Verify YOLO heatmap generation in deep acceptance

backend/app/agents/evaluation_agent.py

@@ -34,6 +34,7 @@ def evaluate_project() -> dict:
 
     frontend_text = frontend.read_text(encoding="utf-8") if frontend.exists() else ""
     backend_text = backend.read_text(encoding="utf-8") if backend.exists() else ""
+    acceptance_text = (settings.project_root / "backend" / "app" / "acceptance.py").read_text(encoding="utf-8")
     readme_text = readme.read_text(encoding="utf-8") if readme.exists() else ""
 
     expectations = {
@@ -44,6 +45,7 @@ def evaluate_project() -> dict:
         "curve_api": "/api/results/curves" in backend_text,
         "deep_acceptance_api": "/api/acceptance/deep" in backend_text,
         "deep_acceptance_ui": "runDeepAcceptance" in frontend_text and "深度训练" in frontend_text,
+        "deep_yolo_heatmap_validation": "yolo_tiny_heatmap_generation" in acceptance_text,
         "coverage_api": "/api/coverage" in backend_text and coverage["task_build_passed"],
         "visual_tools": "visual.yolo11_heatmap_v2" in catalog["task_types"] and "visual.fps" in catalog["task_types"],
         "yolo_dataset_tools": "dataset.yolo_txt_sort" in catalog["task_types"] and "dataset.yolo_resize" in catalog["task_types"],
@@ -64,7 +66,7 @@ def evaluate_project() -> dict:
     if coverage["unmapped_user_scripts"]:
         suggestions.append(f"Map remaining user-facing scripts: {len(coverage['unmapped_user_scripts'])}")
     if not suggestions:
-        suggestions.append("Current platform covers the requested control-plane features; next focus is real dataset/training acceptance tests.")
+        suggestions.append("Current platform covers the requested control-plane features and synthetic deep training/heatmap acceptance; next focus is a user-supplied dataset end-to-end run.")
 
     score = sum(1 for item in checks if item["passed"]) / max(len(checks), 1)
     return {