gwonxhj · hyeokjun32 · May 4, 2026 · May 4, 2026
diff --git a/examples/studio_demo/jetson_power_mode_summary.json b/examples/studio_demo/jetson_power_mode_summary.json
@@ -0,0 +1,70 @@
+{
+  "summary_role": "jetson-power-mode-comparison",
+  "schema_version": "inferedge-jetson-power-mode-summary-v1",
+  "model": "yolov8n",
+  "backend_key": "tensorrt__jetson",
+  "precision": "fp16",
+  "compare_key": "yolov8n__b1__h640w640__fp16",
+  "baseline_power_mode": "25W",
+  "candidate_power_mode": "15W",
+  "baseline_source": "examples/studio_demo/tensorrt_jetson_25w_result.json",
+  "candidate_source": "examples/studio_demo/tensorrt_jetson_15w_result.json",
+  "comparison_scope": "same TensorRT FP16 engine, same 640x640 dummy input, same warmup/runs, different Jetson power mode",
+  "run_config_status": "power_mode_changed",
+  "run_config_note": "Power mode differs, so this is system evidence for deployment review rather than a same-run_config latency regression test.",
+  "metrics": {
+    "mean_ms": {
+      "baseline_25w": 10.066401,
+      "candidate_15w": 10.799106,
+      "delta_ms": 0.732705,
+      "delta_pct": 7.278719
+    },
+    "p95_ms": {
+      "baseline_25w": 15.476641,
+      "candidate_15w": 15.43869,
+      "delta_ms": -0.037951,
+      "delta_pct": -0.245215
+    },
+    "p99_ms": {
+      "baseline_25w": 15.548438,
+      "candidate_15w": 15.529218,
+      "delta_ms": -0.01922,
+      "delta_pct": -0.123614
+    },
+    "fps_value": {
+      "baseline_25w": 99.340373,
+      "candidate_15w": 92.600262,
+      "delta": -6.740111,
+      "delta_pct": -6.784866
+    }
+  },
+  "tegrastats": {
+    "baseline_25w": {
+      "status": "parsed",
+      "sample_count": 3,
+      "max_temp_c": 40.656,
+      "max_temp_name": "gpu",
+      "vdd_in_mw_avg": 4863.0,
+      "vdd_in_mw_max": 5827.0
+    },
+    "candidate_15w": {
+      "status": "parsed",
+      "sample_count": 10,
+      "max_temp_c": 42.437,
+      "max_temp_name": "gpu",
+      "vdd_in_mw_avg": 5707.8,
+      "vdd_in_mw_max": 7120.0
+    }
+  },
+  "deployment_signal": {
+    "decision": "review_note",
+    "reason": "power mode changed; compare as Jetson system evidence",
+    "recommended_action": "Record power_mode, p95/p99 latency, FPS, and tegrastats summary with the deployment evidence."
+  },
+  "notes": [
+    "This is a short Runtime smoke, not a sustained thermal benchmark.",
+    "Power readings are supporting evidence from the captured tegrastats samples.",
+    "AIGuard remains optional; Lab owns the final deployment decision."
+  ],
+  "created_at": "2026-05-04T17:20:00Z"
+}
diff --git a/examples/studio_demo/tensorrt_jetson_15w_result.json b/examples/studio_demo/tensorrt_jetson_15w_result.json
@@ -0,0 +1,146 @@
+{
+  "schema_version": "inferedge-runtime-result-v1",
+  "compare_key": "yolov8n__b1__h640w640__fp16",
+  "backend_key": "tensorrt__jetson",
+  "runtime_role": "runtime-result",
+  "manifest_path": "/home/risenano01/InferEdgeForge/builds/yolov8n__jetson__tensorrt__jetson_fp16/metadata.json",
+  "manifest_applied": true,
+  "model_name": "model.engine",
+  "model_path": "/home/risenano01/InferEdgeForge/builds/yolov8n__jetson__tensorrt__jetson_fp16/model.engine",
+  "engine_name": "tensorrt",
+  "engine_backend": "tensorrt",
+  "device_name": "jetson",
+  "batch": 1,
+  "height": 640,
+  "width": 640,
+  "warmup": 10,
+  "runs": 50,
+  "mean_ms": 10.799106,
+  "p50_ms": 10.338849,
+  "p95_ms": 15.43869,
+  "p99_ms": 15.529218,
+  "fps_value": 92.600262,
+  "success": true,
+  "status": "success",
+  "model": {
+    "path": "/home/risenano01/InferEdgeForge/builds/yolov8n__jetson__tensorrt__jetson_fp16/model.engine",
+    "name": "model.engine"
+  },
+  "engine": {
+    "name": "tensorrt",
+    "backend": "tensorrt",
+    "available": true,
+    "status_message": "TensorRT backend is linked. Engine metadata, one-shot inference, and benchmark execution are available."
