feat: add Jetson 25W Studio evidence fixture

examples/studio_demo/tensorrt_jetson_25w_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": 10.066401,
+  "p50_ms": 9.908564,
+  "p95_ms": 15.476641,
+  "p99_ms": 15.548438,
+  "fps_value": 99.340373,
+  "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": "25W",
+    "jetson_clocks": "unknown",
+    "tegrastats_log_path": "results/jetson_evidence/tegrastats_yolov8n_trt_fp16_25w_20260504T170039Z.log",
+    "manifest_path": "/home/risenano01/InferEdgeForge/builds/yolov8n__jetson__tensorrt__jetson_fp16/metadata.json",
+    "manifest_applied": true
+  },
+  "latency_ms": {
+    "mean": 10.066401,
+    "min": 7.241229,
+    "max": 15.548438,
+    "std": 2.279389,
+    "p50": 9.908564,
+    "p90": 12.284969,
+    "p95": 15.476641,
+    "p99": 15.548438
+  },
+  "fps": 99.340373,
+  "benchmark": {
+    "success": true,
+    "status": "success",
+    "message": "benchmark completed"
+  },
+  "timestamp": "2026-05-04T17:00:41Z",
+  "system": {
+    "os": "linux",
+    "compiler": "GCC",
+    "cpp_standard": "17",
+    "jetson": {
+      "power_mode": "25W",
+      "jetson_clocks": "unknown",
+      "tegrastats_log_path": "results/jetson_evidence/tegrastats_yolov8n_trt_fp16_25w_20260504T170039Z.log"
+    }
+  },
+  "jetson_evidence": {
+    "power_mode": "25W",
+    "jetson_clocks": "unknown",
+    "tegrastats_log_path": "results/jetson_evidence/tegrastats_yolov8n_trt_fp16_25w_20260504T170039Z.log",
+    "tegrastats_summary": {
+      "status": "parsed",
+      "sample_count": 3,
+      "ram_used_mb_avg": 947.666667,
+      "ram_used_mb_max": 1072.0,
+      "ram_total_mb": 7620.0,
+      "max_temp_c": 40.656,
+      "max_temp_name": "gpu",
+      "vdd_in_mw_avg": 4863.0,
+      "vdd_in_mw_max": 5827.0
+    }
+  },
+  "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": "25W",
+    "jetson_clocks": "unknown",
+    "tegrastats_log_path": "results/jetson_evidence/tegrastats_yolov8n_trt_fp16_25w_20260504T170039Z.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"
+  }
+}

inferedgelab/studio/routes.py

@@ -25,7 +25,7 @@
 VALIDATION_PROBLEM_DIR = Path(__file__).resolve().parents[2] / "examples" / "validation_demo" / "problem_cases"
 DEMO_EVIDENCE_FILES = (
     "onnxruntime_cpu_result.json",
-    "tensorrt_jetson_result.json",
+    "tensorrt_jetson_25w_result.json",
 )
 DEMO_EVALUATION_REPORT = "yolov8_coco_subset_evaluation.json"
 DEMO_PROBLEM_REPORTS = (
@@ -174,6 +174,7 @@ def studio_demo_evidence(request: Request) -> dict[str, Any]:
     evaluation_report = _load_demo_evaluation_report()
     problem_cases = _load_demo_problem_cases()
     guard_demo_cases = _load_aiguard_portfolio_cases()
+    jetson_evidence_track = _build_jetson_evidence_track(results)
     imported_results = _get_imported_results(request)
     imported_results.extend(results)
     guard_analysis = _build_demo_guard_analysis(results, evaluation_report)
@@ -183,7 +184,14 @@ def studio_demo_evidence(request: Request) -> dict[str, Any]:
         results[1],
         guard_analysis=guard_analysis,
     )
-    demo_job = _build_demo_job(results, compare, evaluation_report, problem_cases, guard_demo_cases)
+    demo_job = _build_demo_job(
+        results,
+        compare,
+        evaluation_report,
+        problem_cases,
+        guard_demo_cases,
+        jetson_evidence_track,
+    )
     _get_demo_jobs(request)[DEMO_JOB_ID] = demo_job
     return {
         "status": "loaded",
@@ -197,6 +205,7 @@ def studio_demo_evidence(request: Request) -> dict[str, Any]:
         "evaluation_report": evaluation_report,
         "problem_cases": problem_cases,
         "guard_demo_cases": guard_demo_cases,
+        "jetson_evidence_track": jetson_evidence_track,
         "guard_analysis": guard_analysis,
         "deployment_decision": compare["deployment_decision"],
     }
@@ -455,6 +464,7 @@ def _build_demo_job(
     evaluation_report: dict[str, Any],
     problem_cases: list[dict[str, Any]],
     guard_demo_cases: dict[str, Any],
+    jetson_evidence_track: dict[str, Any],
 ) -> dict[str, Any]:
     now = _utc_now_iso()
     runtime_result = results[-1] if results else {}
@@ -477,6 +487,7 @@ def _build_demo_job(
             "evaluation_report": evaluation_report,
             "problem_cases": problem_cases,
             "guard_demo_cases": guard_demo_cases,
+            "jetson_evidence_track": jetson_evidence_track,
             "summary": compare["judgement"]["summary"],
         },
         "error": None,
@@ -488,6 +499,51 @@ def _build_demo_job(
     }
 
