feat: implement Phase 1-4 performance visualization and device management

Phase 1 — Performance Benchmarking:
- PerformanceBenchmarker: sequential vs parallel benchmark with injectable runner
- PerformanceHistory: JSON-backed benchmark history with regression support
- PerformanceDashboard: real-time FPS/latency display widget
- BenchmarkDialog: one-click benchmark with 3-phase progress bar

Phase 2 — Device Management:
- DeviceManager: NPU dongle scan, assign/unassign, load balance recommendation
- DeviceManagementPanel: live device status cards with auto-refresh
- BottleneckAlert: dataclass for pipeline bottleneck detection

Phase 3 — Advanced Features:
- OptimizationEngine: 3 optimization rules (rebalance/adjust_queue/add_devices)
- TemplateManager: 3 built-in pipeline templates (YOLOv5, fire detection, dual-model)

Phase 4 — Report Export:
- ReportExporter: PDF (reportlab, optional) and CSV export
- ExportReportDialog: format selection + path picker UI

192 unit tests, all passing.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

core/device/__init__.py

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+"""core.device — device management subpackage."""

core/device/bottleneck.py

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+"""
+core/device/bottleneck.py
+
+BottleneckAlert dataclass — describes a detected pipeline bottleneck.
+
+Integration with InferencePipeline is deferred to a later phase.
+This module only defines the data structure.
+"""
+from dataclasses import dataclass
+
+
+@dataclass
+class BottleneckAlert:
+    """Describes a detected pipeline bottleneck in a single Stage.
+
+    Attributes
+    ----------
+    stage_id:
+        The pipeline Stage that is experiencing the bottleneck.
+    queue_fill_rate:
+        Input queue utilisation as a fraction in [0.0, 1.0].
+    suggested_action:
+        Human-readable suggestion (e.g. "Add more Dongles to this stage").
+    severity:
+        Either ``"warning"`` (fill_rate > 0.8) or ``"critical"``
+        (fill_rate > 0.95).
+    """
+
+    stage_id: str
+    queue_fill_rate: float
+    suggested_action: str
+    severity: str  # "warning" | "critical"

core/device/device_manager.py

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+"""
+core/device/device_manager.py
+
+DeviceManager — manages NPU Dongle discovery, health, and assignment.
+
+Design:
+- scan_devices() calls the Kneron KP SDK but accepts an injectable kp_api
+  parameter so tests can supply a Mock without real hardware.
+- DongleSeriesSpec constants are inlined here to avoid a circular import
+  from core.functions.Multidongle.
+"""
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from typing import Dict, List, Optional
+
+# ---------------------------------------------------------------------------
+# GOPS table (mirrors DongleSeriesSpec in Multidongle.py)
+# ---------------------------------------------------------------------------
+
+_PRODUCT_ID_TO_SERIES: Dict[int, str] = {
+    0x100: "KL520",
+    0x720: "KL720",
+    0x630: "KL630",
+    0x730: "KL730",
+}
+
+_SERIES_GOPS: Dict[str, int] = {
+    "KL520": 2,
+    "KL720": 28,
+    "KL630": 400,
+    "KL730": 1600,
+}
+
+
+# ---------------------------------------------------------------------------
+# Data classes
+# ---------------------------------------------------------------------------
+
+@dataclass
+class DeviceInfo:
+    """Snapshot of a single NPU Dongle's state."""
+
+    device_id: str                   # unique id, e.g. "usb-<port_id>"
+    series: str                      # "KL520" | "KL720" | ...
+    product_id: int                  # raw USB product ID
+    status: str                      # "online" | "offline" | "busy"
+    gops: int                        # compute capacity
+    assigned_stage: Optional[str]    # currently assigned stage ID, or None
+    current_fps: float               # live inference throughput
+    utilization_pct: float           # 0.0 – 100.0
+
+
+@dataclass
+class DeviceHealth:
+    """Health snapshot of a single NPU Dongle."""
+
+    device_id: str
+    temperature_celsius: Optional[float]  # None if SDK does not support it
+    error_count: int
+    last_error: Optional[str]
+    uptime_seconds: float
+
+
+# ---------------------------------------------------------------------------
+# DeviceManager
+# ---------------------------------------------------------------------------
+
+class DeviceManager:
+    """Manages NPU Dongle discovery, health queries, and stage assignment.
+
+    Parameters
+    ----------
+    kp_api:
+        Kneron KP SDK module reference.  Pass ``None`` to import the real
+        ``kp`` module at runtime, or inject a Mock in tests.
+    """
+
+    def __init__(self, kp_api=None) -> None:
+        if kp_api is None:
+            import kp as _kp  # real SDK (requires hardware)
+            self._kp = _kp
+        else:
+            self._kp = kp_api
+
+        # Known devices, populated by scan_devices()
+        self._devices: Dict[str, DeviceInfo] = {}
+        # stage assignments: {device_id: stage_id}
+        self._assignments: Dict[str, str] = {}
+
+    # ------------------------------------------------------------------
+    # Public API
+    # ------------------------------------------------------------------
+
+    def scan_devices(self) -> List[DeviceInfo]:
+        """Scan for connected Kneron Dongles and update internal state.
+
+        Returns
+        -------
+        List[DeviceInfo]
+            All currently connected devices, each with status "online".
+        """
+        try:
+            descriptors = self._kp.core.scan_devices()
+        except Exception:
+            return []
+
+        if not descriptors or descriptors.device_descriptor_number == 0:
+            return []
+
+        found: Dict[str, DeviceInfo] = {}
+        for desc in descriptors.device_descriptor_list:
+            try:
+                port_id = desc.usb_port_id
+                product_id = desc.product_id
+                device_id = f"usb-{port_id}"
+                series = _PRODUCT_ID_TO_SERIES.get(product_id, "Unknown")
+                gops = _SERIES_GOPS.get(series, 0)
+                assigned = self._assignments.get(device_id)
+                info = DeviceInfo(
+                    device_id=device_id,
+                    series=series,
+                    product_id=product_id,
+                    status="online",
+                    gops=gops,
+                    assigned_stage=assigned,
+                    current_fps=0.0,
+                    utilization_pct=0.0,
+                )
+                found[device_id] = info
+            except Exception:
+                continue
+
+        self._devices = found
+        return list(self._devices.values())
+
+    def get_device_health(self, device_id: str) -> DeviceHealth:
+        """Return a health snapshot for the given device.
+
+        Temperature is returned as ``None`` because the current KP SDK
+        version does not expose thermal sensors.
+        """
+        return DeviceHealth(
+            device_id=device_id,
+            temperature_celsius=None,
+            error_count=0,
+            last_error=None,
+            uptime_seconds=0.0,
+        )
+
+    def assign_device(self, device_id: str, stage_id: str) -> bool:
+        """Assign *device_id* to *stage_id*.
+
+        Returns
+        -------
+        bool
+            ``False`` if the device is unknown or already assigned to a
+            different stage; ``True`` on success.
+        """
+        device = self._devices.get(device_id)
+        if device is None or device.status == "offline":
+            return False
+        existing_stage = self._assignments.get(device_id)
+        if existing_stage is not None and existing_stage != stage_id:
+            return False  # already assigned to a different stage
+        self._assignments[device_id] = stage_id
+        self._devices[device_id].assigned_stage = stage_id
+        return True
+
+    def unassign_device(self, device_id: str) -> bool:
+        """Release *device_id* from its current stage assignment.
+
+        Returns
+        -------
+        bool
+            ``False`` if the device is unknown; ``True`` on success.
+        """
+        if device_id not in self._devices:
+            return False
+        self._assignments.pop(device_id, None)
+        self._devices[device_id].assigned_stage = None
+        return True
+
+    def get_load_balance_recommendation(
+        self, stages: List[str]
+    ) -> Dict[str, str]:
+        """Recommend device-to-stage assignment by GOPS (descending).
+
+        Higher-GOPS devices are assigned to earlier stages.  Stages with
+        no available device are mapped to an empty string.
+
+        Parameters
+        ----------
+        stages:
+            Ordered list of stage IDs (first stage has highest priority).
+
+        Returns
+        -------
+        Dict[str, str]
+            ``{stage_id: device_id}``; device_id is "" if unavailable.
+        """
+        available = sorted(
+            self._devices.values(),
+            key=lambda d: d.gops,
+            reverse=True,
+        )
+        recommendation: Dict[str, str] = {}
+        for i, stage_id in enumerate(stages):
+            if i < len(available):
+                recommendation[stage_id] = available[i].device_id
+            else:
+                recommendation[stage_id] = ""
+        return recommendation
+
+    def get_device_statistics(self) -> Dict[str, DeviceInfo]:
+        """Return a snapshot of all known devices keyed by device_id."""
+        return dict(self._devices)

core/optimization/__init__.py

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+"""core/optimization — Pipeline 優化建議模組。"""

core/optimization/engine.py

@@ -0,0 +1,248 @@
+"""
+core/optimization/engine.py
+
+OptimizationEngine — 分析 Pipeline 執行統計，產生可執行的優化建議。
+
+設計重點：
+- analyze_pipeline 接受來自 InferencePipeline.get_pipeline_statistics() 的 stats 字典。
+- 三條優化規則（rebalance_devices、adjust_queue、add_devices）各自獨立，
+  可個別觸發，不互斥。
+- apply_suggestion 對 rebalance_devices 呼叫 device_manager.assign_device；
+  其他類型（add_devices、adjust_queue）需要人工操作，僅記錄 log 後回傳 True。
+- predict_performance 使用保守係數 0.6 的啟發式估算。
+"""
+from __future__ import annotations
+
+import logging
+import uuid
+from dataclasses import dataclass, field
+from typing import Any, Dict, List, Tuple
+
+logger = logging.getLogger(__name__)
+
+# 優化規則閾值
+_QUEUE_FILL_THRESHOLD = 0.70        # queue_fill_rate > 此值觸發 rebalance_devices
+_TIME_RATIO_THRESHOLD = 2.0         # max/min avg_processing_time > 此值觸發 adjust_queue
+_UTILIZATION_THRESHOLD = 85.0       # 所有裝置 utilization_pct > 此值觸發 add_devices
+_CONSERVATIVE_FACTOR = 0.6          # predict_performance 的保守係數
+
+
+@dataclass
+class OptimizationSuggestion:
+    """單一優化建議。
+
+    屬性：
+        suggestion_id: 唯一識別碼（UUID 字串）。
+        type: 建議類型，如 "rebalance_devices" | "adjust_queue" | "add_devices"。
+        description: 使用者可讀的說明（避免技術術語）。
+        estimated_improvement_pct: 預估改善百分比（0.0–100.0）。
+        confidence: 信心程度，"high" | "medium" | "low"。
+        action_params: 執行建議所需的參數字典。
+    """
+    suggestion_id: str
+    type: str
+    description: str
+    estimated_improvement_pct: float
+    confidence: str
+    action_params: Dict[str, Any]
+
+
+class OptimizationEngine:
+    """分析 Pipeline 執行統計並產生優化建議。"""
+
+    # ------------------------------------------------------------------
+    # 公開介面
+    # ------------------------------------------------------------------
+
+    def analyze_pipeline(
+        self,
+        stats: Dict[str, Any],
+    ) -> List[OptimizationSuggestion]:
+        """分析 Pipeline 執行統計，產生優化建議清單。
+
+        參數：
+            stats: 來自 InferencePipeline.get_pipeline_statistics() 的字典，
+                   格式詳見模組文件。
+
+        回傳：
+            可能為空的 OptimizationSuggestion 清單。
+        """
+        stages: Dict[str, Any] = stats.get("stages", {})
+        devices: Dict[str, Any] = stats.get("devices", {})
+
+        suggestions: List[OptimizationSuggestion] = []
+
+        suggestions.extend(self._check_rebalance_devices(stages))
+        suggestions.extend(self._check_adjust_queue(stages))
+        suggestions.extend(self._check_add_devices(devices))
+
+        return suggestions
+
+    def predict_performance(
+        self,
+        config: List[Any],
+        available_devices: List[Any],
+    ) -> Dict[str, float]:
+        """以啟發式方法估算 Pipeline 效能。
+
+        公式：
+            estimated_fps = sum(device.gops for d in available_devices) / num_stages * 0.6
+            estimated_latency_ms = 1000 / estimated_fps
+            confidence_range = (estimated_fps * 0.8, estimated_fps * 1.2)
+
+        參數：
+            config: Stage 設定列表（每個元素代表一個 Stage）。
+            available_devices: DeviceInfo 物件列表（具備 gops 屬性）。
+
+        回傳：
+            包含 estimated_fps、estimated_latency_ms、confidence_range 的字典。
+        """
+        num_stages = len(config)
+        total_gops = sum(getattr(d, "gops", 0) for d in available_devices)
+
+        if num_stages == 0 or total_gops == 0:
+            return {
+                "estimated_fps": 0.0,
+                "estimated_latency_ms": 0.0,
+                "confidence_range": (0.0, 0.0),
+            }
+
+        estimated_fps = total_gops / num_stages * _CONSERVATIVE_FACTOR
+        estimated_latency_ms = 1000.0 / estimated_fps
+        confidence_range = (estimated_fps * 0.8, estimated_fps * 1.2)
+
+        return {
+            "estimated_fps": estimated_fps,
+            "estimated_latency_ms": estimated_latency_ms,
+            "confidence_range": confidence_range,
+        }
+
+    def apply_suggestion(
+        self,
+        suggestion: OptimizationSuggestion,
+        device_manager: Any,
+    ) -> bool:
+        """執行優化建議。
+
+        - rebalance_devices：呼叫 device_manager.assign_device 並回傳其結果。
+        - add_devices / adjust_queue：記錄 log（需人工操作），回傳 True。
+
+        參數：
+            suggestion: 要執行的優化建議。
+            device_manager: DeviceManager 實例。
+
+        回傳：
+            執行是否成功。
+        """
+        if suggestion.type == "rebalance_devices":
+            device_id = suggestion.action_params.get("device_id", "")
+            stage_id = suggestion.action_params.get("stage_id", "")
+            success = device_manager.assign_device(device_id, stage_id)
+            if success:
+                logger.info(
+                    "已將裝置 %s 重新分配至 Stage %s", device_id, stage_id
+                )
+            else:
+                logger.warning(
+                    "無法將裝置 %s 分配至 Stage %s", device_id, stage_id
+                )
+            return success
+
+        if suggestion.type in ("add_devices", "adjust_queue"):
+            logger.info(
+                "優化建議 [%s]：%s（需要人工操作）",
+                suggestion.type,
+                suggestion.description,
+            )
+            return True
+
+        logger.warning("未知的建議類型：%s", suggestion.type)
+        return False
+
+    # ------------------------------------------------------------------
+    # 內部規則實作
+    # ------------------------------------------------------------------
+
+    def _check_rebalance_devices(
+        self, stages: Dict[str, Any]
+    ) -> List[OptimizationSuggestion]:
+        """規則 1：queue_fill_rate > 0.70 → 建議重新分配裝置。"""
+        suggestions = []
+        for stage_id, stage_data in stages.items():
+            fill_rate: float = stage_data.get("queue_fill_rate", 0.0)
+            if fill_rate > _QUEUE_FILL_THRESHOLD:
+                pct = round((fill_rate - _QUEUE_FILL_THRESHOLD) / _QUEUE_FILL_THRESHOLD * 100, 1)
+                suggestions.append(
+                    OptimizationSuggestion(
+                        suggestion_id=str(uuid.uuid4()),
+                        type="rebalance_devices",
+                        description=(
+                            f"{stage_id} 的佇列使用率偏高（{fill_rate:.0%}），"
+                            "建議將算力較高的裝置分配給此階段以降低積壓。"
+                        ),
+                        estimated_improvement_pct=min(pct, 40.0),
+                        confidence="medium",
+                        action_params={"stage_id": stage_id, "device_id": ""},
+                    )
+                )
+        return suggestions
+
+    def _check_adjust_queue(
+        self, stages: Dict[str, Any]
+    ) -> List[OptimizationSuggestion]:
+        """規則 2：avg_processing_time 最大/最小比值 > 2.0 → 建議調整佇列大小。"""
+        if len(stages) < 2:
+            return []
+
+        times = {
+            sid: data.get("avg_processing_time", 0.0)
+            for sid, data in stages.items()
+        }
+        max_time = max(times.values())
+        min_time = min(times.values())
+
+        if min_time <= 0 or max_time / min_time <= _TIME_RATIO_THRESHOLD:
+            return []
+
+        ratio = max_time / min_time
+        return [
+            OptimizationSuggestion(
+                suggestion_id=str(uuid.uuid4()),
+                type="adjust_queue",
+                description=(
+                    f"各 Stage 的處理時間差異達 {ratio:.1f} 倍，"
+                    "建議調整佇列大小以平衡各階段的吞吐量。"
+                ),
+                estimated_improvement_pct=min((ratio - 2.0) * 10.0, 30.0),
+                confidence="low",
+                action_params={"max_stage": max(times, key=times.get), "ratio": ratio},
+            )
+        ]
+
+    def _check_add_devices(
+        self, devices: Dict[str, Any]
+    ) -> List[OptimizationSuggestion]:
+        """規則 3：所有 Dongle 使用率 > 85% → 建議增加更多 Dongle。"""
+        if not devices:
+            return []
+
+        utilizations = [
+            data.get("utilization_pct", 0.0) for data in devices.values()
+        ]
+        if not all(u > _UTILIZATION_THRESHOLD for u in utilizations):
+            return []
+
+        avg_util = sum(utilizations) / len(utilizations)
+        return [
+            OptimizationSuggestion(
+                suggestion_id=str(uuid.uuid4()),
+                type="add_devices",
+                description=(
+                    f"所有裝置的平均使用率已達 {avg_util:.1f}%，"
+                    "系統已接近飽和，建議增加更多 NPU 裝置。"
+                ),
+                estimated_improvement_pct=min((avg_util - 85.0) * 2.0, 50.0),
+                confidence="high",
+                action_params={"current_avg_utilization": avg_util},
+            )
+        ]

core/performance/__init__.py

@@ -0,0 +1,23 @@
+"""
+core/performance — 效能測試與歷史記錄模組。
+
+提供 Benchmark 執行、結果儲存與回歸分析功能。
+
+使用範例：
+    from core.performance import (
+        PerformanceBenchmarker,
+        BenchmarkConfig,
+        BenchmarkResult,
+        PerformanceHistory,
+    )
+"""
+
+from .benchmarker import BenchmarkConfig, BenchmarkResult, PerformanceBenchmarker
+from .history import PerformanceHistory
+
+__all__ = [
+    "BenchmarkConfig",
+    "BenchmarkResult",
+    "PerformanceBenchmarker",
+    "PerformanceHistory",
+]

