ReUseX::vision::generate_scale	(	cv::Mat &	image,
		const cv::Size &	target_size,
		bool	scale_up = false )

letterbox()

float ReUseX::vision::letterbox	(	cv::Mat &	input_image,
		cv::Mat &	output_image,
		const cv::Size &	target_size )

nms()

torch::Tensor ReUseX::vision::nms	(	const torch::Tensor &	bboces,
		const torch::Tensor &	scores,
		float	iou_threshold = 0.45 )

non_max_suppression()

torch::Tensor ReUseX::vision::non_max_suppression	(	torch::Tensor &	predictions,
		float	confThreshold = 0.25,
		float	iouThreshold = 0.45,
		int	maxDetections = 300 )

project()

auto ReUseX::vision::project	(	const std::filesystem::path &	dbPath,
		CloudConstPtr	cloud ) -> CloudLPtr

Project the labels stored in the database on tho the assebled point cloud.

For each view in the database this constructs a croped point cloud, computes a z-buffer and the assigns the precomputed labels to the closses point in the point cloud.

xywh2xyxy()

torch::Tensor ReUseX::vision::xywh2xyxy ( const torch::Tensor & x )

inline

Definition at line 36 of file utils.hpp.

References xywh_to_xyxy().

xywh_to_xyxy()

torch::Tensor ReUseX::vision::xywh_to_xyxy

(

const torch::Tensor &

x

)

Referenced by xywh2xyxy().

xyxy2xywh()

torch::Tensor ReUseX::vision::xyxy2xywh ( const torch::Tensor & x )

inline

Definition at line 32 of file utils.hpp.

References xyxy_to_xywh().

xyxy_to_xywh()

torch::Tensor ReUseX::vision::xyxy_to_xywh

(

const torch::Tensor &

x

)

Referenced by xyxy2xywh().

Variable Documentation

Yolov8_className

std::vector<std::string> ReUseX::vision::Yolov8_className

extern

YOLO v8 class names for object detection.

Contains the list of class names that can be detected by YOLO v8 model.