Struct Decoder 

pub struct Decoder {
    pub iou_threshold: f32,
    pub score_threshold: f32,
    pub nms: Option<Nms>,
    /* private fields */
}

Fields

iou_threshold: f32

score_threshold: f32

nms: Option<Nms>

NMS mode: Some(mode) applies NMS, None bypasses NMS (for end-to-end models)

Implementations

impl Decoder

pub fn model_type(&self) -> &ModelType

This function returns the parsed model type of the decoder.

Examples

    let decoder = DecoderBuilder::default()
        .with_config_yaml_str(config_yaml)
        .build()?;
    assert!(matches!(
        decoder.model_type(),
        ModelType::ModelPackDetSplit { .. }
    ));

pub fn normalized_boxes(&self) -> Option<bool>

Returns the box coordinate format if known from the model config.

• Some(true): Boxes are in normalized [0,1] coordinates
• Some(false): Boxes are in pixel coordinates relative to model input
• None: Unknown, caller must infer (e.g., check if any coordinate > 1.0)

This is determined by the model config’s normalized field, not the NMS mode. When coordinates are in pixels or unknown, the caller may need to normalize using the model input dimensions.

Examples

    let decoder = DecoderBuilder::default()
        .with_config_yaml_str(config_yaml)
        .build()?;
    // Config doesn't specify normalized, so it's None
    assert!(decoder.normalized_boxes().is_none());

pub fn decode( &self, outputs: &[&TensorDyn], output_boxes: &mut Vec<DetectBox>, output_masks: &mut Vec<Segmentation>, ) -> Result<(), DecoderError>

Decode model outputs into detection boxes and segmentation masks.

This is the primary decode API. Accepts TensorDyn outputs directly from model inference. Automatically dispatches to quantized or float paths based on the tensor dtype.

Arguments

• outputs - Tensor outputs from model inference
• output_boxes - Destination for decoded detection boxes (cleared first)
• output_masks - Destination for decoded segmentation masks (cleared first)

Errors

Returns DecoderError if tensor mapping fails, dtypes are unsupported, or the outputs don’t match the decoder’s model configuration.

pub fn decode_proto( &self, outputs: &[&TensorDyn], output_boxes: &mut Vec<DetectBox>, ) -> Result<Option<ProtoData>, DecoderError>

Decode model outputs into detection boxes, returning raw proto data for segmentation models instead of materialized masks.

Accepts TensorDyn outputs directly from model inference. Returns Ok(None) for detection-only and ModelPack models. Returns Ok(Some(ProtoData)) for YOLO segmentation models.

Arguments

• outputs - Tensor outputs from model inference
• output_boxes - Destination for decoded detection boxes (cleared first)

Errors

Returns DecoderError if tensor mapping fails, dtypes are unsupported, or the outputs don’t match the decoder’s model configuration.

Trait Implementations

impl Clone for Decoder

fn clone(&self) -> Decoder

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for Decoder

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

Formats the value using the given formatter.

impl PartialEq for Decoder

fn eq(&self, other: &Decoder) -> 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 StructuralPartialEq for Decoder