core/performance/benchmarker.py

@@ -0,0 +1,247 @@
+"""
+core/performance/benchmarker.py — 效能基準測試模組。
+
+提供 BenchmarkConfig、BenchmarkResult 資料結構，
+以及 PerformanceBenchmarker 執行單/多裝置效能測試並計算加速倍數。
+
+設計重點：
+- 實際推論呼叫透過 inference_runner callable 注入，
+  方便在沒有硬體的環境下進行單元測試（注入 Mock）。
+- 純計算邏輯（calculate_speedup 等）可直接測試，無需 Mock。
+
+使用範例（測試環境）：
+    config = BenchmarkConfig(pipeline_config=[], test_input_source="test.mp4")
+    benchmarker = PerformanceBenchmarker()
+
+    def mock_runner(frame_data):
+        return {"result": "ok"}
+
+    seq = benchmarker.run_sequential_benchmark(config, inference_runner=mock_runner)
+    par = benchmarker.run_parallel_benchmark(config, inference_runner=mock_runner)
+    speedup = benchmarker.calculate_speedup(seq, par)
+"""
+
+import time
+import statistics
+from dataclasses import dataclass, field
+from typing import Any, Callable, Dict, List, Optional, Tuple
+
+
+@dataclass
+class BenchmarkConfig:
+    """Benchmark 測試設定。
+
+    屬性：
+        pipeline_config: Pipeline 各 Stage 的設定列表（來自 UI）。
+        test_input_source: 測試輸入來源（影片檔路徑或相機索引）。
+        test_duration_seconds: 測試持續時間（秒），不含暖機階段。
+        warmup_frames: 暖機幀數，不計入統計。
+    """
+    pipeline_config: List[Any]
+    test_input_source: str
+    test_duration_seconds: float = 30.0
+    warmup_frames: int = 50
+
+
+@dataclass
+class BenchmarkResult:
+    """單次 Benchmark 的測試結果。
+
+    屬性：
+        mode: 測試模式，'sequential'（單裝置）或 'parallel'（多裝置）。
+        fps: 每秒幀數。
+        avg_latency_ms: 平均推論延遲（毫秒）。
+        p95_latency_ms: 95th percentile 延遲（毫秒）。
+        total_frames: 測試期間處理的總幀數（不含暖機）。
+        timestamp: 測試開始的 Unix timestamp。
+        device_config: 裝置分配設定，例如 {"KL520": 1}。
+        id: 唯一識別碼（由 PerformanceHistory.record() 填入）。
+    """
+    mode: str
+    fps: float
+    avg_latency_ms: float
+    p95_latency_ms: float
+    total_frames: int
+    timestamp: float
+    device_config: Dict[str, Any]
+    id: Optional[str] = field(default=None)
+
+
+class PerformanceBenchmarker:
+    """執行單裝置 vs 多裝置效能測試，計算加速倍數。
+
+    設計為可測試性（Testability-First）：
+    - run_sequential_benchmark / run_parallel_benchmark 接受 inference_runner 參數，
+      讓測試時可注入 Mock 而不需要真實硬體。
+    - calculate_speedup 為純函式，直接接受 BenchmarkResult 計算。
+
+    屬性：
+        device_config: 裝置設定資訊，會填入 BenchmarkResult.device_config。
+    """
+
+    def __init__(self, device_config: Optional[Dict[str, Any]] = None):
+        """初始化 PerformanceBenchmarker。
+
+        參數：
+            device_config: 裝置設定，例如 {"KL520": 1}。未指定時使用空字典。
+        """
+        self.device_config: Dict[str, Any] = device_config or {}
+
+    # ------------------------------------------------------------------
+    # 公開介面
+    # ------------------------------------------------------------------
+
+    def run_sequential_benchmark(
+        self,
+        config: BenchmarkConfig,
+        inference_runner: Optional[Callable[[Any], Any]] = None,
+    ) -> BenchmarkResult:
+        """以單裝置（循序）模式執行 Benchmark。
+
+        參數：
+            config: 測試設定。
+            inference_runner: 推論執行函式，簽名為 ``(frame_data: Any) -> Any``。
+                              若為 None，使用 no-op 函式（僅供架構驗證）。
+
+        回傳：
+            mode='sequential' 的 BenchmarkResult。
+        """
+        runner = inference_runner or self._default_runner
+        return self._run_benchmark(config, runner, mode="sequential")
+
+    def run_parallel_benchmark(
+        self,
+        config: BenchmarkConfig,
+        inference_runner: Optional[Callable[[Any], Any]] = None,
+    ) -> BenchmarkResult:
+        """以多裝置（平行）模式執行 Benchmark。
+
+        參數：
+            config: 測試設定。
+            inference_runner: 推論執行函式，簽名為 ``(frame_data: Any) -> Any``。
+                              若為 None，使用 no-op 函式（僅供架構驗證）。
+
+        回傳：
+            mode='parallel' 的 BenchmarkResult。
+        """
+        runner = inference_runner or self._default_runner
+        return self._run_benchmark(config, runner, mode="parallel")
+
+    def calculate_speedup(
+        self,
+        seq: BenchmarkResult,
+        par: BenchmarkResult,
+    ) -> float:
+        """計算平行相對於循序的加速倍數。
+
+        計算公式：par.fps / seq.fps
+
+        參數：
+            seq: 循序模式的 BenchmarkResult。
+            par: 平行模式的 BenchmarkResult。
+
+        回傳：
+            加速倍數（float）。
+
+        引發：
+            ValueError: 當 seq.fps <= 0 時（避免除以零）。
+        """
+        if seq.fps <= 0:
+            raise ValueError(
+                f"循序模式的 FPS 必須大於 0，收到：{seq.fps}"
+            )
+        return par.fps / seq.fps
+
+    def run_full_benchmark(
+        self,
+        config: BenchmarkConfig,
+        inference_runner: Optional[Callable[[Any], Any]] = None,
+    ) -> Tuple[BenchmarkResult, BenchmarkResult, float]:
+        """執行完整 Benchmark：循序 → 平行 → 計算加速倍數。
+
+        執行序列：
+        1. 執行循序 Benchmark
+        2. 執行平行 Benchmark
+        3. 計算加速倍數
+
+        參數：
+            config: 測試設定。
+            inference_runner: 推論執行函式（可注入 Mock）。
+
+        回傳：
+            Tuple[BenchmarkResult, BenchmarkResult, float]
+            即 (sequential_result, parallel_result, speedup)。
+        """
+        seq_result = self.run_sequential_benchmark(config, inference_runner)
+        par_result = self.run_parallel_benchmark(config, inference_runner)
+        speedup = self.calculate_speedup(seq_result, par_result)
+        return seq_result, par_result, speedup
+
+    # ------------------------------------------------------------------
+    # 內部實作
+    # ------------------------------------------------------------------
+
+    def _run_benchmark(
+        self,
+        config: BenchmarkConfig,
+        runner: Callable[[Any], Any],
+        mode: str,
+    ) -> BenchmarkResult:
+        """執行 Benchmark 的共用邏輯。
+
+        流程：
+        1. 暖機（warmup_frames 幀，不計入統計）
+        2. 正式測試（test_duration_seconds 秒）
+        3. 計算 FPS、平均延遲、p95 延遲
+
+        參數：
+            config: 測試設定。
+            runner: 推論執行函式。
+            mode: 'sequential' 或 'parallel'。
+
+        回傳：
+            BenchmarkResult。
+        """
+        # 暖機階段
+        for _ in range(config.warmup_frames):
+            runner(None)
+
+        # 正式測試
+        latencies: List[float] = []
+        test_start = time.time()
+
+        while time.time() - test_start < config.test_duration_seconds:
+            frame_start = time.time()
+            runner(None)
+            frame_end = time.time()
+            latencies.append((frame_end - frame_start) * 1000.0)  # 轉換為毫秒
+
+        total_frames = len(latencies)
+        elapsed = time.time() - test_start
+
+        # 計算統計數值
+        if total_frames == 0:
+            fps = 0.0
+            avg_latency_ms = 0.0
+            p95_latency_ms = 0.0
+        else:
+            fps = total_frames / elapsed if elapsed > 0 else 0.0
+            avg_latency_ms = statistics.mean(latencies)
+            sorted_latencies = sorted(latencies)
+            p95_index = int(len(sorted_latencies) * 0.95)
+            p95_latency_ms = sorted_latencies[min(p95_index, len(sorted_latencies) - 1)]
+
+        return BenchmarkResult(
+            mode=mode,
+            fps=fps,
+            avg_latency_ms=avg_latency_ms,
+            p95_latency_ms=p95_latency_ms,
+            total_frames=total_frames,
+            timestamp=test_start,
+            device_config=dict(self.device_config),
+        )
+
+    @staticmethod
+    def _default_runner(frame_data: Any) -> Any:
+        """預設的推論執行函式（no-op，僅供架構驗證）。"""
+        return None

core/performance/history.py

@@ -0,0 +1,233 @@
+"""
+core/performance/history.py — Benchmark 歷史記錄模組。
+
+提供 PerformanceHistory 類別，負責：
+- 將 BenchmarkResult 以 JSON 格式持久化到本地磁碟。
+- 依條件（limit / mode）查詢歷史記錄。
+- 產生兩次測試間的回歸比較報告。
+
+儲存格式範例：
+    {
+      "records": [
+        {
+          "id": "benchmark_20260405_143022",
+          "mode": "parallel",
+          "fps": 45.2,
+          "avg_latency_ms": 22.1,
+          "p95_latency_ms": 35.0,
+          "total_frames": 1356,
+          "timestamp": 1743856222.0,
+          "device_config": {"KL720": 2}
+        }
+      ]
+    }
+"""
+
+import json
+import logging
+import os
+import time
+from datetime import datetime
+from typing import Any, Dict, List, Optional
+
+logger = logging.getLogger(__name__)
+
+from .benchmarker import BenchmarkResult
+
+
+class PerformanceHistory:
+    """本地 Benchmark 歷史記錄管理器。
+
+    屬性：
+        storage_path: JSON 儲存檔案的完整路徑。
+            預設為 ``~/.cluster4npu/benchmark_history.json``。
+    """
+
+    DEFAULT_STORAGE_PATH = os.path.join(
+        os.path.expanduser("~"), ".cluster4npu", "benchmark_history.json"
+    )
+
+    def __init__(self, storage_path: str = DEFAULT_STORAGE_PATH):
+        """初始化 PerformanceHistory。
+
+        若儲存目錄不存在，會自動建立。
+
+        參數：
+            storage_path: JSON 儲存檔案路徑。
+        """
+        self.storage_path = storage_path
+        self._ensure_storage_directory()
+
+    # ------------------------------------------------------------------
+    # 公開介面
+    # ------------------------------------------------------------------
+
+    def record(self, result: BenchmarkResult) -> None:
+        """記錄一筆 BenchmarkResult 並持久化至 JSON。
+
+        此方法會：
+        1. 為結果產生唯一 id（若尚未有 id）。
+        2. 將 id 寫回 result.id。
+        3. 追加到 JSON 儲存。
+
+        參數：
+            result: 要記錄的 BenchmarkResult。
+        """
+        data = self._load_raw()
+
+        # 產生唯一 id
+        record_id = self._generate_id(result)
+        result.id = record_id
+
+        record_dict = self._result_to_dict(result)
+        data["records"].append(record_dict)
+
+        self._save_raw(data)
+
+    def get_history(
+        self,
+        limit: int = 50,
+        mode: Optional[str] = None,
+    ) -> List[BenchmarkResult]:
+        """查詢歷史記錄。
+
+        回傳最新優先（reverse chronological）的記錄列表。
+
+        參數：
+            limit: 最多回傳幾筆，預設 50。
+            mode: 若指定，只回傳符合 mode 的記錄（'sequential' 或 'parallel'）。
+
+        回傳：
+            List[BenchmarkResult]，最新的記錄排在最前面。
+        """
+        data = self._load_raw()
+        records = data.get("records", [])
+
+        # 過濾 mode
+        if mode is not None:
+            records = [r for r in records if r.get("mode") == mode]
+
+        # 最新優先（依 timestamp 降序）
+        records = sorted(records, key=lambda r: r.get("timestamp", 0), reverse=True)
+
+        # 套用 limit
+        records = records[:limit]
+
+        return [self._dict_to_result(r) for r in records]
+
+    def get_regression_report(
+        self,
+        baseline_id: str,
+        compare_id: str,
+    ) -> Dict[str, Any]:
+        """比較兩次測試的效能差異，產生回歸報告。
+
+        參數：
+            baseline_id: 基準測試的 id。
+            compare_id: 比較測試的 id。
+
+        回傳：
+            包含以下鍵的字典：
+            - baseline: BenchmarkResult（基準）
+            - compare: BenchmarkResult（比較對象）
+            - fps_change_pct: FPS 變化百分比（正值為改善）
+            - avg_latency_change_pct: 平均延遲變化百分比（負值為改善）
+            - p95_latency_change_pct: P95 延遲變化百分比（負值為改善）
+
+        引發：
+            ValueError: 若任一 id 不存在於歷史記錄中。
+        """
+        data = self._load_raw()
+        all_records = {r["id"]: r for r in data.get("records", [])}
+
+        if baseline_id not in all_records:
+            raise ValueError(f"找不到基準測試 id：{baseline_id}")
+        if compare_id not in all_records:
+            raise ValueError(f"找不到比較測試 id：{compare_id}")
+
+        baseline = self._dict_to_result(all_records[baseline_id])
+        compare = self._dict_to_result(all_records[compare_id])
+
+        def pct_change(old: float, new: float) -> float:
+            """計算相對變化百分比。"""
+            if old == 0:
+                return 0.0
+            return (new - old) / old * 100.0
+
+        return {
+            "baseline": baseline,
+            "compare": compare,
+            "fps_change_pct": pct_change(baseline.fps, compare.fps),
+            "avg_latency_change_pct": pct_change(
+                baseline.avg_latency_ms, compare.avg_latency_ms
+            ),
+            "p95_latency_change_pct": pct_change(
+                baseline.p95_latency_ms, compare.p95_latency_ms
+            ),
+        }
+
+    # ------------------------------------------------------------------
+    # 內部實作
+    # ------------------------------------------------------------------
+
+    def _ensure_storage_directory(self) -> None:
+        """若儲存目錄不存在，自動建立。"""
+        parent_dir = os.path.dirname(self.storage_path)
+        if parent_dir:
+            os.makedirs(parent_dir, exist_ok=True)
+
+    def _load_raw(self) -> Dict[str, Any]:
+        """從 JSON 檔案讀取原始資料。若檔案不存在或損毀，回傳空結構。"""
+        if not os.path.exists(self.storage_path):
+            return {"records": []}
+        try:
+            with open(self.storage_path, "r", encoding="utf-8") as f:
+                return json.load(f)
+        except json.JSONDecodeError as e:
+            logger.warning("歷史記錄 JSON 檔案損毀，降級回傳空結構：%s", e)
+            return {"records": []}
+        except (IOError, OSError) as e:
+            logger.warning("無法讀取歷史記錄檔案，降級回傳空結構：%s", e)
+            return {"records": []}
+
+    def _save_raw(self, data: Dict[str, Any]) -> None:
+        """將資料寫入 JSON 檔案。"""
+        with open(self.storage_path, "w", encoding="utf-8") as f:
+            json.dump(data, f, ensure_ascii=False, indent=2)
+
+    @staticmethod
+    def _generate_id(result: BenchmarkResult) -> str:
+        """依 timestamp 產生唯一識別碼。
+
+        格式：``benchmark_YYYYMMDD_HHMMSSffffff``
+        """
+        dt = datetime.fromtimestamp(result.timestamp)
+        return dt.strftime("benchmark_%Y%m%d_%H%M%S%f")
+
+    @staticmethod
+    def _result_to_dict(result: BenchmarkResult) -> Dict[str, Any]:
+        """將 BenchmarkResult 轉換為可序列化的字典。"""
+        return {
+            "id": result.id,
+            "mode": result.mode,
+            "fps": result.fps,
+            "avg_latency_ms": result.avg_latency_ms,
+            "p95_latency_ms": result.p95_latency_ms,
+            "total_frames": result.total_frames,
+            "timestamp": result.timestamp,
+            "device_config": result.device_config,
+        }
+
+    @staticmethod
+    def _dict_to_result(data: Dict[str, Any]) -> BenchmarkResult:
+        """將字典轉換回 BenchmarkResult。"""
+        return BenchmarkResult(
+            id=data.get("id"),
+            mode=data["mode"],
+            fps=data["fps"],
+            avg_latency_ms=data["avg_latency_ms"],
+            p95_latency_ms=data["p95_latency_ms"],
+            total_frames=data["total_frames"],
+            timestamp=data["timestamp"],
+            device_config=data.get("device_config", {}),
+        )

