rerun::archetypes::SegmentationImage Struct Reference

Archetype: An image made up of integer class-ids. More...

#include <rerun/archetypes/segmentation_image.hpp>

Public Types
using	IndicatorComponent = rerun::components::IndicatorComponent< IndicatorComponentName >
	Indicator component, used to identify the archetype when converting to a list of components.

Public Member Functions
	SegmentationImage (Collection< datatypes::TensorDimension > shape, datatypes::TensorBuffer buffer)
	New segmentation image from height/width and tensor buffer.
	SegmentationImage (components::TensorData data_)
	New segmentation image from tensor data.
template<typename TElement >
	SegmentationImage (Collection< datatypes::TensorDimension > shape, const TElement *data_)
	New segmentation image from dimensions and pointer to segmentation image data.
	SegmentationImage (SegmentationImage &&other)=default
SegmentationImage	with_draw_order (rerun::components::DrawOrder _draw_order) &&
	An optional floating point value that specifies the 2D drawing order.
size_t	num_instances () const
	Returns the number of primary instances of this archetype.

Public Attributes
rerun::components::TensorData	data
	The image data. Should always be a rank-2 tensor.
std::optional< rerun::components::DrawOrder >	draw_order
	An optional floating point value that specifies the 2D drawing order.

Static Public Attributes
static constexpr const char	IndicatorComponentName []

Detailed Description

Archetype: An image made up of integer class-ids.

The shape of the TensorData must be mappable to an HxW tensor. Each pixel corresponds to a class-id that will be mapped to a color based on annotation context.

In the case of floating point images, the label will be looked up based on rounding to the nearest integer value.

Leading and trailing unit-dimensions are ignored, so that 1x640x480x1 is treated as a 640x480 image.

Since the underlying rerun::datatypes::TensorData uses rerun::Collection internally, data can be passed in without a copy from raw pointers or by reference from std::vector/std::array/c-arrays. If needed, this "borrow-behavior" can be extended by defining your own rerun::CollectionAdapter.

Example

Simple segmentation image

#include <rerun.hpp>
 
#include <algorithm> // std::fill_n
#include <vector>
 
int main() {
    const auto rec = rerun::RecordingStream("rerun_example_segmentation_image");
    rec.spawn().exit_on_failure();
 
    // Create a segmentation image
    const int HEIGHT = 8;
    const int WIDTH = 12;
    std::vector<uint8_t> data(WIDTH * HEIGHT, 0);
    for (auto y = 0; y <4; ++y) {                                         // top half
        std::fill_n(data.begin() + y * WIDTH, 6, static_cast<uint8_t>(1)); // left half
    }
    for (auto y = 4; y <8; ++y) {                                             // bottom half
        std::fill_n(data.begin() + y * WIDTH + 6, 6, static_cast<uint8_t>(2)); // right half
    }
 
    // create an annotation context to describe the classes
    rec.log_timeless(
        "/",
        rerun::AnnotationContext({
            rerun::AnnotationInfo(1, "red", rerun::Rgba32(255, 0, 0)),
            rerun::AnnotationInfo(2, "green", rerun::Rgba32(0, 255, 0)),
        })
    );
 
    rec.log("image", rerun::SegmentationImage({HEIGHT, WIDTH}, data));
}

Constructor & Destructor Documentation

SegmentationImage() [1/3]

rerun::archetypes::SegmentationImage::SegmentationImage ( Collection< datatypes::TensorDimension >  shape, datatypes::TensorBuffer  buffer  )

inline

New segmentation image from height/width and tensor buffer.

Parameters

shape	Shape of the image. Calls Error::handle() if the shape is not rank 2. Sets the dimension names to "height" and "width" if they are not specified.
buffer	The tensor buffer containing the segmentation image data.

SegmentationImage() [2/3]

rerun::archetypes::SegmentationImage::SegmentationImage ( components::TensorData  data_ )

explicit

New segmentation image from tensor data.

Parameters

data_

The tensor buffer containing the segmentation image data. Sets the dimension names to "height" and "width" if they are not specified. Calls Error::handle() if the shape is not rank 2.

SegmentationImage() [3/3]

template<typename TElement >

rerun::archetypes::SegmentationImage::SegmentationImage ( Collection< datatypes::TensorDimension >  shape, const TElement *  data_  )

inlineexplicit

New segmentation image from dimensions and pointer to segmentation image data.

Type must be one of the types supported by rerun::datatypes::TensorData.

Parameters

shape	Shape of the image. Calls Error::handle() if the shape is not rank 2. Sets the dimension names to "height", "width" and "channel" if they are not specified. Determines the number of elements expected to be in data.
data_	Target of the pointer must outlive the archetype.

Member Function Documentation

with_draw_order()

SegmentationImage rerun::archetypes::SegmentationImage::with_draw_order ( rerun::components::DrawOrder  _draw_order ) &&

inline

An optional floating point value that specifies the 2D drawing order.

Objects with higher values are drawn on top of those with lower values.

Member Data Documentation

draw_order

std::optional<rerun::components::DrawOrder> rerun::archetypes::SegmentationImage::draw_order

An optional floating point value that specifies the 2D drawing order.

Objects with higher values are drawn on top of those with lower values.

IndicatorComponentName

constexpr const char rerun::archetypes::SegmentationImage::IndicatorComponentName[]

staticconstexpr

Initial value:

=
            "rerun.components.SegmentationImageIndicator"

---

The documentation for this struct was generated from the following file:

• rerun/archetypes/segmentation_image.hpp