+  },
+  "device": {
+    "name": "jetson"
+  },
+  "precision": "fp16",
+  "run_config": {
+    "batch": 1,
+    "height": 640,
+    "width": 640,
+    "warmup": 10,
+    "runs": 50,
+    "power_mode": "15W",
+    "jetson_clocks": "unknown",
+    "tegrastats_log_path": "results/jetson_evidence/tegrastats_yolov8n_trt_fp16_15w_20260504T171959Z.log",
+    "manifest_path": "/home/risenano01/InferEdgeForge/builds/yolov8n__jetson__tensorrt__jetson_fp16/metadata.json",
+    "manifest_applied": true
+  },
+  "latency_ms": {
+    "mean": 10.799106,
+    "min": 8.930218,
+    "max": 15.529218,
+    "std": 1.789919,
+    "p50": 10.338849,
+    "p90": 12.319637,
+    "p95": 15.43869,
+    "p99": 15.529218
+  },
+  "fps": 92.600262,
+  "benchmark": {
+    "success": true,
+    "status": "success",
+    "message": "benchmark completed"
+  },
+  "timestamp": "2026-05-04T17:20:00Z",
+  "system": {
+    "os": "linux",
+    "compiler": "GCC",
+    "cpp_standard": "17",
+    "jetson": {
+      "power_mode": "15W",
+      "jetson_clocks": "unknown",
+      "tegrastats_log_path": "results/jetson_evidence/tegrastats_yolov8n_trt_fp16_15w_20260504T171959Z.log"
+    }
+  },
+  "jetson_evidence": {
+    "power_mode": "15W",
+    "jetson_clocks": "unknown",
+    "tegrastats_log_path": "results/jetson_evidence/tegrastats_yolov8n_trt_fp16_15w_20260504T171959Z.log",
+    "tegrastats_summary": {
+      "status": "parsed",
+      "sample_count": 10,
+      "ram_used_mb_avg": 1066.0,
+      "ram_used_mb_max": 1090.0,
+      "ram_total_mb": 7620.0,
+      "max_temp_c": 42.437,
+      "max_temp_name": "gpu",
+      "vdd_in_mw_avg": 5707.8,
+      "vdd_in_mw_max": 7120.0
+    }
+  },
+  "model_metadata": {
+    "inputs": [
+      {
+        "name": "images",
+        "element_type": "float32",
+        "shape": [
+          1,
+          3,
+          640,
+          640
+        ]
+      }
+    ],
+    "outputs": [
+      {
+        "name": "output0",
+        "element_type": "float32",
+        "shape": [
+          1,
+          84,
+          8400
+        ]
+      }
+    ]
+  },
+  "extra": {
+    "runtime": "inferedge-runtime",
+    "json_export": "enabled",
+    "output_mode": "explicit",
+    "latest_path": "results/latest.json",
+    "manifest_recorded": true,
+    "manifest_precision": "fp16",
+    "manifest_format": "engine",
+    "manifest_preset_name": "tensorrt/jetson_fp16",
+    "manifest_build_id": "yolov8n-tensorrt-jetson_fp16-20260424T133518Z",
+    "source_model_path": "models/onnx/yolov8n.onnx",
+    "source_model_sha256": "4b31ebf8213f2971b8136f7ccca475e27f40559a14bc27e0d8a531a933273eb7",
+    "runtime_artifact_sha256": "29484d824f5be2dfd3e1e801e927298f15f8e77af785711ac6fd429a7445ea22",
+    "runtime_artifact_path": "/home/risenano01/InferEdgeForge/builds/yolov8n__jetson__tensorrt__jetson_fp16/model.engine",
+    "input_mode": "dummy",
+    "input_path": "",
+    "input_preprocess": "dummy_zero_float32",
+    "power_mode": "15W",
+    "jetson_clocks": "unknown",
+    "tegrastats_log_path": "results/jetson_evidence/tegrastats_yolov8n_trt_fp16_15w_20260504T171959Z.log",
+    "tegrastats_status": "parsed",
+    "compare_ready": true,
+    "compare_key": "yolov8n__b1__h640w640__fp16",
+    "backend_key": "tensorrt__jetson",
+    "compare_model_source": "manifest_source_model",
+    "compare_model_name": "yolov8n"
+  }
+}
diff --git a/inferedgelab/studio/routes.py b/inferedgelab/studio/routes.py
@@ -35,6 +35,7 @@
 )
 LATENCY_REGRESSION_SUMMARY = "latency_regression_summary.json"