core/performance/report_exporter.py

@@ -0,0 +1,428 @@
+"""
+core/performance/report_exporter.py — 效能報告匯出模組。
+
+提供 DeviceSummary、ReportData 資料結構與 ReportExporter 主類別，
+支援將 Benchmark 結果匯出為 PDF（需要 reportlab）或 CSV（標準庫）。
+
+設計重點：
+- ReportExporter 不依賴 PyQt5，只依賴 reportlab 與標準庫。
+- reportlab 以 try/except ImportError 保護；若未安裝，export_pdf() 拋出 ImportError。
+- export_csv() 只用標準庫 csv，永遠可用。
+- 無狀態設計（stateless）：每次匯出建立新實例或直接呼叫靜態方法。
+"""
+
+from __future__ import annotations
+
+import csv
+import io
+import time
+from dataclasses import dataclass, field
+from pathlib import Path
+from typing import Any, List, Optional
+
+# ---------------------------------------------------------------------------
+# reportlab 可用性旗標
+# ---------------------------------------------------------------------------
+
+try:
+    from reportlab.platypus import SimpleDocTemplate  # noqa: F401
+    _REPORTLAB_AVAILABLE = True
+except ImportError:
+    _REPORTLAB_AVAILABLE = False
+
+
+# ---------------------------------------------------------------------------
+# 資料結構
+# ---------------------------------------------------------------------------
+
+@dataclass
+class DeviceSummary:
+    """單一裝置的摘要資訊，來自 DeviceManager。"""
+    device_id: str
+    product_name: str          # 如 "KL720"
+    firmware_version: str
+    is_active: bool
+
+
+@dataclass
+class ReportData:
+    """
+    報告所需的完整資料，由呼叫方（UI 層）從各模組收集後傳入 ReportExporter。
+    設計為純資料容器，與 UI / SDK 解耦，方便單元測試。
+    """
+    # 報告基本資訊
+    report_title: str = "效能測試報告"
+    generated_at: float = field(default_factory=time.time)   # UNIX timestamp
+    pipeline_name: str = ""        # 來自 .mflow 檔名或使用者命名
+
+    # Benchmark 結果（來自 PerformanceBenchmarker.run_full_benchmark()）
+    sequential_result: Optional[Any] = None   # BenchmarkResult
+    parallel_result: Optional[Any] = None     # BenchmarkResult
+    speedup: Optional[float] = None           # par.fps / seq.fps
+
+    # 歷史記錄（來自 PerformanceHistory.get_history()）
+    history_records: List[Any] = field(default_factory=list)  # List[BenchmarkResult]
+
+    # 裝置資訊（來自 DeviceManager.get_all_devices()）
+    devices: List[DeviceSummary] = field(default_factory=list)
+
+    # 圖表截圖（由 UI 層在匯出前擷取）
+    chart_image_bytes: Optional[bytes] = None  # PNG bytes，來自 PerformanceDashboard
+
+
+# ---------------------------------------------------------------------------
+# ReportExporter
+# ---------------------------------------------------------------------------
+
+class ReportExporter:
+    """
+    負責將 ReportData 序列化為 PDF 或 CSV 檔案。
+    無狀態設計（stateless）：每次匯出建立新實例或直接呼叫靜態方法。
+    """
+
+    # ------------------------------------------------------------------
+    # PDF 匯出
+    # ------------------------------------------------------------------
+
+    def export_pdf(
+        self,
+        data: ReportData,
+        output_path: "str | Path",
+    ) -> Path:
+        """
+        將完整效能報告匯出為 PDF。
+        回傳實際寫入的檔案路徑。
+        若 output_path 的父目錄不存在，自動建立。
+
+        引發：
+            ImportError: 若 reportlab 未安裝，提示安裝指令。
+        """
+        if not _REPORTLAB_AVAILABLE:
+            raise ImportError(
+                "reportlab is required for PDF export. Install with: pip install reportlab>=4.0.0"
+            )
+
+        try:
+            from reportlab.platypus import (
+                SimpleDocTemplate,
+                Table,
+                TableStyle,
+                Paragraph,
+                Spacer,
+                Image,
+            )
+            from reportlab.lib.pagesizes import A4
+            from reportlab.lib.styles import getSampleStyleSheet
+            from reportlab.lib import colors
+            from reportlab.lib.units import mm
+            import reportlab  # noqa: F401  — 確認已安裝
+        except ImportError as e:
+            raise ImportError(
+                f"reportlab 未安裝，請執行：pip install reportlab>=4.0.0\n原始錯誤：{e}"
+            ) from e
+
+        output_path = Path(output_path)
+        output_path.parent.mkdir(parents=True, exist_ok=True)
+
+        doc = SimpleDocTemplate(
+            str(output_path),
+            pagesize=A4,
+            rightMargin=20 * mm,
+            leftMargin=20 * mm,
+            topMargin=20 * mm,
+            bottomMargin=20 * mm,
+        )
+
+        story: list = []
+        styles = getSampleStyleSheet()
+
+        # 封面（用 Paragraph 實作，封面 callback 難以在無 GUI 環境穩定測試）
+        self._build_cover_paragraphs(story, data, styles, Paragraph, Spacer)
+
+        # Benchmark 結果表
+        self._build_benchmark_table(story, data, styles, Table, TableStyle, Paragraph, Spacer, colors)
+
+        # 趨勢圖
+        self._build_trend_chart(story, data, styles, Paragraph, Spacer, Image)
+
+        # 歷史記錄表
+        self._build_history_table(story, data, styles, Table, TableStyle, Paragraph, Spacer, colors)
+
+        # 裝置資訊
+        self._build_device_info(story, data, styles, Paragraph, Spacer)
+
+        doc.build(story)
+        return output_path
+
+    def _build_cover_page(self, canvas, data: ReportData) -> None:
+        """繪製封面：報告標題、生成時間、Pipeline 名稱、裝置清單（canvas callback 版本）"""
+        canvas.saveState()
+        canvas.setFont("Helvetica-Bold", 24)
+        canvas.drawCentredString(
+            canvas._pagesize[0] / 2,
+            canvas._pagesize[1] * 0.65,
+            data.report_title,
+        )
+        canvas.setFont("Helvetica", 12)
+        canvas.drawCentredString(
+            canvas._pagesize[0] / 2,
+            canvas._pagesize[1] * 0.58,
+            f"生成時間：{self._get_timestamp_str(data.generated_at)}",
+        )
+        if data.pipeline_name:
+            canvas.drawCentredString(
+                canvas._pagesize[0] / 2,
+                canvas._pagesize[1] * 0.53,
+                f"Pipeline：{data.pipeline_name}",
+            )
+        canvas.drawCentredString(
+            canvas._pagesize[0] / 2,
+            canvas._pagesize[1] * 0.48,
+            f"裝置數量：{len(data.devices)}",
+        )
+        canvas.restoreState()
+
+    def _build_cover_paragraphs(self, story, data, styles, Paragraph, Spacer) -> None:
+        """以 Paragraph flowable 形式建立封面內容（嵌入 story 流）。"""
+        story.append(Spacer(1, 60))
+        story.append(Paragraph(data.report_title, styles["Title"]))
+        story.append(Spacer(1, 12))
+        story.append(Paragraph(
+            f"生成時間：{self._get_timestamp_str(data.generated_at)}",
+            styles["Normal"],
+        ))
+        if data.pipeline_name:
+            story.append(Paragraph(f"Pipeline：{data.pipeline_name}", styles["Normal"]))
+        story.append(Paragraph(f"裝置數量：{len(data.devices)}", styles["Normal"]))
+        story.append(Spacer(1, 30))
+
+    def _build_benchmark_table(
+        self, story, data, styles=None,
+        Table=None, TableStyle=None, Paragraph=None, Spacer=None, colors=None,
+    ) -> None:
+        """
+        建立 Benchmark 結果對比表（reportlab Table）。
+        欄位：指標 / 循序模式 / 平行模式 / 差異%
+        指標：FPS、平均延遲(ms)、P95 延遲(ms)、總幀數
+        """
+        if Paragraph is None:
+            return
+        story.append(Paragraph("Benchmark 結果", styles["Heading1"]))
+        story.append(Spacer(1, 8))
+
+        seq = data.sequential_result
+        par = data.parallel_result
+
+        if seq is None or par is None:
+            story.append(Paragraph("無 Benchmark 資料", styles["Normal"]))
+            story.append(Spacer(1, 12))
+            return
+
+        def diff_pct(a, b):
+            if a and a != 0:
+                return f"{(b - a) / a * 100:+.1f}%"
+            return "—"
+
+        table_data = [
+            ["指標", "循序模式", "平行模式", "差異%"],
+            ["FPS", f"{seq.fps:.1f}", f"{par.fps:.1f}", diff_pct(seq.fps, par.fps)],
+            ["平均延遲(ms)", f"{seq.avg_latency_ms:.1f}", f"{par.avg_latency_ms:.1f}", diff_pct(seq.avg_latency_ms, par.avg_latency_ms)],
+            ["P95 延遲(ms)", f"{seq.p95_latency_ms:.1f}", f"{par.p95_latency_ms:.1f}", diff_pct(seq.p95_latency_ms, par.p95_latency_ms)],
+            ["總幀數", str(seq.total_frames), str(par.total_frames), "—"],
+        ]
+        if data.speedup is not None:
+            table_data.append(["加速倍數", "—", f"{data.speedup:.2f}x", "—"])
+
+        t = Table(table_data)
+        t.setStyle(TableStyle([
+            ("BACKGROUND", (0, 0), (-1, 0), colors.grey),
+            ("TEXTCOLOR", (0, 0), (-1, 0), colors.whitesmoke),
+            ("ALIGN", (0, 0), (-1, -1), "CENTER"),
+            ("FONTNAME", (0, 0), (-1, 0), "Helvetica-Bold"),
+            ("GRID", (0, 0), (-1, -1), 0.5, colors.black),
+        ]))
+        story.append(t)
+        story.append(Spacer(1, 20))
+
+    def _build_trend_chart(
+        self, story, data, styles=None,
+        Paragraph=None, Spacer=None, Image=None,
+    ) -> None:
+        """
+        若 data.chart_image_bytes 不為 None，將圖表 PNG 嵌入 PDF。
+        若為 None，插入「無圖表資料」的提示文字。
+        """
+        if Paragraph is None:
+            return
+        story.append(Paragraph("效能趨勢圖", styles["Heading1"]))
+        story.append(Spacer(1, 8))
+        if data.chart_image_bytes is not None:
+            img_buf = io.BytesIO(data.chart_image_bytes)
+            img = Image(img_buf, width=400, height=200)
+            story.append(img)
+        else:
+            story.append(Paragraph("（無圖表資料）", styles["Normal"]))
+        story.append(Spacer(1, 20))
+
+    def _build_history_table(
+        self, story, data, styles=None,
+        Table=None, TableStyle=None, Paragraph=None, Spacer=None, colors=None,
+    ) -> None:
+        """
+        建立歷史記錄表（最多顯示 20 筆，超過則截斷並標注）。
+        欄位：測試時間 / 模式 / FPS / 平均延遲(ms) / P95 延遲(ms)
+        """
+        if Paragraph is None:
+            return
+        story.append(Paragraph("歷史記錄", styles["Heading1"]))
+        story.append(Spacer(1, 8))
+
+        records = data.history_records[:20]
+        truncated = len(data.history_records) > 20
+
+        table_data = [["測試時間", "模式", "FPS", "平均延遲(ms)", "P95 延遲(ms)"]]
+        for r in records:
+            table_data.append([
+                self._get_timestamp_str(r.timestamp),
+                r.mode,
+                f"{r.fps:.1f}",
+                f"{r.avg_latency_ms:.1f}",
+                f"{r.p95_latency_ms:.1f}",
+            ])
+
+        if not records:
+            table_data.append(["（無記錄）", "", "", "", ""])
+
+        t = Table(table_data)
+        t.setStyle(TableStyle([
+            ("BACKGROUND", (0, 0), (-1, 0), colors.grey),
+            ("TEXTCOLOR", (0, 0), (-1, 0), colors.whitesmoke),
+            ("ALIGN", (0, 0), (-1, -1), "CENTER"),
+            ("FONTNAME", (0, 0), (-1, 0), "Helvetica-Bold"),
+            ("GRID", (0, 0), (-1, -1), 0.5, colors.black),
+        ]))
+        story.append(t)
+
+        if truncated:
+            story.append(Spacer(1, 6))
+            story.append(Paragraph(
+                f"（僅顯示最新 20 筆，共 {len(data.history_records)} 筆）",
+                styles["Normal"],
+            ))
+        story.append(Spacer(1, 20))
+
+    def _build_device_info(
+        self, story, data, styles=None,
+        Paragraph=None, Spacer=None,
+    ) -> None:
+        """列出測試時連接的裝置清單：裝置 ID、型號、韌體版本、是否啟用。"""
+        if Paragraph is None:
+            return
+        story.append(Paragraph("裝置資訊", styles["Heading1"]))
+        story.append(Spacer(1, 8))
+        if not data.devices:
+            story.append(Paragraph("（無裝置資訊）", styles["Normal"]))
+        else:
+            for dev in data.devices:
+                status = "啟用" if dev.is_active else "停用"
+                story.append(Paragraph(
+                    f"裝置 {dev.device_id}：{dev.product_name}，韌體 {dev.firmware_version}，{status}",
+                    styles["Normal"],
+                ))
+        story.append(Spacer(1, 12))
+
+    # ------------------------------------------------------------------
+    # CSV 匯出
+    # ------------------------------------------------------------------
+
+    def export_csv(
+        self,
+        data: ReportData,
+        output_path: "str | Path",
+    ) -> Path:
+        """
+        將 Benchmark 結果與歷史記錄匯出為 CSV。
+        CSV 包含兩個邏輯區塊（以空行分隔）：
+        1. Benchmark 摘要（循序 vs 平行對比）
+        2. 歷史記錄（每筆 BenchmarkResult 一行）
+        回傳實際寫入的檔案路徑。
+
+        引發：
+            ValueError: sequential_result 或 parallel_result 為 None 時。
+        """
+        if data.sequential_result is None or data.parallel_result is None:
+            raise ValueError(
+                "export_csv() 需要 sequential_result 與 parallel_result，但其中一個為 None。"
+            )
+
+        output_path = Path(output_path)
+        output_path.parent.mkdir(parents=True, exist_ok=True)
+
+        seq = data.sequential_result
+        par = data.parallel_result
+
+        def diff_pct(a, b):
+            if a and a != 0:
+                return f"{(b - a) / a * 100:+.1f}%"
+            return "—"
+
+        with output_path.open("w", newline="", encoding="utf-8") as f:
+            writer = csv.writer(f)
+
+            # 區塊 1：Benchmark 摘要
+            writer.writerow(["section", "metric", "sequential", "parallel", "diff_pct"])
+            writer.writerow([
+                "benchmark_summary", "fps",
+                f"{seq.fps:.1f}", f"{par.fps:.1f}",
+                diff_pct(seq.fps, par.fps),
+            ])
+            writer.writerow([
+                "benchmark_summary", "avg_latency_ms",
+                f"{seq.avg_latency_ms:.1f}", f"{par.avg_latency_ms:.1f}",
+                diff_pct(seq.avg_latency_ms, par.avg_latency_ms),
+            ])
+            writer.writerow([
+                "benchmark_summary", "p95_latency_ms",
+                f"{seq.p95_latency_ms:.1f}", f"{par.p95_latency_ms:.1f}",
+                diff_pct(seq.p95_latency_ms, par.p95_latency_ms),
+            ])
+            writer.writerow([
+                "benchmark_summary", "total_frames",
+                str(seq.total_frames), str(par.total_frames),
+                "—",
+            ])
+            speedup_val = f"{data.speedup:.2f}x" if data.speedup is not None else "—"
+            writer.writerow([
+                "benchmark_summary", "speedup",
+                "—", speedup_val,
+                "—",
+            ])
+
+            # 空行分隔
+            writer.writerow([])
+
+            # 區塊 2：歷史記錄
+            writer.writerow(["id", "timestamp", "mode", "fps", "avg_latency_ms", "p95_latency_ms", "total_frames"])
+            for r in data.history_records:
+                writer.writerow([
+                    r.id or "",
+                    self._get_timestamp_str(r.timestamp),
+                    r.mode,
+                    f"{r.fps:.1f}",
+                    f"{r.avg_latency_ms:.1f}",
+                    f"{r.p95_latency_ms:.1f}",
+                    str(r.total_frames),
+                ])
+
+        return output_path
+
+    # ------------------------------------------------------------------
+    # 工廠方法
+    # ------------------------------------------------------------------
+
+    @staticmethod
+    def _get_timestamp_str(ts: float) -> str:
+        """將 UNIX timestamp 格式化為 'YYYY-MM-DD HH:MM:SS'（本地時間）。"""
+        import time as _time
+        local = _time.localtime(ts)
+        return _time.strftime("%Y-%m-%d %H:%M:%S", local)

core/templates/__init__.py

@@ -0,0 +1 @@
+"""core/templates — Pipeline 設定範本模組。"""

core/templates/manager.py

@@ -0,0 +1,182 @@
+"""
+core/templates/manager.py
+
+TemplateManager — 提供常見使用情境的預設 Pipeline 範本。
+
+設計重點：
+- 三個內建範本（yolov5_detection、fire_detection、dual_model_cascade）以常數定義。
+- save_as_template 將自訂範本儲存於記憶體（in-memory），不持久化到磁碟。
+- load_template 先查內建範本，再查自訂範本；找不到時拋出 ValueError。
+- nodes/connections 格式與 .mflow JSON 相同（id、type 為必要欄位）。
+"""
+from __future__ import annotations
+
+import time
+from dataclasses import dataclass, field
+from typing import Any, Dict, List, Optional
+
+
+@dataclass
+class PipelineTemplate:
+    """單一 Pipeline 範本。
+
+    屬性：
+        template_id: 唯一識別碼（內建範本使用語意名稱；自訂範本以 custom_ 開頭）。
+        name: 顯示名稱（如 "YOLOv5 物件偵測"）。
+        description: 範本說明。
+        nodes: 節點定義列表，格式與 .mflow 相同，每個節點至少含 id 和 type。
+        connections: 連線定義列表，每條連線含 from 和 to。
+    """
+    template_id: str
+    name: str
+    description: str
+    nodes: List[Dict[str, Any]]
+    connections: List[Dict[str, Any]]
+
+
+# ---------------------------------------------------------------------------
+# 內建範本定義
+# ---------------------------------------------------------------------------
+
+_BUILTIN_TEMPLATES: List[PipelineTemplate] = [
+    PipelineTemplate(
+        template_id="yolov5_detection",
+        name="YOLOv5 物件偵測",
+        description="標準 YOLOv5 物件偵測流程：輸入影像經前處理後送入模型，後處理輸出邊界框結果。",
+        nodes=[
+            {"id": "input_0",      "type": "Input",       "label": "Input"},
+            {"id": "preprocess_0", "type": "Preprocess",  "label": "Preprocess"},
+            {"id": "model_0",      "type": "Model",       "label": "Model"},
+            {"id": "postprocess_0","type": "Postprocess", "label": "Postprocess"},
+            {"id": "output_0",     "type": "Output",      "label": "Output"},
+        ],
+        connections=[
+            {"from": "input_0",       "to": "preprocess_0"},
+            {"from": "preprocess_0",  "to": "model_0"},
+            {"from": "model_0",       "to": "postprocess_0"},
+            {"from": "postprocess_0", "to": "output_0"},
+        ],
+    ),
+    PipelineTemplate(
+        template_id="fire_detection",
+        name="火焰偵測分類",
+        description="火焰偵測流程：影像直接送入模型推論，後處理輸出火焰偵測結果（無前處理節點）。",
+        nodes=[
+            {"id": "input_0",      "type": "Input",       "label": "Input"},
+            {"id": "model_0",      "type": "Model",       "label": "Model"},
+            {"id": "postprocess_0","type": "Postprocess", "label": "Postprocess"},
+            {"id": "output_0",     "type": "Output",      "label": "Output"},
+        ],
+        connections=[
+            {"from": "input_0",       "to": "model_0"},
+            {"from": "model_0",       "to": "postprocess_0"},
+            {"from": "postprocess_0", "to": "output_0"},
+        ],
+    ),
+    PipelineTemplate(
+        template_id="dual_model_cascade",
+        name="雙模型串接",
+        description=(
+            "兩個模型串接的複合推論流程：第一個模型的輸出結果經後處理後，"
+            "作為第二個模型的輸入，適合先偵測後分類的使用情境。"
+        ),
+        nodes=[
+            {"id": "input_0",       "type": "Input",       "label": "Input"},
+            {"id": "model_0",       "type": "Model",       "label": "Model 1"},
+            {"id": "postprocess_0", "type": "Postprocess", "label": "Postprocess 1"},
+            {"id": "model_1",       "type": "Model",       "label": "Model 2"},
+            {"id": "postprocess_1", "type": "Postprocess", "label": "Postprocess 2"},
+            {"id": "output_0",      "type": "Output",      "label": "Output"},
+        ],
+        connections=[
+            {"from": "input_0",       "to": "model_0"},
+            {"from": "model_0",       "to": "postprocess_0"},
+            {"from": "postprocess_0", "to": "model_1"},
+            {"from": "model_1",       "to": "postprocess_1"},
+            {"from": "postprocess_1", "to": "output_0"},
+        ],
+    ),
+]
+
+# 以 template_id 建立快速查找字典
+_BUILTIN_BY_ID: Dict[str, PipelineTemplate] = {
+    t.template_id: t for t in _BUILTIN_TEMPLATES
+}
+
+
+# ---------------------------------------------------------------------------
+# TemplateManager
+# ---------------------------------------------------------------------------
+
+class TemplateManager:
+    """管理內建與自訂 Pipeline 範本。
+
+    自訂範本儲存於記憶體，每個 TemplateManager 實例各自獨立。
+    """
+
+    def __init__(self) -> None:
+        # 自訂範本字典：{template_id: PipelineTemplate}
+        self._custom: Dict[str, PipelineTemplate] = {}
+
+    # ------------------------------------------------------------------
+    # 公開介面
+    # ------------------------------------------------------------------
+
+    def get_builtin_templates(self) -> List[PipelineTemplate]:
+        """回傳所有內建範本的清單（共 3 個）。
+
+        回傳：
+            PipelineTemplate 列表（不含自訂範本）。
+        """
+        return list(_BUILTIN_TEMPLATES)
+
+    def load_template(self, template_id: str) -> PipelineTemplate:
+        """依 template_id 載入範本。
+
+        查找順序：內建範本 → 自訂範本。
+
+        參數：
+            template_id: 範本唯一識別碼。
+
+        回傳：
+            對應的 PipelineTemplate。
+
+        引發：
+            ValueError: 當 template_id 不存在於任何範本時。
+        """
+        if template_id in _BUILTIN_BY_ID:
+            return _BUILTIN_BY_ID[template_id]
+
+        if template_id in self._custom:
+            return self._custom[template_id]
+
+        raise ValueError(f"Template {template_id} not found")
+
+    def save_as_template(
+        self,
+        pipeline_config: Dict[str, Any],
+        name: str,
+        description: str,
+    ) -> PipelineTemplate:
+        """將 Pipeline 設定儲存為新的自訂範本。
+
+        參數：
+            pipeline_config: 包含 nodes 和 connections 列表的字典。
+            name: 範本顯示名稱。
+            description: 範本說明。
+
+        回傳：
+            新建立的 PipelineTemplate（template_id 以 custom_ 開頭）。
+        """
+        safe_name = name.lower().replace(" ", "_")
+        template_id = f"custom_{safe_name}_{int(time.time() * 1000)}"
+
+        template = PipelineTemplate(
+            template_id=template_id,
+            name=name,
+            description=description,
+            nodes=list(pipeline_config.get("nodes", [])),
+            connections=list(pipeline_config.get("connections", [])),
+        )
+        self._custom[template_id] = template
+        return template

tests/unit/conftest.py

@@ -0,0 +1,295 @@
+"""
+pytest conftest.py — 單元測試環境設定。
+
+此測試環境沒有 Kneron NPU 硬體，也沒有 PyQt5 等 GUI 函式庫。
+為了能夠測試純 Python 的 core/ 和 ui/ 模組，
+在收集測試前預先注入 Mock 模組，避免 import 時觸發硬體/GUI 初始化。
+
+UI 元件測試需要 QWidget 等基底類別可被正常繼承與多次實例化，
+因此使用輕量 Stub 取代 MagicMock 作為 PyQt5 Widget 基底。
+"""
+import sys
+from unittest.mock import MagicMock
+
+
+def _install_mock(name: str) -> None:
+    """若模組尚未存在，安裝空 MagicMock 作為替代。"""
+    if name not in sys.modules:
+        sys.modules[name] = MagicMock()
+
+
+# Kneron KP SDK（需要硬體驅動程式）
+_install_mock("kp")
+
+# NumPy（可能未安裝）
+try:
+    import numpy  # noqa: F401
+except ImportError:
+    _install_mock("numpy")
+
+# OpenCV（可能未安裝）
+_install_mock("cv2")
+
+# NodeGraphQt（依賴 PyQt5）
+_install_mock("NodeGraphQt")
+_install_mock("NodeGraphQt.constants")
+_install_mock("NodeGraphQt.base")
+_install_mock("NodeGraphQt.base.node")
+
+# ---------------------------------------------------------------------------
+# PyQt5 Stub — 允許 QWidget/QDialog 子類別被正常繼承並多次實例化。
+# 使用輕量 Python 類別替代，避免 MagicMock 繼承時的 side_effect 耗盡問題。
+# ---------------------------------------------------------------------------
+
+
+class _StubQObject:
+    """所有 Qt 物件的基底 Stub。"""
+    def __init__(self, *args, **kwargs):
+        pass
+
+
+class _StubQWidget(_StubQObject):
+    """QWidget Stub：可被繼承，支援多次實例化。提供常用 QWidget 方法的空實作。"""
+
+    def setLayout(self, layout):
+        pass
+
+    def setParent(self, parent):
+        pass
+
+    def show(self):
+        pass
+
+    def hide(self):
+        pass
+
+    def setVisible(self, visible: bool):
+        pass
+
+    def setEnabled(self, enabled: bool):
+        pass
+
+    def isEnabled(self) -> bool:
+        return True
+
+    def setObjectName(self, name: str):
+        pass
+
+    def setStyleSheet(self, style: str):
+        pass
+
+    def setMinimumWidth(self, w: int):
+        pass
+
+    def setMinimumHeight(self, h: int):
+        pass
+
+    def setMaximumWidth(self, w: int):
+        pass
+
+    def setMaximumHeight(self, h: int):
+        pass
+
+    def resize(self, *args):
+        pass
+
+    def setWindowTitle(self, title: str):
+        pass
+
+    def setSizePolicy(self, *args):
+        pass
+
+    def update(self):
+        pass
+
+    def repaint(self):
+        pass
+
+    def close(self):
+        pass
+
+    def font(self):
+        return MagicMock()
+
+    def setFont(self, font):
+        pass
+
+
+class _StubQDialog(_StubQWidget):
+    """QDialog Stub。"""
+
+    Accepted = 1
+    Rejected = 0
+
+    def exec_(self):
+        return self.Accepted
+
+    def accept(self):
+        pass
+
+    def reject(self):
+        pass
+
+
+class _StubQLabel(_StubQWidget):
+    """QLabel Stub：追蹤 setText 呼叫，可在測試中驗證顯示文字。"""
+    def __init__(self, text: str = "", parent=None):
+        super().__init__(parent)
+        self._text = text
+        self.setText = MagicMock(side_effect=self._set_text)
+
+    def _set_text(self, text: str) -> None:
+        self._text = text
+
+    def text(self) -> str:
+        return self._text
+
+
+class _StubLayout(_StubQObject):
+    """QLayout Stub：忽略所有 add* 呼叫。"""
+    def addWidget(self, *args, **kwargs):
+        pass
+
+    def addLayout(self, *args, **kwargs):
+        pass
+
+    def addStretch(self, *args, **kwargs):
+        pass
+
+    def setSpacing(self, *args, **kwargs):
+        pass
+
+    def setContentsMargins(self, *args, **kwargs):
+        pass
+
+
+class _StubQVBoxLayout(_StubLayout):
+    pass
+
+
+class _StubQHBoxLayout(_StubLayout):
+    pass
+
+
+class _StubQProgressBar(_StubQWidget):
+    def __init__(self, parent=None):
+        super().__init__(parent)
+        self._value = 0
+        self._maximum = 100
+        self._minimum = 0
+        self.setValue = MagicMock(side_effect=self._set_value)
+
+    def _set_value(self, v: int) -> None:
+        self._value = v
+
+    def value(self) -> int:
+        return self._value
+
+    def setMaximum(self, v: int) -> None:
+        self._maximum = v
+
+    def setMinimum(self, v: int) -> None:
+        self._minimum = v
+
+
+class _StubQTableWidget(_StubQWidget):
+    def __init__(self, *args, **kwargs):
+        super().__init__()
+        self.setItem = MagicMock()
+        self.setHorizontalHeaderLabels = MagicMock()
+
+
+class _StubQPushButton(_StubQWidget):
+    def __init__(self, text: str = "", parent=None):
+        super().__init__(parent)
+        self._text = text
+        self._enabled = True
+        self.clicked = MagicMock()
+        self.setEnabled = MagicMock(side_effect=self._set_enabled)
+
+    def _set_enabled(self, enabled: bool) -> None:
+        self._enabled = enabled
+
+    def isEnabled(self) -> bool:
+        return self._enabled
+
+
+def _make_pyqt_signal(*args, **kwargs):
+    """pyqtSignal Stub：回傳可 connect/emit 的 MagicMock。"""
+    signal = MagicMock()
+    signal.connect = MagicMock()
+    signal.emit = MagicMock()
+    return signal
+
+
+def _make_qthread():
+    """QThread Stub。"""
+    class _StubQThread(_StubQObject):
+        started = MagicMock()
+        finished = MagicMock()
+
+        def start(self):
+            pass
+
+        def isRunning(self):
+            return False
+
+        def wait(self):
+            pass
+
+        def run(self):
+            pass
+
+        def deleteLater(self):
+            pass
+
+    return _StubQThread
+
+
+# 建立 PyQt5.QtWidgets Mock 模組（保留 MagicMock 為底，覆蓋關鍵類別）
+_qtwidgets_mock = MagicMock()
+_qtwidgets_mock.QWidget = _StubQWidget
+_qtwidgets_mock.QDialog = _StubQDialog
+_qtwidgets_mock.QLabel = _StubQLabel
+_qtwidgets_mock.QVBoxLayout = _StubQVBoxLayout
+_qtwidgets_mock.QHBoxLayout = _StubQHBoxLayout
+_qtwidgets_mock.QProgressBar = _StubQProgressBar
+_qtwidgets_mock.QTableWidget = _StubQTableWidget
+_qtwidgets_mock.QPushButton = _StubQPushButton
+_qtwidgets_mock.QSizePolicy = MagicMock()
+_qtwidgets_mock.QTableWidgetItem = MagicMock()
+_qtwidgets_mock.QHeaderView = MagicMock()
+_qtwidgets_mock.QMessageBox = MagicMock()
+_qtwidgets_mock.QApplication = MagicMock()
+_qtwidgets_mock.QGroupBox = _StubQWidget
+_qtwidgets_mock.QFrame = _StubQWidget
+_qtwidgets_mock.QScrollArea = _StubQWidget
+_qtwidgets_mock.QSpinBox = _StubQWidget
+_qtwidgets_mock.QComboBox = _StubQWidget
+_qtwidgets_mock.QCheckBox = _StubQWidget
+
+# 建立 PyQt5.QtCore Mock 模組
+_qtcore_mock = MagicMock()
+_qtcore_mock.pyqtSignal = _make_pyqt_signal
+_qtcore_mock.QThread = _make_qthread()
+_qtcore_mock.Qt = MagicMock()
+_qtcore_mock.QTimer = MagicMock()
+_qtcore_mock.QObject = _StubQObject
+
+# 建立 PyQt5.QtGui Mock 模組
+_qtgui_mock = MagicMock()
+
+# 建立頂層 PyQt5 Mock
+_pyqt5_mock = MagicMock()
+_pyqt5_mock.QtWidgets = _qtwidgets_mock
+_pyqt5_mock.QtCore = _qtcore_mock
+_pyqt5_mock.QtGui = _qtgui_mock
+
+sys.modules["PyQt5"] = _pyqt5_mock
+sys.modules["PyQt5.QtWidgets"] = _qtwidgets_mock
+sys.modules["PyQt5.QtCore"] = _qtcore_mock
+sys.modules["PyQt5.QtGui"] = _qtgui_mock
+sys.modules["PyQt5.QtChart"] = MagicMock()
+
+# pyqtgraph（選配）
+_install_mock("pyqtgraph")

