s6.app.pipeline.v1

class s6.app.pipeline.v1.PipelineConfigV1(*, pipeline_name: str = 'PipelineV1', platform: PlatformConfig = None, run_cpp: bool = False, run_level: RunLevel = RunLevel.NORMAL, calibration_file: str = 'configs/calibration.config.json', tracking: TrackingConfig = None, solver: SolverConfig = None, detection: DetectionConfig = None, refine: RefineConfig = None, boundary: BoundaryConfig = None, tip: TipConfig = None, export: ExportConfig = None, demo_mode: bool = False)

Bases: PipelineConfigBase

Root configuration for s6.app.pipeline.v1.PipelineV1.

tracking: TrackingConfig

solver: SolverConfig

detection: DetectionConfig

refine: RefineConfig

boundary: BoundaryConfig

tip: TipConfig

export: ExportConfig

demo_mode: bool

static load_default() → PipelineConfigV1

s6.app.pipeline.v1.PipelineConfig

alias of PipelineConfigV1

class s6.app.pipeline.v1.PipelineV1(config: str | PipelineConfigBase | None = None)

Bases: BasePipeline

Main Sense Core inference pipeline implementation.

config_model

alias of PipelineConfigV1

viewport(view: Any, visual_tree: Any) → None

load_models() → None

load_calibrations() → None

static bgr2gray(image: ndarray) → ndarray

array_copy(context: Dict[str, Any]) → None

detect_markers(context: Dict[str, Any], context_key: str, prev_context: Dict[str, Any] | None = None) → List[Vector2D]

refine_markers(context: Dict[str, Any], context_key: str) → None

boundary_stage(context: Dict[str, Any], prev_context: Dict[str, Any] | None = None) → None

triangulate_markers(context: Dict[str, Any], prev_context: Dict[str, Any] | None = None) → List[Vector3D]

tips_search(context: Dict[str, Any]) → None

tips_solve(context: Dict[str, Any]) → None

experimental_prong_tip_detection(context: Dict[str, Any]) → None