phase 4

core/detect/state.py

@@ -0,0 +1,43 @@
+"""
+LangGraph state definition for the detection pipeline.
+
+This TypedDict flows through all graph nodes. Each node reads what
+it needs and writes its outputs. LangGraph manages the state transitions.
+"""
+
+from __future__ import annotations
+
+from typing import TypedDict
+
+from core.detect.models import BoundingBox, BrandDetection, DetectionReport, Frame, PipelineStats, TextCandidate
+
+
+class DetectState(TypedDict, total=False):
+    # Input
+    video_path: str
+    job_id: str
+    profile_name: str
+    source_asset_id: str  # UUID of the source MediaAsset
+
+    # Stage outputs
+    frames: list[Frame]
+    filtered_frames: list[Frame]
+    field_masks: dict  # {seq: np.ndarray} — pitch mask per frame
+    field_boundaries: dict  # {seq: [(x,y), ...]} — pitch boundary per frame
+    field_coverage: dict  # {seq: float} — pitch coverage ratio per frame
+    edge_regions_by_frame: dict[int, list[BoundingBox]]
+    boxes_by_frame: dict[int, list[BoundingBox]]
+    preprocessed_crops: dict  # "{frame_seq}_{box_idx}" → np.ndarray
+    text_candidates: list[TextCandidate]
+    unresolved_candidates: list[TextCandidate]
+    detections: list[BrandDetection]
+    report: DetectionReport
+
+    # Session brands (accumulated during the run, persisted to DB)
+    session_brands: dict  # {normalized_name: canonical_name}
+
+    # Running stats (updated by each stage)
+    stats: PipelineStats
+
+    # Config overrides for replay (merged into profile configs dict)
+    config_overrides: dict