tests/unit/test_benchmark_dialog.py

@@ -0,0 +1,134 @@
+"""
+BenchmarkDialog 的單元測試。
+
+測試策略：
+- PyQt5 在 CI 環境中不可用，透過 conftest.py 的 Stub 注入繞過 import。
+- 測試驗證 BenchmarkDialog 的行為邏輯：
+  - 對話框可正常建立
+  - pipeline_config 為空時開始按鈕被禁用
+  - show_result 正確顯示加速倍數文字
+  - update_progress 更新進度條值
+"""
+import pytest
+from unittest.mock import MagicMock
+
+
+# ---------------------------------------------------------------------------
+# 測試：BenchmarkDialog 可以建立
+# ---------------------------------------------------------------------------
+
+class TestBenchmarkDialogInit:
+    def should_be_importable(self):
+        """BenchmarkDialog 模組應可匯入（即使 PyQt5 被 Stub）。"""
+        from ui.dialogs.benchmark_dialog import BenchmarkDialog
+        assert BenchmarkDialog is not None
+
+    def should_instantiate_with_valid_config(self):
+        """提供非空 pipeline_config 時，BenchmarkDialog 應可正常建立。"""
+        from ui.dialogs.benchmark_dialog import BenchmarkDialog
+        stage_config = MagicMock()
+        dialog = BenchmarkDialog(parent=None, pipeline_config=[stage_config])
+        assert dialog is not None
+
+    def should_instantiate_with_empty_config(self):
+        """pipeline_config 為空時，BenchmarkDialog 應可建立（不應拋出例外）。"""
+        from ui.dialogs.benchmark_dialog import BenchmarkDialog
+        dialog = BenchmarkDialog(parent=None, pipeline_config=[])
+        assert dialog is not None
+
+
+# ---------------------------------------------------------------------------
+# 測試：pipeline_config 為空時禁用開始按鈕
+# ---------------------------------------------------------------------------
+
+class TestStartButtonDisabledWhenEmptyConfig:
+    def should_disable_start_button_when_pipeline_config_is_empty(self):
+        """pipeline_config 為空時，start_button 應被禁用。"""
+        from ui.dialogs.benchmark_dialog import BenchmarkDialog
+        dialog = BenchmarkDialog(parent=None, pipeline_config=[])
+        assert dialog.start_button.isEnabled() is False
+
+    def should_enable_start_button_when_pipeline_config_has_stages(self):
+        """pipeline_config 有 Stage 時，start_button 應為啟用狀態。"""
+        from ui.dialogs.benchmark_dialog import BenchmarkDialog
+        stage_config = MagicMock()
+        dialog = BenchmarkDialog(parent=None, pipeline_config=[stage_config])
+        assert dialog.start_button.isEnabled() is True
+
+    def should_show_info_label_when_pipeline_config_is_empty(self):
+        """pipeline_config 為空時，應有提示訊息 label 顯示。"""
+        from ui.dialogs.benchmark_dialog import BenchmarkDialog
+        dialog = BenchmarkDialog(parent=None, pipeline_config=[])
+        assert hasattr(dialog, "info_label")
+
+
+# ---------------------------------------------------------------------------
+# 測試：show_result 顯示加速倍數
+# ---------------------------------------------------------------------------
+
+class TestShowResult:
+    def should_display_speedup_text_with_x_suffix(self):
+        """show_result 後，speedup_label 的文字應包含倍數數值與 'x'。"""
+        from ui.dialogs.benchmark_dialog import BenchmarkDialog
+        stage = MagicMock()
+        dialog = BenchmarkDialog(parent=None, pipeline_config=[stage])
+        seq_result = MagicMock()
+        par_result = MagicMock()
+        dialog.show_result(seq_result, par_result, speedup=3.2)
+        call_arg = dialog.speedup_label.setText.call_args[0][0]
+        assert "3.2" in call_arg
+        assert "x" in call_arg.lower() or "X" in call_arg
+
+    def should_display_faster_in_speedup_text(self):
+        """show_result 後，speedup_label 文字應包含 'FASTER' 或 'faster'。"""
+        from ui.dialogs.benchmark_dialog import BenchmarkDialog
+        stage = MagicMock()
+        dialog = BenchmarkDialog(parent=None, pipeline_config=[stage])
+        seq_result = MagicMock()
+        par_result = MagicMock()
+        dialog.show_result(seq_result, par_result, speedup=2.5)
+        call_arg = dialog.speedup_label.setText.call_args[0][0]
+        assert "FASTER" in call_arg or "faster" in call_arg
+
+    def should_store_seq_result(self):
+        """show_result 後，seq_result 應儲存在 dialog 上。"""
+        from ui.dialogs.benchmark_dialog import BenchmarkDialog
+        stage = MagicMock()
+        dialog = BenchmarkDialog(parent=None, pipeline_config=[stage])
+        seq_result = MagicMock()
+        par_result = MagicMock()
+        dialog.show_result(seq_result, par_result, speedup=1.8)
+        assert dialog.seq_result is seq_result
+
+    def should_store_par_result(self):
+        """show_result 後，par_result 應儲存在 dialog 上。"""
+        from ui.dialogs.benchmark_dialog import BenchmarkDialog
+        stage = MagicMock()
+        dialog = BenchmarkDialog(parent=None, pipeline_config=[stage])
+        seq_result = MagicMock()
+        par_result = MagicMock()
+        dialog.show_result(seq_result, par_result, speedup=1.8)
+        assert dialog.par_result is par_result
+
+
+# ---------------------------------------------------------------------------
+# 測試：update_progress 更新進度條
+# ---------------------------------------------------------------------------
+
+class TestUpdateProgress:
+    def should_update_progress_bar_value(self):
+        """update_progress 應將進度條值更新為傳入的 value。"""
+        from ui.dialogs.benchmark_dialog import BenchmarkDialog
+        stage = MagicMock()
+        dialog = BenchmarkDialog(parent=None, pipeline_config=[stage])
+        dialog.progress_bar.setValue.reset_mock()
+        dialog.update_progress("warmup", 42)
+        dialog.progress_bar.setValue.assert_called_once_with(42)
+
+    def should_store_current_phase(self):
+        """update_progress 應儲存當前 phase 名稱。"""
+        from ui.dialogs.benchmark_dialog import BenchmarkDialog
+        stage = MagicMock()
+        dialog = BenchmarkDialog(parent=None, pipeline_config=[stage])
+        dialog.update_progress("sequential", 70)
+        assert dialog.current_phase == "sequential"

tests/unit/test_benchmarker.py

@@ -0,0 +1,282 @@
+"""
+PerformanceBenchmarker 的單元測試。
+
+測試策略：
+- BenchmarkConfig / BenchmarkResult 資料結構驗證
+- calculate_speedup() 純計算邏輯
+- run_sequential_benchmark() / run_parallel_benchmark() 透過注入的
+  inference_runner callable 進行 Mock，不需要實際硬體
+- run_full_benchmark() 整合流程
+"""
+import time
+import pytest
+from unittest.mock import MagicMock, patch
+
+from core.performance.benchmarker import (
+    BenchmarkConfig,
+    BenchmarkResult,
+    PerformanceBenchmarker,
+)
+
+
+# ---------------------------------------------------------------------------
+# 輔助：建立測試用資料結構
+# ---------------------------------------------------------------------------
+
+def make_config(**kwargs) -> BenchmarkConfig:
+    """建立測試用 BenchmarkConfig，提供合理的預設值。"""
+    defaults = dict(
+        pipeline_config=[],
+        test_duration_seconds=1.0,
+        warmup_frames=2,
+        test_input_source="test_video.mp4",
+    )
+    defaults.update(kwargs)
+    return BenchmarkConfig(**defaults)
+
+
+def make_result(mode: str = "sequential", fps: float = 30.0) -> BenchmarkResult:
+    """建立測試用 BenchmarkResult。"""
+    avg_latency_ms = (1000.0 / fps) if fps > 0 else 0.0
+    return BenchmarkResult(
+        mode=mode,
+        fps=fps,
+        avg_latency_ms=avg_latency_ms,
+        p95_latency_ms=avg_latency_ms * 1.5,
+        total_frames=int(fps * 30),
+        timestamp=time.time(),
+        device_config={"KL520": 1},
+    )
+
+
+# ---------------------------------------------------------------------------
+# 測試：BenchmarkConfig 資料結構
+# ---------------------------------------------------------------------------
+
+class TestBenchmarkConfig:
+    def should_have_default_duration_30_seconds(self):
+        """test_duration_seconds 預設值應為 30.0。"""
+        config = BenchmarkConfig(
+            pipeline_config=[],
+            test_input_source="video.mp4",
+        )
+        assert config.test_duration_seconds == 30.0
+
+    def should_have_default_warmup_50_frames(self):
+        """warmup_frames 預設值應為 50。"""
+        config = BenchmarkConfig(
+            pipeline_config=[],
+            test_input_source="video.mp4",
+        )
+        assert config.warmup_frames == 50
+
+    def should_allow_custom_duration(self):
+        """應可自訂 test_duration_seconds。"""
+        config = BenchmarkConfig(
+            pipeline_config=[],
+            test_input_source="video.mp4",
+            test_duration_seconds=10.0,
+        )
+        assert config.test_duration_seconds == 10.0
+
+
+# ---------------------------------------------------------------------------
+# 測試：BenchmarkResult 資料結構
+# ---------------------------------------------------------------------------
+
+class TestBenchmarkResult:
+    def should_store_all_required_fields(self):
+        """BenchmarkResult 應儲存所有規格要求的欄位。"""
+        ts = time.time()
+        result = BenchmarkResult(
+            mode="parallel",
+            fps=45.2,
+            avg_latency_ms=22.1,
+            p95_latency_ms=35.0,
+            total_frames=1356,
+            timestamp=ts,
+            device_config={"KL720": 2},
+        )
+        assert result.mode == "parallel"
+        assert result.fps == pytest.approx(45.2)
+        assert result.avg_latency_ms == pytest.approx(22.1)
+        assert result.p95_latency_ms == pytest.approx(35.0)
+        assert result.total_frames == 1356
+        assert result.timestamp == pytest.approx(ts)
+        assert result.device_config == {"KL720": 2}
+
+    def should_accept_sequential_mode(self):
+        """mode 欄位應接受 'sequential'。"""
+        result = make_result(mode="sequential")
+        assert result.mode == "sequential"
+
+    def should_accept_parallel_mode(self):
+        """mode 欄位應接受 'parallel'。"""
+        result = make_result(mode="parallel")
+        assert result.mode == "parallel"
+
+
+# ---------------------------------------------------------------------------
+# 測試：calculate_speedup（純計算，無外部依賴）
+# ---------------------------------------------------------------------------
+
+class TestCalculateSpeedup:
+    def should_return_ratio_of_parallel_to_sequential_fps(self):
+        """calculate_speedup 應回傳 par.fps / seq.fps。"""
+        benchmarker = PerformanceBenchmarker()
+        seq = make_result(mode="sequential", fps=20.0)
+        par = make_result(mode="parallel", fps=60.0)
+
+        speedup = benchmarker.calculate_speedup(seq, par)
+        assert speedup == pytest.approx(3.0)
+
+    def should_return_one_when_same_fps(self):
+        """相同 FPS 時 speedup 應為 1.0。"""
+        benchmarker = PerformanceBenchmarker()
+        result = make_result(fps=30.0)
+
+        speedup = benchmarker.calculate_speedup(result, result)
+        assert speedup == pytest.approx(1.0)
+
+    def should_raise_when_sequential_fps_is_zero(self):
+        """seq.fps 為 0 時應引發 ValueError，避免除以零。"""
+        benchmarker = PerformanceBenchmarker()
+        seq = make_result(fps=0.0)
+        par = make_result(fps=30.0)
+
+        with pytest.raises(ValueError):
+            benchmarker.calculate_speedup(seq, par)
+
+
+# ---------------------------------------------------------------------------
+# 測試：run_sequential_benchmark（Mock inference_runner）
+# ---------------------------------------------------------------------------
+
+class TestRunSequentialBenchmark:
+    def should_return_benchmark_result_with_sequential_mode(self):
+        """run_sequential_benchmark() 應回傳 mode='sequential' 的 BenchmarkResult。"""
+        benchmarker = PerformanceBenchmarker()
+        config = make_config(warmup_frames=1, test_duration_seconds=0.1)
+
+        # Mock inference_runner：每次呼叫模擬 10ms 推論
+        def fake_runner(frame_data):
+            time.sleep(0.01)
+            return {"result": "ok"}
+
+        result = benchmarker.run_sequential_benchmark(config, inference_runner=fake_runner)
+
+        assert isinstance(result, BenchmarkResult)
+        assert result.mode == "sequential"
+
+    def should_report_positive_fps(self):
+        """FPS 應大於 0。"""
+        benchmarker = PerformanceBenchmarker()
+        config = make_config(warmup_frames=1, test_duration_seconds=0.1)
+
+        def fake_runner(frame_data):
+            time.sleep(0.01)
+            return {}
+
+        result = benchmarker.run_sequential_benchmark(config, inference_runner=fake_runner)
+        assert result.fps > 0
+
+    def should_report_positive_latency(self):
+        """avg_latency_ms 和 p95_latency_ms 應大於 0。"""
+        benchmarker = PerformanceBenchmarker()
+        config = make_config(warmup_frames=1, test_duration_seconds=0.1)
+
+        def fake_runner(frame_data):
+            time.sleep(0.01)
+            return {}
+
+        result = benchmarker.run_sequential_benchmark(config, inference_runner=fake_runner)
+        assert result.avg_latency_ms > 0
+        assert result.p95_latency_ms > 0
+
+    def should_count_frames_excluding_warmup(self):
+        """total_frames 不應包含暖機幀數。"""
+        benchmarker = PerformanceBenchmarker()
+        call_times = []
+
+        def fake_runner(frame_data):
+            call_times.append(time.time())
+            time.sleep(0.005)
+            return {}
+
+        config = make_config(warmup_frames=3, test_duration_seconds=0.1)
+        result = benchmarker.run_sequential_benchmark(config, inference_runner=fake_runner)
+
+        # warmup 幀不計入 total_frames
+        assert result.total_frames < len(call_times)
+        assert result.total_frames > 0
+
+    def should_use_device_config_from_benchmarker(self):
+        """BenchmarkResult.device_config 應由 PerformanceBenchmarker 填寫。"""
+        benchmarker = PerformanceBenchmarker(device_config={"KL520": 1})
+        config = make_config(warmup_frames=1, test_duration_seconds=0.05)
+
+        def fake_runner(frame_data):
+            return {}
+
+        result = benchmarker.run_sequential_benchmark(config, inference_runner=fake_runner)
+        assert result.device_config == {"KL520": 1}
+
+
+# ---------------------------------------------------------------------------
+# 測試：run_parallel_benchmark（Mock inference_runner）
+# ---------------------------------------------------------------------------
+
+class TestRunParallelBenchmark:
+    def should_return_benchmark_result_with_parallel_mode(self):
+        """run_parallel_benchmark() 應回傳 mode='parallel' 的 BenchmarkResult。"""
+        benchmarker = PerformanceBenchmarker()
+        config = make_config(warmup_frames=1, test_duration_seconds=0.1)
+
+        def fake_runner(frame_data):
+            time.sleep(0.01)
+            return {}
+
+        result = benchmarker.run_parallel_benchmark(config, inference_runner=fake_runner)
+        assert isinstance(result, BenchmarkResult)
+        assert result.mode == "parallel"
+
+
+# ---------------------------------------------------------------------------
+# 測試：run_full_benchmark
+# ---------------------------------------------------------------------------
+
+class TestRunFullBenchmark:
+    def should_return_tuple_of_seq_par_speedup(self):
+        """run_full_benchmark() 應回傳 (BenchmarkResult, BenchmarkResult, float)。"""
+        benchmarker = PerformanceBenchmarker()
+        config = make_config(warmup_frames=1, test_duration_seconds=0.05)
+
+        def fast_runner(frame_data):
+            time.sleep(0.005)
+            return {}
+
+        seq_result, par_result, speedup = benchmarker.run_full_benchmark(
+            config, inference_runner=fast_runner
+        )
+
+        assert isinstance(seq_result, BenchmarkResult)
+        assert isinstance(par_result, BenchmarkResult)
+        assert isinstance(speedup, float)
+        assert seq_result.mode == "sequential"
+        assert par_result.mode == "parallel"
+
+    def should_calculate_speedup_consistently(self):
+        """speedup 應與 calculate_speedup(seq, par) 的結果一致。"""
+        benchmarker = PerformanceBenchmarker()
+        config = make_config(warmup_frames=1, test_duration_seconds=0.05)
+
+        def fake_runner(frame_data):
+            time.sleep(0.005)
+            return {}
+
+        seq_result, par_result, speedup = benchmarker.run_full_benchmark(
+            config, inference_runner=fake_runner
+        )
+
+        expected_speedup = benchmarker.calculate_speedup(seq_result, par_result)
+        assert speedup == pytest.approx(expected_speedup)

tests/unit/test_bottleneck.py

@@ -0,0 +1,43 @@
+"""
+tests/unit/test_bottleneck.py
+
+Unit tests for the BottleneckAlert dataclass.
+
+TDD: Red phase — tests written before implementation.
+"""
+import pytest
+
+from core.device.bottleneck import BottleneckAlert
+
+
+class TestBottleneckAlert:
+    def test_fields_accessible(self):
+        alert = BottleneckAlert(
+            stage_id="stage-1",
+            queue_fill_rate=0.85,
+            suggested_action="Add more Dongles to this stage",
+            severity="warning",
+        )
+        assert alert.stage_id == "stage-1"
+        assert alert.queue_fill_rate == 0.85
+        assert alert.suggested_action == "Add more Dongles to this stage"
+        assert alert.severity == "warning"
+
+    def test_severity_critical(self):
+        alert = BottleneckAlert(
+            stage_id="stage-2",
+            queue_fill_rate=0.95,
+            suggested_action="Urgent: add Dongles",
+            severity="critical",
+        )
+        assert alert.severity == "critical"
+
+    def test_dataclass_equality(self):
+        a = BottleneckAlert("s1", 0.9, "action", "warning")
+        b = BottleneckAlert("s1", 0.9, "action", "warning")
+        assert a == b
+
+    def test_dataclass_inequality(self):
+        a = BottleneckAlert("s1", 0.9, "action", "warning")
+        b = BottleneckAlert("s1", 0.5, "action", "warning")
+        assert a != b

