#include <cstdint>
#include <memory>
#include <span>
#include <variant>
#include <vector>

Include dependency graph for TensorBuffer.hpp:

This graph shows which files directly or indirectly include this file:

Classes
struct	TensorBuffer< T, Format, FORMAT_CONSTANT >

Typedefs
template<FloatTensorFormat FORMAT>
using	FloatTensorBuffer = TensorBuffer<float, FloatTensorFormat, FORMAT>

Enumerations
enum class	FloatTensorFormat : std::uint8_t { ImageRGB , ImageRGB255 , MiDaSImageRGB , YoloImageRGB , RelativeDepth , RawRelativeDepth , Rel2AbsDepthInput , Rel2AbsDepthCoefficientOutput , MetricDepth , YoloOutput , NLPOutput , NLPInput }

Functions
std::string_view	format_float_tensor_format (FloatTensorFormat format)

Typedef Documentation

◆ FloatTensorBuffer

template<FloatTensorFormat FORMAT>

enum class FloatTensorFormat : std::uint8_t

strong

Enumerator
ImageRGB	3 floats for r, g, b, all in range [0.f, 1.f]
ImageRGB255	3 floats for r, g, b, all in range [0.f, 255.f]
MiDaSImageRGB	3 floats for r, g, b, each in the range [-1.f, 1.f]
YoloImageRGB	3 floats for r, g, b, all in range [0.f, 1.f]
RelativeDepth	1 float per pixel for relative depth in range [0.f, 1.f]
RawRelativeDepth	1 float per pixel for relative depth, all values possible
Rel2AbsDepthInput	4 floats per pixel (RGBD) where RGB is in range [-1.f, 1.f] (colorspace: sRGB) and D is the raw relative depth remapped from [0.f, 1500.f] to [-1.f, 1.f] (and clamped!)
Rel2AbsDepthCoefficientOutput	simple float array of the coefficients of the polynomial relative to absolute function produced by the RelToAbs model
MetricDepth	1 float per pixel for metric depth in meters
YoloOutput	special yolo output of detected objects and their confidence
NLPOutput	output for nlp model
NLPInput	input string for nlp

std::string_view format_float_tensor_format ( FloatTensorFormat format )