phase 3

detect/profiles/soccer.py

@@ -2,6 +2,7 @@
 
 from __future__ import annotations
 
+from core.schema.models.pipeline_config import PipelineConfig
 from detect.models import BrandDetection, BrandStats, DetectionReport, PipelineStats
 
 from .base import (
@@ -12,12 +13,46 @@ from .base import (
     RegionAnalysisConfig,
     ResolverConfig,
     SceneFilterConfig,
+    pipeline_config_from_dict,
 )
 
 
 class SoccerBroadcastProfile:
     name = "soccer_broadcast"
 
+    # Pipeline topology as JSONB — will be a DB field when profiles are persisted
+    pipeline = {
+        "name": "soccer_broadcast",
+        "profile_name": "soccer_broadcast",
+        "stages": [
+            {"name": "extract_frames", "branch": "trunk"},
+            {"name": "filter_scenes", "branch": "trunk"},
+            {"name": "detect_edges", "branch": "hoarding"},
+            {"name": "detect_objects", "branch": "objects"},
+            {"name": "preprocess"},
+            {"name": "run_ocr"},
+            {"name": "match_brands"},
+            {"name": "escalate_vlm"},
+            {"name": "escalate_cloud"},
+            {"name": "compile_report"},
+        ],
+        "edges": [
+            {"source": "extract_frames", "target": "filter_scenes"},
+            {"source": "filter_scenes", "target": "detect_edges"},
+            {"source": "filter_scenes", "target": "detect_objects"},
+            {"source": "detect_edges", "target": "preprocess"},
+            {"source": "detect_objects", "target": "preprocess"},
+            {"source": "preprocess", "target": "run_ocr"},
+            {"source": "run_ocr", "target": "match_brands"},
+            {"source": "match_brands", "target": "escalate_vlm"},
+            {"source": "escalate_vlm", "target": "escalate_cloud"},
+            {"source": "escalate_cloud", "target": "compile_report"},
+        ],
+    }
+
+    def pipeline_config(self) -> PipelineConfig:
+        return pipeline_config_from_dict(self.pipeline)
+
     def frame_extraction_config(self) -> FrameExtractionConfig:
         return FrameExtractionConfig(fps=2.0, max_frames=500)