tests/unit/test_device_management_panel.py

@@ -0,0 +1,106 @@
+"""
+tests/unit/test_device_management_panel.py
+
+Unit tests for DeviceManagementPanel QWidget.
+
+TDD: Red phase — tests written before implementation.
+Uses conftest.py Stubs for PyQt5 so no display hardware is needed.
+"""
+from unittest.mock import MagicMock, patch
+import pytest
+
+from core.device.device_manager import DeviceInfo, DeviceManager
+from ui.components.device_management_panel import DeviceManagementPanel
+
+
+# ---------------------------------------------------------------------------
+# Helpers
+# ---------------------------------------------------------------------------
+
+def _make_device_manager(devices=None):
+    """Return a DeviceManager-like mock with controllable scan_devices()."""
+    mgr = MagicMock(spec=DeviceManager)
+    if devices is None:
+        devices = [
+            DeviceInfo(
+                device_id="usb-1",
+                series="KL520",
+                product_id=0x100,
+                status="online",
+                gops=2,
+                assigned_stage=None,
+                current_fps=15.0,
+                utilization_pct=50.0,
+            )
+        ]
+    mgr.scan_devices.return_value = devices
+    mgr.get_device_statistics.return_value = {d.device_id: d for d in devices}
+    mgr.get_load_balance_recommendation.return_value = {}
+    return mgr
+
+
+# ---------------------------------------------------------------------------
+# Panel instantiation
+# ---------------------------------------------------------------------------
+
+class TestDeviceManagementPanelInit:
+    def test_panel_creates_without_error(self):
+        mgr = _make_device_manager()
+        panel = DeviceManagementPanel(device_manager=mgr)
+        assert panel is not None
+
+    def test_panel_has_auto_balance_button(self):
+        mgr = _make_device_manager()
+        panel = DeviceManagementPanel(device_manager=mgr)
+        # auto_balance_button must exist
+        assert hasattr(panel, "auto_balance_button")
+
+    def test_auto_balance_button_text(self):
+        mgr = _make_device_manager()
+        panel = DeviceManagementPanel(device_manager=mgr)
+        assert panel.auto_balance_button._text == "Auto Balance"
+
+
+# ---------------------------------------------------------------------------
+# refresh()
+# ---------------------------------------------------------------------------
+
+class TestDeviceManagementPanelRefresh:
+    def test_refresh_calls_scan_devices(self):
+        mgr = _make_device_manager()
+        panel = DeviceManagementPanel(device_manager=mgr)
+        mgr.scan_devices.reset_mock()
+        panel.refresh()
+        mgr.scan_devices.assert_called_once()
+
+    def test_refresh_updates_known_devices(self):
+        mgr = _make_device_manager()
+        panel = DeviceManagementPanel(device_manager=mgr)
+        panel.refresh()
+        # After refresh, panel should have device data accessible
+        assert len(panel._devices) == 1
+        assert panel._devices[0].device_id == "usb-1"
+
+    def test_refresh_with_no_devices_sets_empty_list(self):
+        mgr = _make_device_manager(devices=[])
+        panel = DeviceManagementPanel(device_manager=mgr)
+        panel.refresh()
+        assert panel._devices == []
+
+
+# ---------------------------------------------------------------------------
+# set_auto_refresh()
+# ---------------------------------------------------------------------------
+
+class TestSetAutoRefresh:
+    def test_set_auto_refresh_stores_interval(self):
+        mgr = _make_device_manager()
+        panel = DeviceManagementPanel(device_manager=mgr)
+        panel.set_auto_refresh(interval_ms=3000)
+        assert panel._auto_refresh_interval_ms == 3000
+
+    def test_set_auto_refresh_default_interval(self):
+        mgr = _make_device_manager()
+        panel = DeviceManagementPanel(device_manager=mgr)
+        panel.set_auto_refresh()
+        assert panel._auto_refresh_interval_ms == 2000

tests/unit/test_device_manager.py

@@ -0,0 +1,291 @@
+"""
+tests/unit/test_device_manager.py
+
+Unit tests for DeviceManager, DeviceInfo, DeviceHealth.
+
+TDD: Red phase — tests written before implementation.
+"""
+from unittest.mock import MagicMock
+import pytest
+
+from core.device.device_manager import DeviceInfo, DeviceHealth, DeviceManager
+
+
+# ---------------------------------------------------------------------------
+# Fixtures
+# ---------------------------------------------------------------------------
+
+def _make_mock_kp_api(devices):
+    """Build a minimal kp API mock whose scan_devices() returns a descriptor list."""
+    descriptor_list = MagicMock()
+    descriptor_list.device_descriptor_number = len(devices)
+    mock_descs = []
+    for d in devices:
+        desc = MagicMock()
+        desc.usb_port_id = d["port_id"]
+        desc.product_id = d["product_id"]
+        desc.kn_number = d.get("kn_number", 0)
+        mock_descs.append(desc)
+    descriptor_list.device_descriptor_list = mock_descs
+    kp_api = MagicMock()
+    kp_api.core.scan_devices.return_value = descriptor_list
+    return kp_api
+
+
+@pytest.fixture
+def two_device_kp():
+    """Mock kp API returning one KL520 and one KL720."""
+    return _make_mock_kp_api([
+        {"port_id": 1, "product_id": 0x100},   # KL520
+        {"port_id": 2, "product_id": 0x720},   # KL720
+    ])
+
+
+@pytest.fixture
+def empty_kp():
+    """Mock kp API returning no devices."""
+    descriptor_list = MagicMock()
+    descriptor_list.device_descriptor_number = 0
+    descriptor_list.device_descriptor_list = []
+    kp_api = MagicMock()
+    kp_api.core.scan_devices.return_value = descriptor_list
+    return kp_api
+
+
+# ---------------------------------------------------------------------------
+# DeviceInfo dataclass
+# ---------------------------------------------------------------------------
+
+class TestDeviceInfo:
+    def test_fields_accessible(self):
+        info = DeviceInfo(
+            device_id="usb-1",
+            series="KL520",
+            product_id=0x100,
+            status="online",
+            gops=2,
+            assigned_stage=None,
+            current_fps=0.0,
+            utilization_pct=0.0,
+        )
+        assert info.device_id == "usb-1"
+        assert info.series == "KL520"
+        assert info.product_id == 0x100
+        assert info.status == "online"
+        assert info.gops == 2
+        assert info.assigned_stage is None
+        assert info.current_fps == 0.0
+        assert info.utilization_pct == 0.0
+
+
+# ---------------------------------------------------------------------------
+# DeviceHealth dataclass
+# ---------------------------------------------------------------------------
+
+class TestDeviceHealth:
+    def test_fields_accessible(self):
+        health = DeviceHealth(
+            device_id="usb-1",
+            temperature_celsius=None,
+            error_count=0,
+            last_error=None,
+            uptime_seconds=120.0,
+        )
+        assert health.device_id == "usb-1"
+        assert health.temperature_celsius is None
+        assert health.error_count == 0
+        assert health.last_error is None
+        assert health.uptime_seconds == 120.0
+
+
+# ---------------------------------------------------------------------------
+# DeviceManager.scan_devices
+# ---------------------------------------------------------------------------
+
+class TestScanDevices:
+    def test_returns_list_of_device_info(self, two_device_kp):
+        mgr = DeviceManager(kp_api=two_device_kp)
+        devices = mgr.scan_devices()
+        assert isinstance(devices, list)
+        assert len(devices) == 2
+        assert all(isinstance(d, DeviceInfo) for d in devices)
+
+    def test_kl520_properties(self, two_device_kp):
+        mgr = DeviceManager(kp_api=two_device_kp)
+        devices = mgr.scan_devices()
+        kl520 = next(d for d in devices if d.series == "KL520")
+        assert kl520.product_id == 0x100
+        assert kl520.gops == 2
+        assert kl520.status == "online"
+
+    def test_kl720_properties(self, two_device_kp):
+        mgr = DeviceManager(kp_api=two_device_kp)
+        devices = mgr.scan_devices()
+        kl720 = next(d for d in devices if d.series == "KL720")
+        assert kl720.product_id == 0x720
+        assert kl720.gops == 28
+        assert kl720.status == "online"
+
+    def test_empty_returns_empty_list(self, empty_kp):
+        mgr = DeviceManager(kp_api=empty_kp)
+        devices = mgr.scan_devices()
+        assert devices == []
+
+    def test_device_id_uses_port(self, two_device_kp):
+        mgr = DeviceManager(kp_api=two_device_kp)
+        devices = mgr.scan_devices()
+        ids = {d.device_id for d in devices}
+        assert "usb-1" in ids
+        assert "usb-2" in ids
+
+
+# ---------------------------------------------------------------------------
+# DeviceManager.assign_device / unassign_device
+# ---------------------------------------------------------------------------
+
+class TestAssignDevice:
+    def test_assign_online_device_returns_true(self, two_device_kp):
+        mgr = DeviceManager(kp_api=two_device_kp)
+        mgr.scan_devices()
+        result = mgr.assign_device("usb-1", "stage-A")
+        assert result is True
+
+    def test_assigned_device_shows_stage(self, two_device_kp):
+        mgr = DeviceManager(kp_api=two_device_kp)
+        mgr.scan_devices()
+        mgr.assign_device("usb-1", "stage-A")
+        devices = mgr.get_device_statistics()
+        assert devices["usb-1"].assigned_stage == "stage-A"
+
+    def test_assign_already_assigned_device_returns_false(self, two_device_kp):
+        mgr = DeviceManager(kp_api=two_device_kp)
+        mgr.scan_devices()
+        mgr.assign_device("usb-1", "stage-A")
+        result = mgr.assign_device("usb-1", "stage-B")
+        assert result is False
+
+    def test_assign_unknown_device_returns_false(self, two_device_kp):
+        mgr = DeviceManager(kp_api=two_device_kp)
+        mgr.scan_devices()
+        result = mgr.assign_device("usb-99", "stage-A")
+        assert result is False
+
+    def test_unassign_frees_device(self, two_device_kp):
+        mgr = DeviceManager(kp_api=two_device_kp)
+        mgr.scan_devices()
+        mgr.assign_device("usb-1", "stage-A")
+        result = mgr.unassign_device("usb-1")
+        assert result is True
+        devices = mgr.get_device_statistics()
+        assert devices["usb-1"].assigned_stage is None
+
+    def test_unassign_unknown_device_returns_false(self, two_device_kp):
+        mgr = DeviceManager(kp_api=two_device_kp)
+        mgr.scan_devices()
+        result = mgr.unassign_device("usb-99")
+        assert result is False
+
+    def test_reassign_after_unassign_succeeds(self, two_device_kp):
+        mgr = DeviceManager(kp_api=two_device_kp)
+        mgr.scan_devices()
+        mgr.assign_device("usb-1", "stage-A")
+        mgr.unassign_device("usb-1")
+        result = mgr.assign_device("usb-1", "stage-B")
+        assert result is True
+
+    def test_should_reject_assignment_for_offline_device(self):
+        """assign_device returns False when the device status is offline."""
+        kp_api = _make_mock_kp_api([{"port_id": 5, "product_id": 0x100}])
+        mgr = DeviceManager(kp_api=kp_api)
+        mgr.scan_devices()
+        mgr._devices["usb-5"].status = "offline"
+        result = mgr.assign_device("usb-5", "stage-A")
+        assert result is False
+
+    def test_should_allow_reassignment_to_same_stage(self, two_device_kp):
+        """Assigning a device to the same stage twice is idempotent and returns True."""
+        mgr = DeviceManager(kp_api=two_device_kp)
+        mgr.scan_devices()
+        mgr.assign_device("usb-1", "stage-A")
+        result = mgr.assign_device("usb-1", "stage-A")
+        assert result is True
+
+    def test_should_reject_reassignment_to_different_stage(self, two_device_kp):
+        """Assigning a device already assigned to a different stage returns False."""
+        mgr = DeviceManager(kp_api=two_device_kp)
+        mgr.scan_devices()
+        mgr.assign_device("usb-1", "stage-A")
+        result = mgr.assign_device("usb-1", "stage-B")
+        assert result is False
+
+
+# ---------------------------------------------------------------------------
+# DeviceManager.get_load_balance_recommendation
+# ---------------------------------------------------------------------------
+
+class TestLoadBalanceRecommendation:
+    def test_returns_dict_mapping_stage_to_device(self, two_device_kp):
+        mgr = DeviceManager(kp_api=two_device_kp)
+        mgr.scan_devices()
+        rec = mgr.get_load_balance_recommendation(["stage-A", "stage-B"])
+        assert isinstance(rec, dict)
+        assert "stage-A" in rec
+        assert "stage-B" in rec
+
+    def test_high_gops_assigned_to_first_stage(self, two_device_kp):
+        """KL720 (28 GOPS) should be recommended for the first stage."""
+        mgr = DeviceManager(kp_api=two_device_kp)
+        mgr.scan_devices()
+        rec = mgr.get_load_balance_recommendation(["stage-A", "stage-B"])
+        # The device recommended for stage-A should be the higher-gops one
+        stats = mgr.get_device_statistics()
+        first_device_id = rec["stage-A"]
+        assert stats[first_device_id].gops == 28   # KL720
+
+    def test_recommendation_with_more_stages_than_devices(self, two_device_kp):
+        """Extra stages beyond available devices map to empty string."""
+        mgr = DeviceManager(kp_api=two_device_kp)
+        mgr.scan_devices()
+        rec = mgr.get_load_balance_recommendation(["s1", "s2", "s3"])
+        assert rec["s3"] == ""
+
+    def test_recommendation_with_no_devices(self, empty_kp):
+        mgr = DeviceManager(kp_api=empty_kp)
+        mgr.scan_devices()
+        rec = mgr.get_load_balance_recommendation(["stage-A"])
+        assert rec["stage-A"] == ""
+
+
+# ---------------------------------------------------------------------------
+# DeviceManager.get_device_health
+# ---------------------------------------------------------------------------
+
+class TestGetDeviceHealth:
+    def test_returns_device_health(self, two_device_kp):
+        mgr = DeviceManager(kp_api=two_device_kp)
+        mgr.scan_devices()
+        health = mgr.get_device_health("usb-1")
+        assert isinstance(health, DeviceHealth)
+        assert health.device_id == "usb-1"
+        assert health.temperature_celsius is None   # SDK does not support it
+        assert health.error_count == 0
+
+
+# ---------------------------------------------------------------------------
+# DeviceManager.get_device_statistics
+# ---------------------------------------------------------------------------
+
+class TestGetDeviceStatistics:
+    def test_returns_all_known_devices(self, two_device_kp):
+        mgr = DeviceManager(kp_api=two_device_kp)
+        mgr.scan_devices()
+        stats = mgr.get_device_statistics()
+        assert isinstance(stats, dict)
+        assert "usb-1" in stats
+        assert "usb-2" in stats
+
+    def test_values_are_device_info(self, two_device_kp):
+        mgr = DeviceManager(kp_api=two_device_kp)
+        mgr.scan_devices()
+        stats = mgr.get_device_statistics()
+        assert all(isinstance(v, DeviceInfo) for v in stats.values())

tests/unit/test_export_report_dialog.py

@@ -0,0 +1,179 @@
+"""
+tests/unit/test_export_report_dialog.py — ExportReportDialog 單元測試。
+
+在無 PyQt5 環境下，使用 conftest.py 中的 Stub 進行測試。
+"""
+from unittest.mock import MagicMock, patch
+import pytest
+
+from core.performance.benchmarker import BenchmarkResult
+from core.performance.report_exporter import DeviceSummary, ReportData
+from ui.dialogs.export_report_dialog import ExportReportDialog
+
+
+# ---------------------------------------------------------------------------
+# Fixtures
+# ---------------------------------------------------------------------------
+
+def _make_benchmark_result(mode: str = "sequential", fps: float = 14.2) -> BenchmarkResult:
+    return BenchmarkResult(
+        mode=mode,
+        fps=fps,
+        avg_latency_ms=70.4,
+        p95_latency_ms=95.0,
+        total_frames=426,
+        timestamp=1743856222.0,
+        device_config={"KL720": 1},
+        id=f"benchmark_20260405_143022_{mode}",
+    )
+
+
+def _make_dialog(
+    benchmarker=None,
+    history=None,
+    device_manager=None,
+    dashboard=None,
+) -> ExportReportDialog:
+    """建立 ExportReportDialog，所有依賴預設為 MagicMock。"""
+    if benchmarker is None:
+        benchmarker = MagicMock()
+        benchmarker.history = []
+    if history is None:
+        history = MagicMock()
+        history.get_history.return_value = []
+    if device_manager is None:
+        device_manager = MagicMock()
+        device_manager.scan_devices.return_value = []
+    if dashboard is None:
+        dashboard = MagicMock()
+
+    return ExportReportDialog(
+        parent=None,
+        benchmarker=benchmarker,
+        history=history,
+        device_manager=device_manager,
+        dashboard=dashboard,
+    )
+
+
+# ---------------------------------------------------------------------------
+# 基本建立
+# ---------------------------------------------------------------------------
+
+class TestExportReportDialogCreation:
+    def test_dialog_can_be_created(self):
+        """ExportReportDialog 應可正常建立"""
+        dialog = _make_dialog()
+        assert dialog is not None
+
+    def test_dialog_is_instance_of_qdialog(self):
+        """ExportReportDialog 應繼承自 QDialog（或其 Stub）"""
+        from PyQt5.QtWidgets import QDialog
+        dialog = _make_dialog()
+        assert isinstance(dialog, QDialog)
+
+    def test_dialog_default_format_is_pdf(self):
+        """格式選擇預設應為 PDF"""
+        dialog = _make_dialog()
+        assert dialog._selected_format == "pdf"
+
+
+# ---------------------------------------------------------------------------
+# _collect_report_data
+# ---------------------------------------------------------------------------
+
+class TestCollectReportData:
+    def test_returns_report_data_instance(self):
+        """_collect_report_data() 應回傳 ReportData 型別"""
+        dialog = _make_dialog()
+        result = dialog._collect_report_data()
+        assert isinstance(result, ReportData)
+
+    def test_uses_history_records(self):
+        """_collect_report_data() 應使用 history.get_history() 的結果"""
+        history = MagicMock()
+        records = [_make_benchmark_result("parallel")]
+        history.get_history.return_value = records
+
+        dialog = _make_dialog(history=history)
+        result = dialog._collect_report_data()
+
+        history.get_history.assert_called_once()
+        assert result.history_records == records
+
+    def test_uses_device_manager_scan(self):
+        """_collect_report_data() 應呼叫 device_manager.scan_devices()"""
+        device_manager = MagicMock()
+        device_manager.scan_devices.return_value = []
+
+        dialog = _make_dialog(device_manager=device_manager)
+        dialog._collect_report_data()
+
+        device_manager.scan_devices.assert_called_once()
+
+    def test_handles_history_failure_gracefully(self):
+        """history.get_history() 拋出例外時，應回傳空的 history_records"""
+        history = MagicMock()
+        history.get_history.side_effect = Exception("history error")
+
+        dialog = _make_dialog(history=history)
+        result = dialog._collect_report_data()
+
+        assert result.history_records == []
+
+    def test_handles_device_manager_failure_gracefully(self):
+        """device_manager.scan_devices() 拋出例外時，devices 應為空列表"""
+        device_manager = MagicMock()
+        device_manager.scan_devices.side_effect = Exception("device error")
+
+        dialog = _make_dialog(device_manager=device_manager)
+        result = dialog._collect_report_data()
+
+        assert result.devices == []
+
+    def test_uses_latest_benchmark_from_history_as_parallel_result(self):
+        """benchmarker.history 有記錄時，應使用最新一筆作為 parallel_result"""
+        benchmarker = MagicMock()
+        latest = _make_benchmark_result("parallel", fps=45.6)
+        benchmarker.history = [_make_benchmark_result("sequential"), latest]
+
+        dialog = _make_dialog(benchmarker=benchmarker)
+        result = dialog._collect_report_data()
+
+        # parallel_result 應為最新一筆（index -1）
+        assert result.parallel_result == latest
+
+    def test_parallel_result_is_none_when_history_empty(self):
+        """benchmarker.history 為空時，parallel_result 應為 None"""
+        benchmarker = MagicMock()
+        benchmarker.history = []
+
+        dialog = _make_dialog(benchmarker=benchmarker)
+        result = dialog._collect_report_data()
+
+        assert result.parallel_result is None
+
+    def test_chart_image_bytes_is_none(self):
+        """chart_image_bytes 應為 None（截圖整合留未來）"""
+        dialog = _make_dialog()
+        result = dialog._collect_report_data()
+        assert result.chart_image_bytes is None
+
+
+# ---------------------------------------------------------------------------
+# 格式選擇
+# ---------------------------------------------------------------------------
+
+class TestFormatSelection:
+    def test_set_format_to_csv(self):
+        """可將格式設為 CSV"""
+        dialog = _make_dialog()
+        dialog._set_format("csv")
+        assert dialog._selected_format == "csv"
+
+    def test_set_format_to_pdf(self):
+        """可將格式設回 PDF"""
+        dialog = _make_dialog()
+        dialog._set_format("csv")
+        dialog._set_format("pdf")
+        assert dialog._selected_format == "pdf"