 
+def _build_jetson_evidence_track(results: list[dict[str, Any]]) -> dict[str, Any]:
+    candidate = next(
+        (
+            result
+            for result in reversed(results)
+            if str(result.get("backend_key") or "").startswith("tensorrt__")
+            and str(result.get("device_name") or _display_value(result.get("device"))).lower() == "jetson"
+        ),
+        {},
+    )
+    jetson_evidence = candidate.get("jetson_evidence") if isinstance(candidate, dict) else {}
+    if not isinstance(jetson_evidence, dict):
+        jetson_evidence = {}
+    run_config = candidate.get("run_config") if isinstance(candidate.get("run_config"), dict) else {}
+    tegrastats_summary = jetson_evidence.get("tegrastats_summary")
+    if not isinstance(tegrastats_summary, dict):
+        tegrastats_summary = {}
+
+    return {
+        "track": "jetson_runtime_evidence",
+        "scope": "Jetson Orin Nano TensorRT FP16 25W Runtime smoke",
+        "runtime_result_source": candidate.get("_source_path") or "examples/studio_demo/tensorrt_jetson_25w_result.json",
+        "backend_key": candidate.get("backend_key"),
+        "compare_key": candidate.get("compare_key"),
+        "precision": candidate.get("precision"),
+        "power_mode": jetson_evidence.get("power_mode") or run_config.get("power_mode"),
+        "jetson_clocks": jetson_evidence.get("jetson_clocks") or run_config.get("jetson_clocks"),
+        "mean_ms": candidate.get("mean_ms"),
+        "p50_ms": candidate.get("p50_ms") or (candidate.get("latency_ms") or {}).get("p50"),
+        "p95_ms": candidate.get("p95_ms") or (candidate.get("latency_ms") or {}).get("p95"),
+        "p99_ms": candidate.get("p99_ms"),
+        "fps_value": candidate.get("fps_value") or candidate.get("fps"),
+        "tegrastats_status": tegrastats_summary.get("status"),
+        "tegrastats_samples": tegrastats_summary.get("sample_count"),
+        "max_temp_c": tegrastats_summary.get("max_temp_c"),
+        "max_temp_name": tegrastats_summary.get("max_temp_name"),
+        "vdd_in_mw_avg": tegrastats_summary.get("vdd_in_mw_avg"),
+        "vdd_in_mw_max": tegrastats_summary.get("vdd_in_mw_max"),
+        "note": (
+            "This is empirical Jetson runtime evidence for the Local Studio demo, "
+            "not a production inference server or cloud benchmark track."
+        ),
+    }
+
+
 def _build_demo_guard_analysis(
     results: list[dict[str, Any]],
     evaluation_report: dict[str, Any],

inferedgelab/studio/static/app.js

@@ -32,6 +32,7 @@ let demoEvaluationReport = null;
 let demoProblemCases = [];
 let activeGuardAnalysis = null;
 let guardDemoCases = null;
+let demoJetsonEvidence = null;
 const importedResultsByJobId = {};
 