 AIGUARD_PORTFOLIO_CASES = "aiguard_portfolio_cases.json"
+JETSON_POWER_MODE_SUMMARY = "jetson_power_mode_summary.json"
 DEMO_JOB_ID = "demo_yolov8n_trt_vs_onnx"
 STATIC_ASSETS = {
     "app.js": "application/javascript",
@@ -175,6 +176,7 @@ def studio_demo_evidence(request: Request) -> dict[str, Any]:
     problem_cases = _load_demo_problem_cases()
     guard_demo_cases = _load_aiguard_portfolio_cases()
     jetson_evidence_track = _build_jetson_evidence_track(results)
+    jetson_power_mode_summary = _load_jetson_power_mode_summary()
     imported_results = _get_imported_results(request)
     imported_results.extend(results)
     guard_analysis = _build_demo_guard_analysis(results, evaluation_report)
@@ -191,6 +193,7 @@ def studio_demo_evidence(request: Request) -> dict[str, Any]:
         problem_cases,
         guard_demo_cases,
         jetson_evidence_track,
+        jetson_power_mode_summary,
     )
     _get_demo_jobs(request)[DEMO_JOB_ID] = demo_job
     return {
@@ -206,6 +209,7 @@ def studio_demo_evidence(request: Request) -> dict[str, Any]:
         "problem_cases": problem_cases,
         "guard_demo_cases": guard_demo_cases,
         "jetson_evidence_track": jetson_evidence_track,
+        "jetson_power_mode_summary": jetson_power_mode_summary,
         "guard_analysis": guard_analysis,
         "deployment_decision": compare["deployment_decision"],
     }
@@ -431,6 +435,25 @@ def _load_aiguard_portfolio_cases() -> dict[str, Any]:
     }
 
 
+def _load_jetson_power_mode_summary() -> dict[str, Any]:
+    path = DEMO_EVIDENCE_DIR / JETSON_POWER_MODE_SUMMARY
+    try:
+        summary = json.loads(path.read_text(encoding="utf-8"))
+    except OSError as exc:
+        raise HTTPException(status_code=500, detail=f"Jetson power-mode summary not found: {JETSON_POWER_MODE_SUMMARY}") from exc
+    except json.JSONDecodeError as exc:
+        raise HTTPException(status_code=500, detail=f"Jetson power-mode summary is invalid JSON: {JETSON_POWER_MODE_SUMMARY}") from exc
+
+    metrics = summary.get("metrics") if isinstance(summary, dict) else None
+    deployment_signal = summary.get("deployment_signal") if isinstance(summary, dict) else None
+    if not isinstance(metrics, dict) or not isinstance(deployment_signal, dict):
+        raise HTTPException(status_code=500, detail=f"Jetson power-mode summary schema error: {JETSON_POWER_MODE_SUMMARY}")
+
+    enriched = dict(summary)
+    enriched["source"] = f"examples/studio_demo/{JETSON_POWER_MODE_SUMMARY}"
+    return enriched
+
+
 def _load_problem_report(file_name: str) -> dict[str, Any]:
     path = VALIDATION_PROBLEM_DIR / file_name
     try:
@@ -465,6 +488,7 @@ def _build_demo_job(
     problem_cases: list[dict[str, Any]],
     guard_demo_cases: dict[str, Any],
     jetson_evidence_track: dict[str, Any],
+    jetson_power_mode_summary: dict[str, Any],
 ) -> dict[str, Any]:
     now = _utc_now_iso()
     runtime_result = results[-1] if results else {}
@@ -488,6 +512,7 @@ def _build_demo_job(
             "problem_cases": problem_cases,
             "guard_demo_cases": guard_demo_cases,
             "jetson_evidence_track": jetson_evidence_track,
+            "jetson_power_mode_summary": jetson_power_mode_summary,
             "summary": compare["judgement"]["summary"],
         },
         "error": None,

diff --git a/inferedgelab/studio/static/app.js b/inferedgelab/studio/static/app.js
@@ -33,6 +33,7 @@ let demoProblemCases = [];
 let activeGuardAnalysis = null;
 let guardDemoCases = null;