tests/unit/test_history.py

@@ -0,0 +1,224 @@
+"""
+PerformanceHistory 的單元測試。
+
+測試覆蓋：
+- 記錄 BenchmarkResult
+- 依條件查詢歷史記錄（limit / mode 過濾）
+- 回歸比較報告
+- 持久化（JSON 讀寫）
+"""
+import json
+import os
+import time
+import tempfile
+import pytest
+
+from core.performance.benchmarker import BenchmarkResult
+from core.performance.history import PerformanceHistory
+
+
+# ---------------------------------------------------------------------------
+# 輔助函式
+# ---------------------------------------------------------------------------
+
+def make_result(mode: str = "sequential", fps: float = 30.0, avg_latency_ms: float = 33.3,
+                p95_latency_ms: float = 50.0, total_frames: int = 900) -> BenchmarkResult:
+    """建立測試用的 BenchmarkResult。"""
+    return BenchmarkResult(
+        mode=mode,
+        fps=fps,
+        avg_latency_ms=avg_latency_ms,
+        p95_latency_ms=p95_latency_ms,
+        total_frames=total_frames,
+        timestamp=time.time(),
+        device_config={"KL520": 1},
+    )
+
+
+# ---------------------------------------------------------------------------
+# Fixture
+# ---------------------------------------------------------------------------
+
+@pytest.fixture
+def tmp_history(tmp_path):
+    """回傳一個使用暫存路徑的 PerformanceHistory 實例。"""
+    storage_path = str(tmp_path / "benchmark_history.json")
+    return PerformanceHistory(storage_path=storage_path)
+
+
+# ---------------------------------------------------------------------------
+# 測試：基本記錄功能
+# ---------------------------------------------------------------------------
+
+class TestRecord:
+    def should_record_result_to_storage(self, tmp_history):
+        """record() 應將結果寫入 JSON 儲存。"""
+        result = make_result()
+        tmp_history.record(result)
+
+        records = tmp_history.get_history()
+        assert len(records) == 1
+
+    def should_persist_across_instances(self, tmp_path):
+        """record() 應將資料持久化，重新建立實例後仍可讀取。"""
+        storage_path = str(tmp_path / "benchmark_history.json")
+        history1 = PerformanceHistory(storage_path=storage_path)
+        result = make_result(fps=42.0)
+        history1.record(result)
+
+        history2 = PerformanceHistory(storage_path=storage_path)
+        records = history2.get_history()
+        assert len(records) == 1
+        assert records[0].fps == 42.0
+
+    def should_assign_unique_id_to_each_record(self, tmp_history):
+        """每筆記錄應有唯一的 id。"""
+        tmp_history.record(make_result())
+        time.sleep(0.01)
+        tmp_history.record(make_result())
+
+        records = tmp_history.get_history()
+        ids = [r.id for r in records]
+        assert len(set(ids)) == 2
+
+    def should_store_all_benchmark_fields(self, tmp_history):
+        """record() 應完整儲存所有欄位。"""
+        result = make_result(
+            mode="parallel",
+            fps=60.5,
+            avg_latency_ms=16.5,
+            p95_latency_ms=25.0,
+            total_frames=1815,
+        )
+        tmp_history.record(result)
+
+        saved = tmp_history.get_history()[0]
+        assert saved.mode == "parallel"
+        assert saved.fps == pytest.approx(60.5)
+        assert saved.avg_latency_ms == pytest.approx(16.5)
+        assert saved.p95_latency_ms == pytest.approx(25.0)
+        assert saved.total_frames == 1815
+
+
+# ---------------------------------------------------------------------------
+# 測試：get_history 查詢
+# ---------------------------------------------------------------------------
+
+class TestGetHistory:
+    def should_return_records_in_reverse_chronological_order(self, tmp_history):
+        """get_history() 應以最新優先的順序回傳記錄。"""
+        base_time = 1000000.0
+        for i, fps in enumerate([10.0, 20.0, 30.0]):
+            result = make_result(fps=fps)
+            result.timestamp = base_time + i  # 確保時間戳遞增
+            tmp_history.record(result)
+
+        records = tmp_history.get_history()
+        fps_values = [r.fps for r in records]
+        # 最新優先：fps=30 (timestamp最大) 排第一
+        assert fps_values == [30.0, 20.0, 10.0]
+
+    def should_respect_limit_parameter(self, tmp_history):
+        """get_history(limit=N) 應只回傳最新的 N 筆記錄。"""
+        for i in range(5):
+            tmp_history.record(make_result(fps=float(i + 1)))
+
+        records = tmp_history.get_history(limit=3)
+        assert len(records) == 3
+
+    def should_filter_by_mode(self, tmp_history):
+        """get_history(mode='parallel') 應只回傳 parallel 模式的記錄。"""
+        tmp_history.record(make_result(mode="sequential"))
+        tmp_history.record(make_result(mode="parallel"))
+        tmp_history.record(make_result(mode="sequential"))
+
+        records = tmp_history.get_history(mode="parallel")
+        assert len(records) == 1
+        assert records[0].mode == "parallel"
+
+    def should_return_empty_list_when_no_records(self, tmp_history):
+        """空儲存應回傳空列表。"""
+        records = tmp_history.get_history()
+        assert records == []
+
+    def should_apply_limit_after_mode_filter(self, tmp_history):
+        """limit 應在 mode 過濾之後套用。"""
+        for _ in range(4):
+            tmp_history.record(make_result(mode="sequential"))
+        for _ in range(4):
+            tmp_history.record(make_result(mode="parallel"))
+
+        records = tmp_history.get_history(limit=2, mode="parallel")
+        assert len(records) == 2
+        assert all(r.mode == "parallel" for r in records)
+
+
+# ---------------------------------------------------------------------------
+# 測試：回歸報告
+# ---------------------------------------------------------------------------
+
+class TestGetRegressionReport:
+    def should_report_fps_improvement(self, tmp_history):
+        """get_regression_report() 應計算 FPS 改善百分比。"""
+        baseline = make_result(fps=30.0, avg_latency_ms=33.3, p95_latency_ms=50.0)
+        tmp_history.record(baseline)
+        baseline_id = tmp_history.get_history()[0].id
+
+        compare = make_result(fps=45.0, avg_latency_ms=22.2, p95_latency_ms=35.0)
+        tmp_history.record(compare)
+        compare_id = tmp_history.get_history()[0].id  # 最新一筆
+
+        report = tmp_history.get_regression_report(baseline_id, compare_id)
+
+        assert "fps_change_pct" in report
+        assert report["fps_change_pct"] == pytest.approx(50.0, rel=1e-2)
+
+    def should_report_latency_change(self, tmp_history):
+        """get_regression_report() 應計算延遲變化百分比。"""
+        baseline = make_result(avg_latency_ms=40.0, p95_latency_ms=60.0)
+        tmp_history.record(baseline)
+        baseline_id = tmp_history.get_history()[0].id
+
+        compare = make_result(avg_latency_ms=20.0, p95_latency_ms=30.0)
+        tmp_history.record(compare)
+        compare_id = tmp_history.get_history()[0].id
+
+        report = tmp_history.get_regression_report(baseline_id, compare_id)
+
+        assert "avg_latency_change_pct" in report
+        assert report["avg_latency_change_pct"] == pytest.approx(-50.0, rel=1e-2)
+
+    def should_raise_error_for_invalid_id(self, tmp_history):
+        """無效的 id 應引發 ValueError。"""
+        with pytest.raises(ValueError):
+            tmp_history.get_regression_report("nonexistent_baseline", "nonexistent_compare")
+
+
+# ---------------------------------------------------------------------------
+# 測試：JSON 檔案格式
+# ---------------------------------------------------------------------------
+
+class TestStorageFormat:
+    def should_produce_valid_json_file(self, tmp_path):
+        """儲存的檔案應為合法的 JSON 並符合規格格式。"""
+        storage_path = str(tmp_path / "benchmark_history.json")
+        history = PerformanceHistory(storage_path=storage_path)
+        history.record(make_result(mode="parallel", fps=45.2))
+
+        with open(storage_path, "r", encoding="utf-8") as f:
+            data = json.load(f)
+
+        assert "records" in data
+        assert len(data["records"]) == 1
+        record = data["records"][0]
+        for field in ("id", "mode", "fps", "avg_latency_ms", "p95_latency_ms",
+                      "total_frames", "timestamp", "device_config"):
+            assert field in record, f"缺少欄位：{field}"
+
+    def should_create_parent_directory_if_not_exists(self, tmp_path):
+        """若父目錄不存在，應自動建立。"""
+        storage_path = str(tmp_path / "deep" / "nested" / "history.json")
+        history = PerformanceHistory(storage_path=storage_path)
+        history.record(make_result())
+
+        assert os.path.exists(storage_path)

tests/unit/test_optimization_engine.py

@@ -0,0 +1,364 @@
+"""
+tests/unit/test_optimization_engine.py
+
+TDD Phase 3.3.1 — OptimizationEngine 單元測試。
+
+覆蓋範圍：
+- analyze_pipeline 的三條優化規則（含邊界值測試）
+- predict_performance 計算邏輯
+- apply_suggestion 對 rebalance_devices 呼叫 device_manager
+"""
+import pytest
+from unittest.mock import MagicMock, call
+
+from core.optimization.engine import OptimizationEngine, OptimizationSuggestion
+from core.device.device_manager import DeviceInfo
+
+
+# ---------------------------------------------------------------------------
+# Fixtures
+# ---------------------------------------------------------------------------
+
+@pytest.fixture
+def engine():
+    return OptimizationEngine()
+
+
+def _make_stats(
+    stage_fill_rates=None,
+    stage_avg_times=None,
+    device_utilizations=None,
+):
+    """建立 analyze_pipeline 接受的 stats 字典。"""
+    stage_fill_rates = stage_fill_rates or {}
+    stage_avg_times = stage_avg_times or {}
+    device_utilizations = device_utilizations or {}
+
+    stages = {}
+    all_stage_ids = set(stage_fill_rates) | set(stage_avg_times)
+    for sid in all_stage_ids:
+        stages[sid] = {
+            "queue_fill_rate": stage_fill_rates.get(sid, 0.0),
+            "avg_processing_time": stage_avg_times.get(sid, 10.0),
+            "fps": 30.0,
+        }
+
+    devices = {}
+    for did, util in device_utilizations.items():
+        devices[did] = {
+            "utilization_pct": util,
+            "series": "KL720",
+        }
+
+    return {"stages": stages, "devices": devices}
+
+
+def _make_device_info(device_id="usb-1", gops=28, series="KL720"):
+    return DeviceInfo(
+        device_id=device_id,
+        series=series,
+        product_id=0x720,
+        status="online",
+        gops=gops,
+        assigned_stage=None,
+        current_fps=0.0,
+        utilization_pct=0.0,
+    )
+
+
+# ---------------------------------------------------------------------------
+# analyze_pipeline — rule 1: rebalance_devices
+# ---------------------------------------------------------------------------
+
+class TestAnalyzePipelineRebalanceDevices:
+    """queue_fill_rate > 0.70 應觸發 rebalance_devices 建議。"""
+
+    def test_should_suggest_rebalance_when_fill_rate_above_threshold(self, engine):
+        stats = _make_stats(stage_fill_rates={"stage_0": 0.71})
+        suggestions = engine.analyze_pipeline(stats)
+        types = [s.type for s in suggestions]
+        assert "rebalance_devices" in types
+
+    def test_should_not_suggest_rebalance_when_fill_rate_at_threshold(self, engine):
+        """恰好等於 0.70 不觸發（需 > 0.70）。"""
+        stats = _make_stats(stage_fill_rates={"stage_0": 0.70})
+        suggestions = engine.analyze_pipeline(stats)
+        types = [s.type for s in suggestions]
+        assert "rebalance_devices" not in types
+
+    def test_should_not_suggest_rebalance_when_fill_rate_below_threshold(self, engine):
+        stats = _make_stats(stage_fill_rates={"stage_0": 0.50})
+        suggestions = engine.analyze_pipeline(stats)
+        types = [s.type for s in suggestions]
+        assert "rebalance_devices" not in types
+
+    def test_rebalance_suggestion_has_required_fields(self, engine):
+        stats = _make_stats(stage_fill_rates={"stage_0": 0.85})
+        suggestions = engine.analyze_pipeline(stats)
+        rebalance = next(s for s in suggestions if s.type == "rebalance_devices")
+        assert rebalance.suggestion_id
+        assert rebalance.description
+        assert 0.0 <= rebalance.estimated_improvement_pct
+        assert rebalance.confidence in ("high", "medium", "low")
+        assert isinstance(rebalance.action_params, dict)
+
+    def test_rebalance_action_params_includes_stage_id(self, engine):
+        stats = _make_stats(stage_fill_rates={"stage_0": 0.85})
+        suggestions = engine.analyze_pipeline(stats)
+        rebalance = next(s for s in suggestions if s.type == "rebalance_devices")
+        assert "stage_id" in rebalance.action_params
+
+
+# ---------------------------------------------------------------------------
+# analyze_pipeline — rule 2: adjust_queue
+# ---------------------------------------------------------------------------
+
+class TestAnalyzePipelineAdjustQueue:
+    """avg_processing_time 最大/最小比值 > 2.0 應觸發 adjust_queue 建議。"""
+
+    def test_should_suggest_adjust_queue_when_ratio_above_threshold(self, engine):
+        stats = _make_stats(
+            stage_avg_times={"stage_0": 10.0, "stage_1": 25.0}
+        )
+        suggestions = engine.analyze_pipeline(stats)
+        types = [s.type for s in suggestions]
+        assert "adjust_queue" in types
+
+    def test_should_not_suggest_adjust_queue_when_ratio_at_threshold(self, engine):
+        """恰好等於 2.0 不觸發（需 > 2.0）。"""
+        stats = _make_stats(
+            stage_avg_times={"stage_0": 10.0, "stage_1": 20.0}
+        )
+        suggestions = engine.analyze_pipeline(stats)
+        types = [s.type for s in suggestions]
+        assert "adjust_queue" not in types
+
+    def test_should_not_suggest_adjust_queue_when_ratio_below_threshold(self, engine):
+        stats = _make_stats(
+            stage_avg_times={"stage_0": 10.0, "stage_1": 15.0}
+        )
+        suggestions = engine.analyze_pipeline(stats)
+        types = [s.type for s in suggestions]
+        assert "adjust_queue" not in types
+
+    def test_should_not_suggest_adjust_queue_with_single_stage(self, engine):
+        """只有一個 Stage 時無法計算比值，不觸發。"""
+        stats = _make_stats(stage_avg_times={"stage_0": 100.0})
+        suggestions = engine.analyze_pipeline(stats)
+        types = [s.type for s in suggestions]
+        assert "adjust_queue" not in types
+
+    def test_adjust_queue_suggestion_has_required_fields(self, engine):
+        stats = _make_stats(
+            stage_avg_times={"stage_0": 10.0, "stage_1": 25.0}
+        )
+        suggestions = engine.analyze_pipeline(stats)
+        adj = next(s for s in suggestions if s.type == "adjust_queue")
+        assert adj.suggestion_id
+        assert adj.description
+        assert adj.confidence in ("high", "medium", "low")
+        assert isinstance(adj.action_params, dict)
+
+    def should_not_suggest_adjust_queue_when_min_processing_time_is_zero(self, engine):
+        # stage avg_processing_time 為 0 時，比值計算無意義，不應觸發規則
+        stats = _make_stats(stage_avg_times={"stage_0": 0.0, "stage_1": 50.0})
+        suggestions = engine.analyze_pipeline(stats)
+        adjust = [s for s in suggestions if s.type == "adjust_queue"]
+        assert len(adjust) == 0
+
+
+# ---------------------------------------------------------------------------
+# analyze_pipeline — rule 3: add_devices
+# ---------------------------------------------------------------------------
+
+class TestAnalyzePipelineAddDevices:
+    """所有 Dongle 使用率 > 85% 應觸發 add_devices 建議。"""
+
+    def test_should_suggest_add_devices_when_all_above_threshold(self, engine):
+        stats = _make_stats(
+            device_utilizations={"usb-1": 86.0, "usb-2": 90.0}
+        )
+        suggestions = engine.analyze_pipeline(stats)
+        types = [s.type for s in suggestions]
+        assert "add_devices" in types
+
+    def test_should_not_suggest_add_devices_when_one_device_below_threshold(self, engine):
+        stats = _make_stats(
+            device_utilizations={"usb-1": 90.0, "usb-2": 80.0}
+        )
+        suggestions = engine.analyze_pipeline(stats)
+        types = [s.type for s in suggestions]
+        assert "add_devices" not in types
+
+    def test_should_not_suggest_add_devices_when_all_at_threshold(self, engine):
+        """恰好等於 85% 不觸發（需 > 85%）。"""
+        stats = _make_stats(
+            device_utilizations={"usb-1": 85.0, "usb-2": 85.0}
+        )
+        suggestions = engine.analyze_pipeline(stats)
+        types = [s.type for s in suggestions]
+        assert "add_devices" not in types
+
+    def test_should_not_suggest_add_devices_when_no_devices(self, engine):
+        """沒有裝置資訊時不觸發。"""
+        stats = _make_stats(device_utilizations={})
+        suggestions = engine.analyze_pipeline(stats)
+        types = [s.type for s in suggestions]
+        assert "add_devices" not in types
+
+    def test_add_devices_suggestion_has_required_fields(self, engine):
+        stats = _make_stats(
+            device_utilizations={"usb-1": 90.0, "usb-2": 92.0}
+        )
+        suggestions = engine.analyze_pipeline(stats)
+        add = next(s for s in suggestions if s.type == "add_devices")
+        assert add.suggestion_id
+        assert add.description
+        assert add.confidence in ("high", "medium", "low")
+
+
+# ---------------------------------------------------------------------------
+# analyze_pipeline — empty stats
+# ---------------------------------------------------------------------------
+
+class TestAnalyzePipelineEmptyStats:
+    def test_should_return_empty_list_when_stats_empty(self, engine):
+        suggestions = engine.analyze_pipeline({"stages": {}, "devices": {}})
+        assert suggestions == []
+
+
+# ---------------------------------------------------------------------------
+# predict_performance
+# ---------------------------------------------------------------------------
+
+class TestPredictPerformance:
+    """predict_performance 使用 sum(gops) / num_stages * 0.6 計算 FPS。"""
+
+    def test_should_return_expected_fps_with_single_device_single_stage(self, engine):
+        devices = [_make_device_info(gops=28)]
+        # estimated_fps = 28 / 1 * 0.6 = 16.8
+        config = [MagicMock()]  # 1 stage
+        result = engine.predict_performance(config, devices)
+        assert result["estimated_fps"] == pytest.approx(16.8)
+
+    def test_should_return_expected_latency(self, engine):
+        devices = [_make_device_info(gops=28)]
+        config = [MagicMock()]  # 1 stage
+        result = engine.predict_performance(config, devices)
+        # estimated_latency_ms = 1000 / 16.8
+        assert result["estimated_latency_ms"] == pytest.approx(1000.0 / 16.8, rel=1e-4)
+
+    def test_should_return_confidence_range_as_tuple(self, engine):
+        devices = [_make_device_info(gops=28)]
+        config = [MagicMock()]  # 1 stage
+        result = engine.predict_performance(config, devices)
+        low, high = result["confidence_range"]
+        fps = result["estimated_fps"]
+        assert low == pytest.approx(fps * 0.8)
+        assert high == pytest.approx(fps * 1.2)
+
+    def test_should_scale_fps_with_multiple_devices(self, engine):
+        devices = [
+            _make_device_info("usb-1", gops=28),
+            _make_device_info("usb-2", gops=28),
+        ]
+        config = [MagicMock(), MagicMock()]  # 2 stages
+        result = engine.predict_performance(config, devices)
+        # estimated_fps = (28 + 28) / 2 * 0.6 = 16.8
+        assert result["estimated_fps"] == pytest.approx(16.8)
+
+    def test_should_decrease_fps_with_more_stages(self, engine):
+        devices = [_make_device_info(gops=28)]
+        config_1 = [MagicMock()]           # 1 stage
+        config_4 = [MagicMock()] * 4      # 4 stages
+        result_1 = engine.predict_performance(config_1, devices)
+        result_4 = engine.predict_performance(config_4, devices)
+        assert result_4["estimated_fps"] < result_1["estimated_fps"]
+
+    def test_should_handle_zero_stages_without_crash(self, engine):
+        """num_stages = 0 時回傳 0 FPS（不拋錯）。"""
+        devices = [_make_device_info(gops=28)]
+        result = engine.predict_performance([], devices)
+        assert result["estimated_fps"] == 0.0
+
+    def test_should_return_zero_fps_with_no_devices(self, engine):
+        config = [MagicMock()]
+        result = engine.predict_performance(config, [])
+        assert result["estimated_fps"] == 0.0
+
+
+# ---------------------------------------------------------------------------
+# apply_suggestion
+# ---------------------------------------------------------------------------
+
+class TestApplySuggestion:
+    def _make_rebalance_suggestion(self, stage_id="stage_0", device_id="usb-1"):
+        return OptimizationSuggestion(
+            suggestion_id="test-001",
+            type="rebalance_devices",
+            description="Rebalance test",
+            estimated_improvement_pct=10.0,
+            confidence="medium",
+            action_params={"stage_id": stage_id, "device_id": device_id},
+        )
+
+    def test_should_call_assign_device_for_rebalance_suggestion(self, engine):
+        dm = MagicMock()
+        dm.assign_device.return_value = True
+        suggestion = self._make_rebalance_suggestion("stage_0", "usb-1")
+        result = engine.apply_suggestion(suggestion, dm)
+        dm.assign_device.assert_called_once_with("usb-1", "stage_0")
+        assert result is True
+
+    def test_should_return_false_when_assign_device_fails(self, engine):
+        dm = MagicMock()
+        dm.assign_device.return_value = False
+        suggestion = self._make_rebalance_suggestion()
+        result = engine.apply_suggestion(suggestion, dm)
+        assert result is False
+
+    def test_should_return_true_for_add_devices_without_calling_assign(self, engine):
+        dm = MagicMock()
+        suggestion = OptimizationSuggestion(
+            suggestion_id="test-002",
+            type="add_devices",
+            description="Add more dongles",
+            estimated_improvement_pct=20.0,
+            confidence="high",
+            action_params={},
+        )
+        result = engine.apply_suggestion(suggestion, dm)
+        dm.assign_device.assert_not_called()
+        assert result is True
+
+    def test_should_return_true_for_adjust_queue_without_calling_assign(self, engine):
+        dm = MagicMock()
+        suggestion = OptimizationSuggestion(
+            suggestion_id="test-003",
+            type="adjust_queue",
+            description="Adjust queue size",
+            estimated_improvement_pct=5.0,
+            confidence="low",
+            action_params={},
+        )
+        result = engine.apply_suggestion(suggestion, dm)
+        dm.assign_device.assert_not_called()
+        assert result is True
+
+    def should_call_assign_device_with_empty_device_id_when_not_populated(self, engine):
+        # analyze_pipeline 產生的 rebalance 建議 device_id 預設為空字串
+        # apply_suggestion 應如實傳遞空字串給 device_manager（行為可預期）
+        suggestion = OptimizationSuggestion(
+            suggestion_id="test",
+            type="rebalance_devices",
+            description="test",
+            estimated_improvement_pct=10.0,
+            confidence="medium",
+            action_params={"device_id": "", "stage_id": "stage_0"}
+        )
+        mock_dm = MagicMock()
+        mock_dm.assign_device.return_value = False  # 空 device_id 通常回傳 False
+        result = engine.apply_suggestion(suggestion, mock_dm)
+        mock_dm.assign_device.assert_called_once_with("", "stage_0")
+        # result 取決於 assign_device 回傳值
+        assert result == False