 function createElement(tagName, className, textContent) {
@@ -375,6 +376,7 @@ async function loadDemoEvidence() {
     demoEvaluationReport = payload.evaluation_report || null;
     demoProblemCases = Array.isArray(payload.problem_cases) ? payload.problem_cases : [];
     guardDemoCases = payload.guard_demo_cases || null;
+    demoJetsonEvidence = payload.jetson_evidence_track || null;
     compareData = payload.compare || null;
     updateGuardEvidence(payload.guard_analysis || payload.compare?.guard_analysis || null);
     selectedJobId = payload.job_id || payload.job?.job_id || selectedJobId;
@@ -501,6 +503,15 @@ function renderDemoEvaluation(report) {
     evidenceItem("contract", contract.status || "-"),
     evidenceItem("report", report.source || "-"),
   );
+
+  if (demoJetsonEvidence) {
+    target.append(
+      evidenceItem("jetson_power", demoJetsonEvidence.power_mode || "-"),
+      evidenceItem("jetson_p95", demoJetsonEvidence.p95_ms === undefined ? "-" : `${formatNumber(demoJetsonEvidence.p95_ms)} ms`),
+      evidenceItem("jetson_temp", demoJetsonEvidence.max_temp_c === undefined ? "-" : `${formatNumber(demoJetsonEvidence.max_temp_c)} C`),
+      evidenceItem("tegrastats", demoJetsonEvidence.tegrastats_status || "-"),
+    );
+  }
 }
 
 function renderPipeline() {
@@ -1144,7 +1155,22 @@ function findResultByBackend(results, keyword) {
 }
 
 function runtimeModelName(result = {}) {
-  return firstDisplayValue(result.model_name, result.model?.name, result.model, result.model_path);
+  return firstDisplayValue(
+    result.extra?.compare_model_name,
+    pathBasename(result.extra?.source_model_path),
+    result.model_name,
+    result.model?.name,
+    result.model,
+    result.model_path,
+  );
+}
+
+function pathBasename(path) {
+  if (!path || typeof path !== "string") {
+    return "";
+  }
+  const parts = path.split(/[\\/]/).filter(Boolean);
+  return parts[parts.length - 1] || path;
 }
 
 function runtimeBackendName(result = {}) {

tests/test_studio_routes.py

@@ -132,6 +132,7 @@ def test_studio_static_assets_include_redesigned_ui_contracts():
     assert "request record only" in app_text
     assert "loadDemoEvidence" in app_text
     assert "renderDemoEvaluation" in app_text
+    assert "demoJetsonEvidence" in app_text
     assert "renderDemoProblemCases" in app_text
     assert "renderGuardEvidence" in app_text
     assert "renderGuardDemoCases" in app_text
@@ -361,9 +362,19 @@ def test_studio_demo_evidence_loads_compare_ready_pair():
     assert response["results"][0]["backend_key"] == "onnxruntime__cpu"
     assert response["results"][1]["backend_key"] == "tensorrt__jetson"
     assert response["results"][0]["mean_ms"] == 45.4299
-    assert response["results"][1]["mean_ms"] == 9.9375
+    assert response["results"][1]["mean_ms"] == 10.066401
+    assert response["results"][1]["precision"] == "fp16"
+    assert response["results"][1]["run_config"]["power_mode"] == "25W"
+    assert response["results"][1]["jetson_evidence"]["tegrastats_summary"]["status"] == "parsed"
+    assert response["jetson_evidence_track"]["power_mode"] == "25W"
+    assert response["jetson_evidence_track"]["mean_ms"] == 10.066401
+    assert response["jetson_evidence_track"]["p95_ms"] == 15.476641
+    assert response["jetson_evidence_track"]["tegrastats_status"] == "parsed"
+    assert response["jetson_evidence_track"]["runtime_result_source"] == (
+        "examples/studio_demo/tensorrt_jetson_25w_result.json"
+    )
     assert response["compare"]["status"] == "ok"
-    assert response["compare"]["judgement"]["overall"] == "improvement"
+    assert response["compare"]["judgement"]["overall"] == "tradeoff_faster"
     assert response["guard_analysis"]["guard_verdict"] == "review_required"
     assert response["guard_analysis"]["evidence"][0]["metric_name"] == "map50"
     assert response["guard_demo_cases"]["schema_version"] == "inferedge-aiguard-portfolio-demo-v1"
@@ -417,6 +428,8 @@ def test_studio_demo_evidence_is_listed_and_selectable_as_job():
     assert detail["job_id"] == "demo_yolov8n_trt_vs_onnx"
     assert detail["status"] == "completed"
     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"]["guard_analysis"]["guard_verdict"] == "review_required"
     assert detail["result"]["guard_demo_cases"]["case_count"] == 4
     assert detail["result"]["comparison"]["base"]["backend_key"] == "onnxruntime__cpu"