"""
approbot_pipeline
=================
Roboter-Pose-Schätzung aus Mehrkamera-ArUco-Bildern.

Zwei Interfaces, gleiche Logik darunter:

  (A) Python-Bibliothek — direkt einbindbar:
        from approbot_pipeline import estimate_from_dir, PipelineResult
        result = estimate_from_dir("path/to/images", robot_json="robot.json")
        print(result.joints)          # {"x": 50.2, "y": -2.1, ...}
        print(result.confidence)      # {"x": "high", "b": "low", ...}

  (B) REST-API — läuft als Service im Docker-Container:
        POST /v1/estimate   (multipart: images + intrinsics)
        GET  /v1/health
        GET  /v1/config
        → JSON mit joints, confidence, residual_rms, processing_ms
"""
from approbot_pipeline.pipeline import estimate_from_dir, PipelineResult

__version__ = "1.0.0"
__all__ = ["estimate_from_dir", "PipelineResult", "__version__"]