s6.app.pipeline.t1ΒΆ

class s6.app.pipeline.t1.PipelineConfigT1(*, pipeline_name: str = 'PipelineT1', platform: PlatformConfig = None, run_cpp: bool = False, run_level: RunLevel = RunLevel.NORMAL, calibration_file: str = 'configs/calibration.config.json', tracking: TrackingConfig = None, tip: TipConfig = None, export: ExportConfig = None)

Bases: PipelineConfigBase

Root configuration for s6.app.pipeline.t1.PipelineT1.

default_config_candidates: ClassVar[Tuple[str, ...]] = ('configs/pipeline_t1.config.yaml', 'configs/pipeline_t1.config.yml', 'configs/pipeline.config.t1.yaml', 'configs/pipeline.config.t1.yml', 'configs/pipeline.config.yaml', 'configs/pipeline.config.yml')
pipeline_name: str
platform: PlatformConfig
tracking: TrackingConfig
tip: TipConfig
export: ExportConfig
static load_default() PipelineConfigT1
class s6.app.pipeline.t1.PipelineT1(config: str | PipelineConfigBase | None = None)

Bases: BasePipeline

Two-camera lower stereo pipeline that triangulates directly from LL/LR tips.

config_model

alias of PipelineConfigT1

static second_largest_threshold_component_mask(image: ndarray, percentile: float = 80.0) ndarray

Return the dilated second-largest threshold component as a binary mask.

load_models() None
load_calibrations() None
static bgr2gray(image: ndarray) ndarray
array_copy(context: Dict[str, Any]) None
viewport(view: Any, visual_tree: Any) None
point_refine_median_filter(image)
preprocess_roi_det(context: Dict[str, Any], context_key: str) None
inference_roi_det(context: Dict[str, Any], camera_keys: Tuple[str, ...]) None
postprocess_roi_det(context: Dict[str, Any], context_key: str) None
roi_det(context: Dict[str, Any]) None
roi_solve(context)