tests/unit/test_performance_dashboard.py

@@ -0,0 +1,152 @@
+"""
+PerformanceDashboard 的單元測試。
+
+測試策略：
+- PyQt5 在 CI 環境中不可用，透過 conftest.py 的 Mock 注入繞過 import。
+- 測試驗證 PerformanceDashboard 的行為邏輯：
+  update_stats 是否更新顯示值、reset 是否歸零、set_display_window 是否儲存設定。
+- 使用 MagicMock 取代真實 QLabel，透過記錄 setText 呼叫來驗證。
+"""
+import sys
+import pytest
+from unittest.mock import MagicMock, patch, call
+
+
+# ---------------------------------------------------------------------------
+# 測試：PerformanceDashboard 可以建立
+# ---------------------------------------------------------------------------
+
+class TestPerformanceDashboardInit:
+    def should_be_importable(self):
+        """PerformanceDashboard 模組應可匯入（即使 PyQt5 被 Mock）。"""
+        from ui.components.performance_dashboard import PerformanceDashboard
+        assert PerformanceDashboard is not None
+
+    def should_instantiate_without_error(self):
+        """PerformanceDashboard() 應可無錯誤地建立實例。"""
+        from ui.components.performance_dashboard import PerformanceDashboard
+        dashboard = PerformanceDashboard()
+        assert dashboard is not None
+
+
+# ---------------------------------------------------------------------------
+# 測試：update_stats 更新顯示值
+# ---------------------------------------------------------------------------
+
+class TestUpdateStats:
+    def should_store_fps_after_update(self):
+        """update_stats 後，current_fps 屬性應更新為傳入的值。"""
+        from ui.components.performance_dashboard import PerformanceDashboard
+        dashboard = PerformanceDashboard()
+        dashboard.update_stats({"fps": 30.5, "avg_latency_ms": 10.0, "p95_latency_ms": 15.0})
+        assert dashboard.current_fps == pytest.approx(30.5)
+
+    def should_store_avg_latency_after_update(self):
+        """update_stats 後，current_avg_latency_ms 屬性應更新。"""
+        from ui.components.performance_dashboard import PerformanceDashboard
+        dashboard = PerformanceDashboard()
+        dashboard.update_stats({"fps": 30.0, "avg_latency_ms": 12.3, "p95_latency_ms": 20.0})
+        assert dashboard.current_avg_latency_ms == pytest.approx(12.3)
+
+    def should_store_p95_latency_after_update(self):
+        """update_stats 後，current_p95_latency_ms 屬性應更新。"""
+        from ui.components.performance_dashboard import PerformanceDashboard
+        dashboard = PerformanceDashboard()
+        dashboard.update_stats({"fps": 30.0, "avg_latency_ms": 12.0, "p95_latency_ms": 25.7})
+        assert dashboard.current_p95_latency_ms == pytest.approx(25.7)
+
+    def should_call_fps_label_setText(self):
+        """update_stats 應對 fps_label 呼叫 setText，包含 fps 數值。"""
+        from ui.components.performance_dashboard import PerformanceDashboard
+        dashboard = PerformanceDashboard()
+        dashboard.fps_label.setText.reset_mock()
+        dashboard.update_stats({"fps": 45.0, "avg_latency_ms": 10.0, "p95_latency_ms": 15.0})
+        dashboard.fps_label.setText.assert_called_once()
+        call_arg = dashboard.fps_label.setText.call_args[0][0]
+        assert "45" in call_arg
+
+    def should_call_avg_latency_label_setText(self):
+        """update_stats 應對 avg_latency_label 呼叫 setText，包含延遲數值。"""
+        from ui.components.performance_dashboard import PerformanceDashboard
+        dashboard = PerformanceDashboard()
+        dashboard.avg_latency_label.setText.reset_mock()
+        dashboard.update_stats({"fps": 30.0, "avg_latency_ms": 8.5, "p95_latency_ms": 12.0})
+        dashboard.avg_latency_label.setText.assert_called_once()
+        call_arg = dashboard.avg_latency_label.setText.call_args[0][0]
+        assert "8.5" in call_arg or "8" in call_arg
+
+    def should_call_p95_latency_label_setText(self):
+        """update_stats 應對 p95_latency_label 呼叫 setText，包含 p95 數值。"""
+        from ui.components.performance_dashboard import PerformanceDashboard
+        dashboard = PerformanceDashboard()
+        dashboard.p95_latency_label.setText.reset_mock()
+        dashboard.update_stats({"fps": 30.0, "avg_latency_ms": 8.0, "p95_latency_ms": 19.2})
+        dashboard.p95_latency_label.setText.assert_called_once()
+        call_arg = dashboard.p95_latency_label.setText.call_args[0][0]
+        assert "19" in call_arg
+
+
+# ---------------------------------------------------------------------------
+# 測試：reset 歸零
+# ---------------------------------------------------------------------------
+
+class TestReset:
+    def should_reset_fps_to_zero(self):
+        """reset() 後 current_fps 應歸零。"""
+        from ui.components.performance_dashboard import PerformanceDashboard
+        dashboard = PerformanceDashboard()
+        dashboard.update_stats({"fps": 55.0, "avg_latency_ms": 5.0, "p95_latency_ms": 8.0})
+        dashboard.reset()
+        assert dashboard.current_fps == 0.0
+
+    def should_reset_avg_latency_to_zero(self):
+        """reset() 後 current_avg_latency_ms 應歸零。"""
+        from ui.components.performance_dashboard import PerformanceDashboard
+        dashboard = PerformanceDashboard()
+        dashboard.update_stats({"fps": 30.0, "avg_latency_ms": 12.0, "p95_latency_ms": 18.0})
+        dashboard.reset()
+        assert dashboard.current_avg_latency_ms == 0.0
+
+    def should_reset_p95_latency_to_zero(self):
+        """reset() 後 current_p95_latency_ms 應歸零。"""
+        from ui.components.performance_dashboard import PerformanceDashboard
+        dashboard = PerformanceDashboard()
+        dashboard.update_stats({"fps": 30.0, "avg_latency_ms": 12.0, "p95_latency_ms": 18.0})
+        dashboard.reset()
+        assert dashboard.current_p95_latency_ms == 0.0
+
+    def should_call_label_setText_with_zero_on_reset(self):
+        """reset() 應對 fps_label 呼叫 setText，更新為 0 值。"""
+        from ui.components.performance_dashboard import PerformanceDashboard
+        dashboard = PerformanceDashboard()
+        dashboard.fps_label.setText.reset_mock()
+        dashboard.reset()
+        dashboard.fps_label.setText.assert_called_once()
+
+
+# ---------------------------------------------------------------------------
+# 測試：set_display_window 儲存設定
+# ---------------------------------------------------------------------------
+
+class TestSetDisplayWindow:
+    def should_store_display_window_seconds(self):
+        """set_display_window(120) 後，display_window_seconds 應為 120。"""
+        from ui.components.performance_dashboard import PerformanceDashboard
+        dashboard = PerformanceDashboard()
+        dashboard.set_display_window(120)
+        assert dashboard.display_window_seconds == 120
+
+    def should_default_to_60_seconds(self):
+        """不傳參數時 display_window_seconds 預設應為 60。"""
+        from ui.components.performance_dashboard import PerformanceDashboard
+        dashboard = PerformanceDashboard()
+        dashboard.set_display_window()
+        assert dashboard.display_window_seconds == 60
+
+    def should_update_display_window_on_second_call(self):
+        """連續呼叫 set_display_window 應覆蓋舊值。"""
+        from ui.components.performance_dashboard import PerformanceDashboard
+        dashboard = PerformanceDashboard()
+        dashboard.set_display_window(30)
+        dashboard.set_display_window(90)
+        assert dashboard.display_window_seconds == 90

tests/unit/test_report_exporter.py

@@ -0,0 +1,250 @@
+"""
+tests/unit/test_report_exporter.py — ReportExporter 單元測試。
+
+按照 TDD 3.4.9 的測試清單實作。
+"""
+import csv
+import io
+import time
+from pathlib import Path
+from unittest.mock import patch, MagicMock
+
+import pytest
+
+from core.performance.benchmarker import BenchmarkResult
+from core.performance.report_exporter import DeviceSummary, ReportData, ReportExporter
+
+
+# ---------------------------------------------------------------------------
+# Fixtures
+# ---------------------------------------------------------------------------
+
+def _make_benchmark_result(mode: str = "sequential", fps: float = 14.2) -> BenchmarkResult:
+    return BenchmarkResult(
+        mode=mode,
+        fps=fps,
+        avg_latency_ms=70.4,
+        p95_latency_ms=95.0,
+        total_frames=426,
+        timestamp=1743856222.0,
+        device_config={"KL720": 1},
+        id=f"benchmark_20260405_143022_{mode}",
+    )
+
+
+def _make_report_data_with_benchmark() -> ReportData:
+    seq = _make_benchmark_result("sequential", fps=14.2)
+    par = _make_benchmark_result("parallel", fps=45.6)
+    return ReportData(
+        report_title="Test Report",
+        pipeline_name="test_pipeline",
+        sequential_result=seq,
+        parallel_result=par,
+        speedup=45.6 / 14.2,
+        history_records=[seq, par],
+    )
+
+
+# ---------------------------------------------------------------------------
+# _get_timestamp_str
+# ---------------------------------------------------------------------------
+
+class TestGetTimestampStr:
+    def test_format_is_yyyy_mm_dd_hh_mm_ss(self):
+        """_get_timestamp_str 應回傳 'YYYY-MM-DD HH:MM:SS' 格式的字串"""
+        ts = 1743856222.0
+        result = ReportExporter._get_timestamp_str(ts)
+        # 驗證格式：長度固定為 19，包含 '-' 和 ':'
+        assert len(result) == 19
+        assert result[4] == "-"
+        assert result[7] == "-"
+        assert result[10] == " "
+        assert result[13] == ":"
+        assert result[16] == ":"
+
+    def test_all_parts_are_digits(self):
+        """timestamp 各欄位均應為數字"""
+        ts = 1743856222.0
+        result = ReportExporter._get_timestamp_str(ts)
+        parts = result.replace("-", "").replace(":", "").replace(" ", "")
+        assert parts.isdigit()
+
+
+# ---------------------------------------------------------------------------
+# ReportData 預設值
+# ---------------------------------------------------------------------------
+
+class TestReportDataDefaults:
+    def test_report_title_is_non_empty(self):
+        """ReportData 預設 report_title 應非空"""
+        data = ReportData()
+        assert data.report_title
+        assert len(data.report_title) > 0
+
+    def test_generated_at_is_close_to_now(self):
+        """ReportData 預設 generated_at 應接近當下時間（誤差 < 5 秒）"""
+        before = time.time()
+        data = ReportData()
+        after = time.time()
+        assert before <= data.generated_at <= after + 5
+
+    def test_history_records_defaults_to_empty_list(self):
+        """ReportData 預設 history_records 應為空列表"""
+        data = ReportData()
+        assert data.history_records == []
+
+    def test_devices_defaults_to_empty_list(self):
+        """ReportData 預設 devices 應為空列表"""
+        data = ReportData()
+        assert data.devices == []
+
+    def test_sequential_result_defaults_to_none(self):
+        data = ReportData()
+        assert data.sequential_result is None
+
+    def test_parallel_result_defaults_to_none(self):
+        data = ReportData()
+        assert data.parallel_result is None
+
+
+# ---------------------------------------------------------------------------
+# export_csv
+# ---------------------------------------------------------------------------
+
+class TestExportCsv:
+    def test_creates_file_at_given_path(self, tmp_path):
+        """export_csv() 應在指定路徑建立 CSV 檔案"""
+        data = _make_report_data_with_benchmark()
+        output_path = tmp_path / "report.csv"
+        exporter = ReportExporter()
+        result = exporter.export_csv(data, output_path)
+        assert output_path.exists()
+        assert result == output_path
+
+    def test_contains_benchmark_summary_section(self, tmp_path):
+        """CSV 應包含完整的 benchmark_summary header 行"""
+        data = _make_report_data_with_benchmark()
+        output_path = tmp_path / "report.csv"
+        exporter = ReportExporter()
+        exporter.export_csv(data, output_path)
+
+        content = output_path.read_text(encoding="utf-8")
+        assert "section,metric,sequential,parallel,diff_pct" in content
+
+    def test_contains_history_section(self, tmp_path):
+        """CSV 應包含完整的歷史記錄 header 行"""
+        data = _make_report_data_with_benchmark()
+        output_path = tmp_path / "report.csv"
+        exporter = ReportExporter()
+        exporter.export_csv(data, output_path)
+
+        content = output_path.read_text(encoding="utf-8")
+        assert "id,timestamp,mode,fps,avg_latency_ms,p95_latency_ms,total_frames" in content
+
+        # 歷史記錄有 2 筆，驗證資料行數
+        lines = [l for l in content.splitlines() if l.strip()]
+        history_data_lines = [l for l in lines if l.startswith("benchmark_2")]
+        assert len(history_data_lines) == len(data.history_records)
+
+    def test_two_sections_separated_by_blank_line(self, tmp_path):
+        """CSV 的兩個 header 行之間恰有一行空行"""
+        data = _make_report_data_with_benchmark()
+        output_path = tmp_path / "report.csv"
+        exporter = ReportExporter()
+        exporter.export_csv(data, output_path)
+
+        content = output_path.read_text(encoding="utf-8")
+        lines = content.splitlines()
+
+        summary_header = "section,metric,sequential,parallel,diff_pct"
+        history_header = "id,timestamp,mode,fps,avg_latency_ms,p95_latency_ms,total_frames"
+
+        idx_summary = next(i for i, l in enumerate(lines) if l == summary_header)
+        idx_history = next(i for i, l in enumerate(lines) if l == history_header)
+
+        # 兩個 header 行之間，緊鄰 history header 的前一行必須是空行
+        assert idx_history > idx_summary + 1
+        assert lines[idx_history - 1] == ""
+
+    def test_no_benchmark_result_raises_value_error(self, tmp_path):
+        """sequential_result 或 parallel_result 為 None 時，應拋出 ValueError"""
+        data = ReportData()  # sequential_result=None, parallel_result=None
+        output_path = tmp_path / "report.csv"
+        exporter = ReportExporter()
+        with pytest.raises(ValueError):
+            exporter.export_csv(data, output_path)
+
+    def test_empty_history_produces_only_summary(self, tmp_path):
+        """history_records 為空時，CSV 只輸出 Benchmark 摘要區塊，歷史記錄表為空"""
+        seq = _make_benchmark_result("sequential", fps=14.2)
+        par = _make_benchmark_result("parallel", fps=45.6)
+        data = ReportData(
+            sequential_result=seq,
+            parallel_result=par,
+            speedup=45.6 / 14.2,
+            history_records=[],
+        )
+        output_path = tmp_path / "report.csv"
+        exporter = ReportExporter()
+        exporter.export_csv(data, output_path)
+
+        content = output_path.read_text(encoding="utf-8")
+        assert "benchmark_summary" in content
+        # 沒有歷史資料行（id 開頭的行）
+        data_lines = [l for l in content.splitlines() if l.startswith("benchmark_2")]
+        assert len(data_lines) == 0
+
+    def test_auto_creates_parent_directory(self, tmp_path):
+        """若輸出路徑的父目錄不存在，export_csv() 應自動建立"""
+        data = _make_report_data_with_benchmark()
+        output_path = tmp_path / "subdir" / "report.csv"
+        exporter = ReportExporter()
+        exporter.export_csv(data, output_path)
+        assert output_path.exists()
+
+
+# ---------------------------------------------------------------------------
+# export_pdf
+# ---------------------------------------------------------------------------
+
+class TestExportPdf:
+    def test_creates_file_at_given_path(self, tmp_path):
+        """export_pdf() 應在指定路徑建立 PDF 檔案（不驗證內容，只驗證存在）"""
+        reportlab = pytest.importorskip("reportlab")
+        data = _make_report_data_with_benchmark()
+        output_path = tmp_path / "report.pdf"
+        exporter = ReportExporter()
+        result = exporter.export_pdf(data, output_path)
+        assert output_path.exists()
+        assert result == output_path
+
+    def test_auto_creates_parent_directory(self, tmp_path):
+        """若輸出路徑的父目錄不存在，export_pdf() 應自動建立"""
+        pytest.importorskip("reportlab")
+        data = _make_report_data_with_benchmark()
+        output_path = tmp_path / "subdir" / "report.pdf"
+        exporter = ReportExporter()
+        exporter.export_pdf(data, output_path)
+        assert output_path.exists()
+
+    def test_without_chart_image_does_not_raise(self, tmp_path):
+        """chart_image_bytes 為 None 時，PDF 匯出不應拋出例外"""
+        pytest.importorskip("reportlab")
+        data = _make_report_data_with_benchmark()
+        data.chart_image_bytes = None
+        output_path = tmp_path / "report.pdf"
+        exporter = ReportExporter()
+        # 不應拋出例外
+        exporter.export_pdf(data, output_path)
+
+    def test_raises_import_error_when_reportlab_missing(self, tmp_path):
+        """reportlab 未安裝時，export_pdf() 應拋出 ImportError"""
+        import core.performance.report_exporter as re_mod
+
+        data = _make_report_data_with_benchmark()
+        output_path = tmp_path / "report.pdf"
+        exporter = ReportExporter()
+
+        with patch.object(re_mod, "_REPORTLAB_AVAILABLE", False):
+            with pytest.raises(ImportError, match="reportlab"):
+                exporter.export_pdf(data, output_path)

tests/unit/test_result_serializer.py

@@ -0,0 +1,88 @@
+"""
+Tests for ResultSerializer — JSON serialization of inference result objects.
+"""
+import dataclasses
+import pytest
+from unittest.mock import MagicMock
+
+from core.functions.result_handler import ResultSerializer
+
+
+# Minimal stand-ins for the SDK dataclasses (no kp import needed)
+@dataclasses.dataclass
+class FakeBoundingBox:
+    x1: int = 0
+    y1: int = 0
+    x2: int = 100
+    y2: int = 100
+    class_name: str = "fire"
+    score: float = 0.9
+
+
+@dataclasses.dataclass
+class FakeObjectDetectionResult:
+    class_count: int = 1
+    box_count: int = 1
+    box_list: list = dataclasses.field(default_factory=list)
+
+
+@dataclasses.dataclass
+class FakeClassificationResult:
+    probability: float = 0.85
+    class_name: str = "fire"
+    class_num: int = 0
+
+
+class TestResultSerializerToJson:
+    def setup_method(self):
+        self.serializer = ResultSerializer()
+
+    def should_serialize_plain_dict(self):
+        data = {"fps": 30.0, "pipeline_id": "p1"}
+        result = self.serializer.to_json(data)
+        assert '"fps"' in result
+        assert "30.0" in result
+
+    def should_serialize_dict_containing_dataclass_object(self):
+        """Bug reproduction: ObjectDetectionResult in result dict caused TypeError."""
+        det = FakeObjectDetectionResult(
+            class_count=1,
+            box_count=1,
+            box_list=[FakeBoundingBox()]
+        )
+        data = {"stage_results": {"stage_0": det}}
+        # Should NOT raise TypeError: Object of type FakeObjectDetectionResult is not JSON serializable
+        result = self.serializer.to_json(data)
+        assert result is not None
+        assert "stage_0" in result
+
+    def should_serialize_dict_containing_classification_result(self):
+        """ClassificationResult must also be handled."""
+        clf = FakeClassificationResult(probability=0.85, class_name="fire")
+        data = {"stage_results": {"stage_0": clf}}
+        result = self.serializer.to_json(data)
+        assert "stage_0" in result
+
+    def should_serialize_nested_dataclass_in_list(self):
+        """box_list inside ObjectDetectionResult contains BoundingBox dataclasses."""
+        det = FakeObjectDetectionResult(
+            box_count=1,
+            box_list=[FakeBoundingBox(x1=10, y1=20, x2=110, y2=120, class_name="fire")]
+        )
+        data = {"detections": det}
+        result = self.serializer.to_json(data)
+        assert "fire" in result
+
+    def should_preserve_primitive_values_unchanged(self):
+        data = {"fps": 45.2, "count": 3, "name": "test", "flag": True}
+        import json
+        result = json.loads(self.serializer.to_json(data))
+        assert result["fps"] == 45.2
+        assert result["count"] == 3
+        assert result["name"] == "test"
+        assert result["flag"] is True
+
+    def should_handle_none_values(self):
+        data = {"result": None, "stage": "stage_0"}
+        result = self.serializer.to_json(data)
+        assert "null" in result

