Struct SegmentationImage

pub struct SegmentationImage {
    pub buffer: Option<SerializedComponentBatch>,
    pub format: Option<SerializedComponentBatch>,
    pub opacity: Option<SerializedComponentBatch>,
    pub draw_order: Option<SerializedComponentBatch>,
}

Archetype: An image made up of integer components::ClassIds.

Each pixel corresponds to a components::ClassId that will be mapped to a color based on archetypes::AnnotationContext.

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

Use archetypes::AnnotationContext to associate each class with a color and a label.

Example

Simple segmentation image

use ndarray::{s, Array, ShapeBuilder as _};

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let rec = rerun::RecordingStreamBuilder::new("rerun_example_segmentation_image").spawn()?;

    // create a segmentation image
    let mut image = Array::<u8, _>::zeros((8, 12).f());
    image.slice_mut(s![0..4, 0..6]).fill(1);
    image.slice_mut(s![4..8, 6..12]).fill(2);

    // create an annotation context to describe the classes
    let annotation = rerun::AnnotationContext::new([
        (1, "red", rerun::Rgba32::from_rgb(255, 0, 0)),
        (2, "green", rerun::Rgba32::from_rgb(0, 255, 0)),
    ]);

    // log the annotation and the image
    rec.log_static("/", &annotation)?;

    rec.log("image", &rerun::SegmentationImage::try_from(image)?)?;

    Ok(())
}

Fields

buffer: Option<SerializedComponentBatch>

The raw image data.

format: Option<SerializedComponentBatch>

The format of the image.

opacity: Option<SerializedComponentBatch>

Opacity of the image, useful for layering the segmentation image on top of another image.

Defaults to 0.5 if there’s any other images in the scene, otherwise 1.0.

draw_order: Option<SerializedComponentBatch>

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

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

Implementations

impl SegmentationImage

pub fn descriptor_buffer() -> ComponentDescriptor

Returns the ComponentDescriptor for Self::buffer.

pub fn descriptor_format() -> ComponentDescriptor

Returns the ComponentDescriptor for Self::format.

pub fn descriptor_opacity() -> ComponentDescriptor

Returns the ComponentDescriptor for Self::opacity.

pub fn descriptor_draw_order() -> ComponentDescriptor

Returns the ComponentDescriptor for Self::draw_order.

pub fn descriptor_indicator() -> ComponentDescriptor

Returns the ComponentDescriptor for the associated indicator component.

impl SegmentationImage

pub const NUM_COMPONENTS: usize = 5usize

The total number of components in the archetype: 2 required, 1 recommended, 2 optional

impl SegmentationImage

pub fn new( buffer: impl Into<ImageBuffer>, format: impl Into<ImageFormat>, ) -> SegmentationImage

Create a new SegmentationImage.

pub fn update_fields() -> SegmentationImage

Update only some specific fields of a SegmentationImage.

pub fn clear_fields() -> SegmentationImage

Clear all the fields of a SegmentationImage.

pub fn columns<I>( self, _lengths: I, ) -> Result<impl Iterator<Item = SerializedComponentColumn>, SerializationError>

where I: IntoIterator<Item = usize> + Clone,

Partitions the component data into multiple sub-batches.

Specifically, this transforms the existing SerializedComponentBatches data into SerializedComponentColumns instead, via SerializedComponentBatch::partitioned.

This makes it possible to use RecordingStream::send_columns to send columnar data directly into Rerun.

The specified lengths must sum to the total length of the component batch.

pub fn columns_of_unit_batches( self, ) -> Result<impl Iterator<Item = SerializedComponentColumn>, SerializationError>

Helper to partition the component data into unit-length sub-batches.

This is semantically similar to calling Self::columns with std::iter::take(1).repeat(n), where n is automatically guessed.

pub fn with_buffer(self, buffer: impl Into<ImageBuffer>) -> SegmentationImage

The raw image data.

pub fn with_many_buffer( self, buffer: impl IntoIterator<Item = impl Into<ImageBuffer>>, ) -> SegmentationImage

This method makes it possible to pack multiple crate::components::ImageBuffer in a single component batch.

This only makes sense when used in conjunction with Self::columns. Self::with_buffer should be used when logging a single row’s worth of data.

pub fn with_format(self, format: impl Into<ImageFormat>) -> SegmentationImage

The format of the image.

pub fn with_many_format( self, format: impl IntoIterator<Item = impl Into<ImageFormat>>, ) -> SegmentationImage

This method makes it possible to pack multiple crate::components::ImageFormat in a single component batch.