 let demoJetsonEvidence = null;
+let demoPowerModeSummary = null;
 const importedResultsByJobId = {};
 
 function createElement(tagName, className, textContent) {
@@ -377,6 +378,7 @@ async function loadDemoEvidence() {
     demoProblemCases = Array.isArray(payload.problem_cases) ? payload.problem_cases : [];
     guardDemoCases = payload.guard_demo_cases || null;
     demoJetsonEvidence = payload.jetson_evidence_track || null;
+    demoPowerModeSummary = payload.jetson_power_mode_summary || null;
     compareData = payload.compare || null;
     updateGuardEvidence(payload.guard_analysis || payload.compare?.guard_analysis || null);
     selectedJobId = payload.job_id || payload.job?.job_id || selectedJobId;
@@ -512,6 +514,17 @@ function renderDemoEvaluation(report) {
       evidenceItem("tegrastats", demoJetsonEvidence.tegrastats_status || "-"),
     );
   }
+
+  if (demoPowerModeSummary) {
+    const meanDelta = demoPowerModeSummary.metrics?.mean_ms?.delta_pct;
+    const fpsDelta = demoPowerModeSummary.metrics?.fps_value?.delta_pct;
+    target.append(
+      evidenceItem("power_compare", `${demoPowerModeSummary.baseline_power_mode || "25W"} vs ${demoPowerModeSummary.candidate_power_mode || "15W"}`),
+      evidenceItem("mean_delta", formatPercent(meanDelta)),
+      evidenceItem("fps_delta", formatPercent(fpsDelta)),
+      evidenceItem("power_note", demoPowerModeSummary.run_config_status || "-"),
+    );
+  }
 }
 
 function renderPipeline() {

diff --git a/tests/test_studio_routes.py b/tests/test_studio_routes.py
@@ -133,6 +133,7 @@ def test_studio_static_assets_include_redesigned_ui_contracts():
     assert "loadDemoEvidence" in app_text
     assert "renderDemoEvaluation" in app_text
     assert "demoJetsonEvidence" in app_text
+    assert "demoPowerModeSummary" in app_text
     assert "renderDemoProblemCases" in app_text
     assert "renderGuardEvidence" in app_text
     assert "renderGuardDemoCases" in app_text
@@ -373,6 +374,11 @@ def test_studio_demo_evidence_loads_compare_ready_pair():
     assert response["jetson_evidence_track"]["runtime_result_source"] == (
         "examples/studio_demo/tensorrt_jetson_25w_result.json"
     )
+    assert response["jetson_power_mode_summary"]["baseline_power_mode"] == "25W"
+    assert response["jetson_power_mode_summary"]["candidate_power_mode"] == "15W"
+    assert response["jetson_power_mode_summary"]["metrics"]["mean_ms"]["delta_pct"] == 7.278719
+    assert response["jetson_power_mode_summary"]["metrics"]["fps_value"]["delta_pct"] == -6.784866
+    assert response["jetson_power_mode_summary"]["deployment_signal"]["decision"] == "review_note"
     assert response["compare"]["status"] == "ok"
     assert response["compare"]["judgement"]["overall"] == "tradeoff_faster"
     assert response["guard_analysis"]["guard_verdict"] == "review_required"
@@ -430,6 +436,7 @@ def test_studio_demo_evidence_is_listed_and_selectable_as_job():
     assert detail["result"]["runtime_result"]["backend_key"] == "tensorrt__jetson"
     assert detail["result"]["runtime_result"]["run_config"]["power_mode"] == "25W"
     assert detail["result"]["jetson_evidence_track"]["power_mode"] == "25W"
+    assert detail["result"]["jetson_power_mode_summary"]["candidate_power_mode"] == "15W"
     assert detail["result"]["guard_analysis"]["guard_verdict"] == "review_required"
     assert detail["result"]["guard_demo_cases"]["case_count"] == 4
     assert detail["result"]["comparison"]["base"]["backend_key"] == "onnxruntime__cpu"