This only makes sense when used in conjunction with Self::columns. Self::with_format should be used when logging a single row’s worth of data.

pub fn with_opacity(self, opacity: impl Into<Opacity>) -> SegmentationImage

Opacity of the image, useful for layering the segmentation image on top of another image.

Defaults to 0.5 if there’s any other images in the scene, otherwise 1.0.

pub fn with_many_opacity( self, opacity: impl IntoIterator<Item = impl Into<Opacity>>, ) -> SegmentationImage

This method makes it possible to pack multiple crate::components::Opacity in a single component batch.

This only makes sense when used in conjunction with Self::columns. Self::with_opacity should be used when logging a single row’s worth of data.

pub fn with_draw_order( self, draw_order: impl Into<DrawOrder>, ) -> SegmentationImage

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

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

pub fn with_many_draw_order( self, draw_order: impl IntoIterator<Item = impl Into<DrawOrder>>, ) -> SegmentationImage

This method makes it possible to pack multiple crate::components::DrawOrder in a single component batch.

This only makes sense when used in conjunction with Self::columns. Self::with_draw_order should be used when logging a single row’s worth of data.

impl SegmentationImage

pub fn try_from<T>( data: T, ) -> Result<SegmentationImage, ImageConstructionError<T>>

where T: TryInto<TensorData>, <T as TryInto<TensorData>>::Error: Error,

Try to construct a SegmentationImage from anything that can be converted into TensorData

Will return an ImageConstructionError if the shape of the tensor data is invalid for treating as an image.

This is useful for constructing a SegmentationImage from an ndarray.

Trait Implementations

impl Archetype for SegmentationImage

type Indicator = GenericIndicatorComponent<SegmentationImage>

The associated indicator component, whose presence indicates that the high-level archetype-based APIs were used to log the data.

fn name() -> ArchetypeName

The fully-qualified name of this archetype, e.g. rerun.archetypes.Points2D.

fn display_name() -> &'static str

Readable name for displaying in UI.

fn indicator() -> SerializedComponentBatch

Creates a ComponentBatch out of the associated Self::Indicator component.

fn required_components() -> Cow<'static, [ComponentDescriptor]>

Returns all component descriptors that must be provided by the user when constructing this archetype.

fn recommended_components() -> Cow<'static, [ComponentDescriptor]>

Returns all component descriptors that should be provided by the user when constructing this archetype.

fn optional_components() -> Cow<'static, [ComponentDescriptor]>

Returns all component descriptors that may be provided by the user when constructing this archetype.

fn all_components() -> Cow<'static, [ComponentDescriptor]>

Returns all component descriptors that must, should and may be provided by the user when constructing this archetype.

fn from_arrow_components( arrow_data: impl IntoIterator<Item = (ComponentDescriptor, Arc<dyn Array>)>, ) -> Result<SegmentationImage, DeserializationError>

Given an iterator of Arrow arrays and their respective ComponentNames, deserializes them into this archetype.

fn from_arrow( data: impl IntoIterator<Item = (Field, Arc<dyn Array>)>, ) -> Result<Self, DeserializationError>

where Self: Sized,

Given an iterator of Arrow arrays and their respective field metadata, deserializes them into this archetype.

impl AsComponents for SegmentationImage

fn as_serialized_batches(&self) -> Vec<SerializedComponentBatch>

Exposes the object’s contents as a set of SerializedComponentBatches.

fn to_arrow(&self) -> Result<Vec<(Field, Arc<dyn Array>)>, SerializationError>

Serializes all non-null Components of this bundle into Arrow arrays.

impl Clone for SegmentationImage

fn clone(&self) -> SegmentationImage

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for SegmentationImage

fn fmt(&self, f: &mut Formatter<'_>) -> Result<(), Error>

Formats the value using the given formatter.

impl Default for SegmentationImage

fn default() -> SegmentationImage

Returns the “default value” for a type.

impl PartialEq for SegmentationImage

fn eq(&self, other: &SegmentationImage) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl SizeBytes for SegmentationImage

fn heap_size_bytes(&self) -> u64

Returns how many bytes self uses on the heap.

fn total_size_bytes(&self) -> u64

Returns the total size of self in bytes, accounting for both stack and heap space.

fn stack_size_bytes(&self) -> u64

Returns the total size of self on the stack, in bytes.

fn is_pod() -> bool

Is Self just plain old data?

impl ArchetypeReflectionMarker for SegmentationImage

impl StructuralPartialEq for SegmentationImage