tests/unit/test_template_manager.py

@@ -0,0 +1,231 @@
+"""
+tests/unit/test_template_manager.py
+
+TDD Phase 3.3.2 — TemplateManager 單元測試。
+
+覆蓋範圍：
+- get_builtin_templates 回傳 3 個範本
+- load_template 正確載入內建範本
+- load_template 對不存在的 ID 拋出 ValueError
+- save_as_template 建立新範本並可被 load_template 讀取
+"""
+import pytest
+
+from core.templates.manager import TemplateManager, PipelineTemplate
+
+
+# ---------------------------------------------------------------------------
+# Fixtures
+# ---------------------------------------------------------------------------
+
+@pytest.fixture
+def manager():
+    return TemplateManager()
+
+
+# ---------------------------------------------------------------------------
+# get_builtin_templates
+# ---------------------------------------------------------------------------
+
+class TestGetBuiltinTemplates:
+    def test_should_return_exactly_three_builtin_templates(self, manager):
+        templates = manager.get_builtin_templates()
+        assert len(templates) == 3
+
+    def test_should_return_list_of_pipeline_template_instances(self, manager):
+        templates = manager.get_builtin_templates()
+        for t in templates:
+            assert isinstance(t, PipelineTemplate)
+
+    def test_should_include_yolov5_detection_template(self, manager):
+        templates = manager.get_builtin_templates()
+        ids = [t.template_id for t in templates]
+        assert "yolov5_detection" in ids
+
+    def test_should_include_fire_detection_template(self, manager):
+        templates = manager.get_builtin_templates()
+        ids = [t.template_id for t in templates]
+        assert "fire_detection" in ids
+
+    def test_should_include_dual_model_cascade_template(self, manager):
+        templates = manager.get_builtin_templates()
+        ids = [t.template_id for t in templates]
+        assert "dual_model_cascade" in ids
+
+    def test_each_template_has_non_empty_name_and_description(self, manager):
+        templates = manager.get_builtin_templates()
+        for t in templates:
+            assert t.name
+            assert t.description
+
+    def test_each_template_has_nodes_list(self, manager):
+        templates = manager.get_builtin_templates()
+        for t in templates:
+            assert isinstance(t.nodes, list)
+            assert len(t.nodes) >= 2
+
+    def test_each_template_has_connections_list(self, manager):
+        templates = manager.get_builtin_templates()
+        for t in templates:
+            assert isinstance(t.connections, list)
+
+
+# ---------------------------------------------------------------------------
+# load_template — 內建範本
+# ---------------------------------------------------------------------------
+
+class TestLoadTemplate:
+    def test_should_load_yolov5_detection_by_id(self, manager):
+        t = manager.load_template("yolov5_detection")
+        assert isinstance(t, PipelineTemplate)
+        assert t.template_id == "yolov5_detection"
+
+    def test_should_load_fire_detection_by_id(self, manager):
+        t = manager.load_template("fire_detection")
+        assert t.template_id == "fire_detection"
+
+    def test_should_load_dual_model_cascade_by_id(self, manager):
+        t = manager.load_template("dual_model_cascade")
+        assert t.template_id == "dual_model_cascade"
+
+    def test_should_raise_value_error_for_unknown_id(self, manager):
+        with pytest.raises(ValueError, match="not found"):
+            manager.load_template("nonexistent_template_xyz")
+
+    def test_should_raise_value_error_with_template_id_in_message(self, manager):
+        bad_id = "totally_unknown_id"
+        with pytest.raises(ValueError, match=bad_id):
+            manager.load_template(bad_id)
+
+
+# ---------------------------------------------------------------------------
+# yolov5_detection 節點結構驗證
+# ---------------------------------------------------------------------------
+
+class TestYolov5DetectionStructure:
+    """Input → Preprocess → Model → Postprocess → Output 順序。"""
+
+    def test_should_have_five_nodes(self, manager):
+        t = manager.load_template("yolov5_detection")
+        assert len(t.nodes) == 5
+
+    def test_nodes_should_include_input_and_output(self, manager):
+        t = manager.load_template("yolov5_detection")
+        node_types = [n["type"] for n in t.nodes]
+        assert "Input" in node_types
+        assert "Output" in node_types
+
+    def test_nodes_should_include_model_and_preprocess_postprocess(self, manager):
+        t = manager.load_template("yolov5_detection")
+        node_types = [n["type"] for n in t.nodes]
+        assert "Model" in node_types
+        assert "Preprocess" in node_types
+        assert "Postprocess" in node_types
+
+
+# ---------------------------------------------------------------------------
+# fire_detection 節點結構驗證
+# ---------------------------------------------------------------------------
+
+class TestFireDetectionStructure:
+    """Input → Model → Postprocess → Output 順序。"""
+
+    def test_should_have_four_nodes(self, manager):
+        t = manager.load_template("fire_detection")
+        assert len(t.nodes) == 4
+
+    def test_nodes_should_include_input_model_postprocess_output(self, manager):
+        t = manager.load_template("fire_detection")
+        node_types = [n["type"] for n in t.nodes]
+        assert "Input" in node_types
+        assert "Model" in node_types
+        assert "Postprocess" in node_types
+        assert "Output" in node_types
+
+    def test_nodes_should_not_include_preprocess(self, manager):
+        t = manager.load_template("fire_detection")
+        node_types = [n["type"] for n in t.nodes]
+        assert "Preprocess" not in node_types
+
+
+# ---------------------------------------------------------------------------
+# dual_model_cascade 節點結構驗證
+# ---------------------------------------------------------------------------
+
+class TestDualModelCascadeStructure:
+    """Input → Model1 → Postprocess1 → Model2 → Postprocess2 → Output 順序。"""
+
+    def test_should_have_six_nodes(self, manager):
+        t = manager.load_template("dual_model_cascade")
+        assert len(t.nodes) == 6
+
+    def test_should_have_two_model_nodes(self, manager):
+        t = manager.load_template("dual_model_cascade")
+        model_nodes = [n for n in t.nodes if n["type"] == "Model"]
+        assert len(model_nodes) == 2
+
+    def test_should_have_two_postprocess_nodes(self, manager):
+        t = manager.load_template("dual_model_cascade")
+        pp_nodes = [n for n in t.nodes if n["type"] == "Postprocess"]
+        assert len(pp_nodes) == 2
+
+
+# ---------------------------------------------------------------------------
+# save_as_template
+# ---------------------------------------------------------------------------
+
+class TestSaveAsTemplate:
+    def _sample_config(self):
+        return {
+            "nodes": [
+                {"id": "n1", "type": "Input"},
+                {"id": "n2", "type": "Output"},
+            ],
+            "connections": [
+                {"from": "n1", "to": "n2"},
+            ],
+        }
+
+    def test_should_return_pipeline_template_instance(self, manager):
+        t = manager.save_as_template(
+            self._sample_config(), "My Template", "A test template"
+        )
+        assert isinstance(t, PipelineTemplate)
+
+    def test_returned_template_has_correct_name(self, manager):
+        t = manager.save_as_template(self._sample_config(), "Custom Pipeline", "desc")
+        assert t.name == "Custom Pipeline"
+
+    def test_returned_template_has_correct_description(self, manager):
+        t = manager.save_as_template(self._sample_config(), "name", "My description")
+        assert t.description == "My description"
+
+    def test_returned_template_has_unique_id(self, manager):
+        t1 = manager.save_as_template(self._sample_config(), "T1", "desc")
+        t2 = manager.save_as_template(self._sample_config(), "T2", "desc")
+        assert t1.template_id != t2.template_id
+
+    def test_returned_template_id_starts_with_custom(self, manager):
+        t = manager.save_as_template(self._sample_config(), "My Template", "desc")
+        assert t.template_id.startswith("custom_")
+
+    def test_saved_template_can_be_loaded_by_id(self, manager):
+        saved = manager.save_as_template(self._sample_config(), "Loadable", "desc")
+        loaded = manager.load_template(saved.template_id)
+        assert loaded.template_id == saved.template_id
+        assert loaded.name == "Loadable"
+
+    def test_saved_template_nodes_match_pipeline_config(self, manager):
+        config = self._sample_config()
+        saved = manager.save_as_template(config, "Node Test", "desc")
+        assert saved.nodes == config["nodes"]
+
+    def test_saved_template_connections_match_pipeline_config(self, manager):
+        config = self._sample_config()
+        saved = manager.save_as_template(config, "Conn Test", "desc")
+        assert saved.connections == config["connections"]
+
+    def test_saving_does_not_affect_builtin_templates(self, manager):
+        manager.save_as_template(self._sample_config(), "Extra", "desc")
+        builtins = manager.get_builtin_templates()
+        assert len(builtins) == 3

ui/components/device_management_panel.py

@@ -0,0 +1,123 @@
+"""
+ui/components/device_management_panel.py
+
+DeviceManagementPanel — QWidget that displays the status of all connected
+NPU Dongles and provides manual/automatic assignment controls.
+"""
+from __future__ import annotations
+
+from typing import List, Optional
+
+from PyQt5.QtCore import QTimer, pyqtSignal
+from PyQt5.QtWidgets import (
+    QHBoxLayout,
+    QLabel,
+    QPushButton,
+    QVBoxLayout,
+    QWidget,
+)
+
+from core.device.device_manager import DeviceInfo, DeviceManager
+
+
+class DeviceManagementPanel(QWidget):
+    """Displays real-time NPU Dongle status and assignment controls.
+
+    Signals
+    -------
+    device_assignment_changed(device_id, stage_id):
+        Emitted when the user changes a device's stage assignment.
+    """
+
+    device_assignment_changed = pyqtSignal(str, str)
+
+    def __init__(
+        self,
+        device_manager: DeviceManager,
+        parent: Optional[QWidget] = None,
+    ) -> None:
+        super().__init__(parent)
+        self._device_manager = device_manager
+        self._devices: List[DeviceInfo] = []
+        self._auto_refresh_interval_ms: int = 0
+        self._timer: Optional[QTimer] = None
+
+        self._setup_ui()
+        self.refresh()
+
+    # ------------------------------------------------------------------
+    # UI construction
+    # ------------------------------------------------------------------
+
+    def _setup_ui(self) -> None:
+        layout = QVBoxLayout()
+
+        # Toolbar row: Auto Balance button
+        toolbar = QHBoxLayout()
+        self.auto_balance_button = QPushButton("Auto Balance")
+        self.auto_balance_button.clicked.connect(self._on_auto_balance)
+        toolbar.addWidget(self.auto_balance_button)
+        toolbar.addStretch()
+
+        # Device cards area
+        self._cards_layout = QVBoxLayout()
+        self._no_device_label = QLabel("No devices connected")
+
+        layout.addLayout(toolbar)
+        layout.addWidget(self._no_device_label)
+        layout.addLayout(self._cards_layout)
+        self.setLayout(layout)
+
+    # ------------------------------------------------------------------
+    # Public API
+    # ------------------------------------------------------------------
+
+    def refresh(self) -> None:
+        """Re-scan devices and update the displayed cards."""
+        self._devices = self._device_manager.scan_devices()
+        self._rebuild_cards()
+
+    def set_auto_refresh(self, interval_ms: int = 2000) -> None:
+        """Configure periodic auto-refresh using a QTimer.
+
+        Parameters
+        ----------
+        interval_ms:
+            Refresh interval in milliseconds.  Defaults to 2 000 ms.
+        """
+        if interval_ms <= 0:
+            if self._timer is not None:
+                self._timer.stop()
+            return
+        self._auto_refresh_interval_ms = interval_ms
+        if self._timer is None:
+            self._timer = QTimer(self)
+            self._timer.timeout.connect(self.refresh)
+        self._timer.start(interval_ms)
+
+    # ------------------------------------------------------------------
+    # Private helpers
+    # ------------------------------------------------------------------
+
+    def _rebuild_cards(self) -> None:
+        """Recreate device card widgets from the current device list."""
+        if not self._devices:
+            self._no_device_label.setVisible(True)
+            return
+        self._no_device_label.setVisible(False)
+
+    def _on_auto_balance(self) -> None:
+        """Handle Auto Balance button click."""
+        if not self._devices:
+            return
+        stage_ids = [
+            d.assigned_stage for d in self._devices if d.assigned_stage
+        ]
+        if not stage_ids:
+            return
+        recommendations = self._device_manager.get_load_balance_recommendation(
+            stage_ids
+        )
+        for stage_id, device_id in recommendations.items():
+            if device_id:
+                self.device_assignment_changed.emit(device_id, stage_id)

ui/components/performance_dashboard.py

@@ -0,0 +1,97 @@
+"""
+ui/components/performance_dashboard.py
+
+PerformanceDashboard — 顯示即時 FPS 與延遲數值的 QWidget。
+
+使用 pyqtgraph 繪製折線圖（如可用），否則降級為純 QLabel 顯示數值，
+避免 import error 導致應用崩潰。
+"""
+from typing import Any, Dict, Optional
+
+from PyQt5.QtCore import pyqtSignal
+from PyQt5.QtWidgets import QHBoxLayout, QLabel, QVBoxLayout, QWidget
+
+try:
+    import pyqtgraph as pg  # type: ignore
+    _PYQTGRAPH_AVAILABLE = True
+except ImportError:
+    _PYQTGRAPH_AVAILABLE = False
+# TODO: Phase 2 - 當 pyqtgraph 可用時，改用折線圖顯示歷史 FPS/Latency
+
+
+class PerformanceDashboard(QWidget):
+    """即時效能儀錶板元件。
+
+    顯示當前 FPS、平均延遲與 p95 延遲。
+    接受 update_stats(stats) 推送的數據並更新 QLabel 顯示值。
+    """
+
+    update_requested = pyqtSignal(dict)
+
+    def __init__(self, parent: Optional[QWidget] = None) -> None:
+        super().__init__(parent)
+
+        # 內部狀態
+        self.current_fps: float = 0.0
+        self.current_avg_latency_ms: float = 0.0
+        self.current_p95_latency_ms: float = 0.0
+        self.display_window_seconds: int = 60
+
+        # UI 元件（動態值 label，前綴由靜態 label 負責）
+        self.fps_label = QLabel("0.0")
+        self.avg_latency_label = QLabel("0.0")
+        self.p95_latency_label = QLabel("0.0")
+
+        self._setup_ui()
+
+    def _setup_ui(self) -> None:
+        layout = QVBoxLayout()
+
+        fps_row = QHBoxLayout()
+        fps_row.addWidget(QLabel("FPS:"))
+        fps_row.addWidget(self.fps_label)
+
+        avg_row = QHBoxLayout()
+        avg_row.addWidget(QLabel("Avg Latency:"))
+        avg_row.addWidget(self.avg_latency_label)
+
+        p95_row = QHBoxLayout()
+        p95_row.addWidget(QLabel("P95 Latency:"))
+        p95_row.addWidget(self.p95_latency_label)
+
+        layout.addLayout(fps_row)
+        layout.addLayout(avg_row)
+        layout.addLayout(p95_row)
+        self.setLayout(layout)
+
+    def update_stats(self, stats: Dict[str, Any]) -> None:
+        """接收效能數據並更新顯示。
+
+        Args:
+            stats: 包含 "fps"、"avg_latency_ms"、"p95_latency_ms" 的字典。
+        """
+        self.current_fps = float(stats.get("fps", 0.0))
+        self.current_avg_latency_ms = float(stats.get("avg_latency_ms", 0.0))
+        self.current_p95_latency_ms = float(stats.get("p95_latency_ms", 0.0))
+
+        self.fps_label.setText(f"{self.current_fps:.1f} FPS")
+        self.avg_latency_label.setText(f"{self.current_avg_latency_ms:.1f} ms")
+        self.p95_latency_label.setText(f"{self.current_p95_latency_ms:.1f} ms")
+
+    def reset(self) -> None:
+        """清空所有顯示值，回到初始狀態（0）。"""
+        self.current_fps = 0.0
+        self.current_avg_latency_ms = 0.0
+        self.current_p95_latency_ms = 0.0
+
+        self.fps_label.setText("0.0 FPS")
+        self.avg_latency_label.setText("0.0 ms")
+        self.p95_latency_label.setText("0.0 ms")
+
+    def set_display_window(self, seconds: int = 60) -> None:
+        """設定圖表顯示的時間視窗（秒）。
+
+        Args:
+            seconds: 要顯示的歷史時間範圍，預設 60 秒。
+        """
+        self.display_window_seconds = seconds

ui/dialogs/benchmark_dialog.py

@@ -0,0 +1,207 @@
+"""
+ui/dialogs/benchmark_dialog.py
+
+BenchmarkDialog — 一鍵啟動 Benchmark 的 QDialog。
+
+顯示三階段進度條（熱機/循序/平行）、即時 FPS、完成後加速倍數大字體
+以及循序 vs 平行的 FPS 與延遲對比表。
+
+Benchmark 執行透過 QThread 進行，避免 UI 凍結。
+若 pipeline_config 為空，顯示提示訊息並禁用開始按鈕。
+"""
+from typing import Any, List, Optional
+
+from PyQt5.QtCore import QThread, pyqtSignal
+from PyQt5.QtWidgets import (
+    QDialog,
+    QHBoxLayout,
+    QLabel,
+    QProgressBar,
+    QPushButton,
+    QTableWidget,
+    QTableWidgetItem,
+    QVBoxLayout,
+    QWidget,
+)
+
+
+class _BenchmarkWorker(QThread):
+    """在背景執行緒執行 benchmark，避免 UI 凍結。"""
+
+    progress_updated = pyqtSignal(str, int)
+    result_ready = pyqtSignal(object, object, float)
+    error_occurred = pyqtSignal(str)
+
+    def __init__(self, benchmarker: Any) -> None:
+        super().__init__()
+        self._benchmarker = benchmarker
+
+    def run(self) -> None:
+        try:
+            seq_result, par_result, speedup = self._benchmarker.run_full_benchmark(
+                progress_callback=self._on_progress
+            )
+            self.result_ready.emit(seq_result, par_result, speedup)
+        except Exception as exc:
+            self.error_occurred.emit(str(exc))
+
+    def _on_progress(self, phase: str, value: int) -> None:
+        self.progress_updated.emit(phase, value)
+
+
+class BenchmarkDialog(QDialog):
+    """Benchmark 觸發與結果顯示對話框。
+
+    Args:
+        parent: 父視窗。
+        pipeline_config: 目前的 pipeline Stage 設定列表。若為空，禁用開始按鈕。
+    """
+
+    def __init__(
+        self,
+        parent: Optional[QWidget],
+        pipeline_config: List[Any],
+    ) -> None:
+        super().__init__(parent)
+
+        self._pipeline_config = pipeline_config
+        self.seq_result: Optional[Any] = None
+        self.par_result: Optional[Any] = None
+        self.current_phase: str = ""
+        self._worker: Optional[_BenchmarkWorker] = None
+
+        self.setWindowTitle("Performance Benchmark")
+
+        # UI 元件
+        self.info_label = QLabel("")
+        self.progress_bar = QProgressBar()
+        self.progress_bar.setMinimum(0)
+        self.progress_bar.setMaximum(100)
+
+        self.fps_label = QLabel("FPS: —")
+        self.phase_label = QLabel("")
+        self.speedup_label = QLabel("")
+
+        self.result_table = QTableWidget(2, 3)
+        self.result_table.setHorizontalHeaderLabels(["模式", "FPS", "Avg Latency (ms)"])
+
+        self.start_button = QPushButton("開始 Benchmark")
+        self.close_button = QPushButton("關閉")
+
+        self._setup_ui()
+        self._apply_initial_state()
+
+    def _setup_ui(self) -> None:
+        layout = QVBoxLayout()
+
+        layout.addWidget(self.info_label)
+
+        progress_row = QHBoxLayout()
+        progress_row.addWidget(self.progress_bar)
+        progress_row.addWidget(self.phase_label)
+        layout.addLayout(progress_row)
+
+        fps_row = QHBoxLayout()
+        fps_row.addWidget(QLabel("即時 FPS："))
+        fps_row.addWidget(self.fps_label)
+        layout.addLayout(fps_row)
+
+        layout.addWidget(self.speedup_label)
+        layout.addWidget(self.result_table)
+
+        btn_row = QHBoxLayout()
+        btn_row.addWidget(self.start_button)
+        btn_row.addWidget(self.close_button)
+        layout.addLayout(btn_row)
+
+        self.setLayout(layout)
+
+    def _apply_initial_state(self) -> None:
+        if not self._pipeline_config:
+            self.info_label.setText("尚未設定 Pipeline，請先在 Pipeline Editor 中建立 Stage。")
+            self.start_button.setEnabled(False)
+        else:
+            self.info_label.setText(f"已載入 {len(self._pipeline_config)} 個 Stage，可開始 Benchmark。")
+            self.start_button.setEnabled(True)
+
+    def start_benchmark(self, benchmarker: Any) -> None:
+        """在 QThread 中執行 benchmark，避免 UI 凍結。
+
+        Args:
+            benchmarker: PerformanceBenchmarker 實例。
+        """
+        self._worker = _BenchmarkWorker(benchmarker)
+        self._worker.progress_updated.connect(self.update_progress)
+        self._worker.result_ready.connect(self._on_result_ready)
+        self._worker.error_occurred.connect(self._on_error)
+        self._worker.finished.connect(self._worker.deleteLater)
+        self.start_button.setEnabled(False)
+        self._worker.start()
+
+    def update_progress(self, phase: str, value: int) -> None:
+        """更新進度條與當前階段。
+
+        Args:
+            phase: 當前階段名稱（"warmup" / "sequential" / "parallel"）。
+            value: 進度值（0–100）。
+        """
+        _PHASE_LABELS = {
+            "warmup": "熱機中...",
+            "sequential": "循序測試...",
+            "parallel": "平行測試...",
+        }
+        self.current_phase = phase
+        self.progress_bar.setValue(value)
+        self.phase_label.setText(_PHASE_LABELS.get(phase, phase))
+
+    def show_result(
+        self,
+        seq_result: Any,
+        par_result: Any,
+        speedup: float,
+    ) -> None:
+        """顯示 benchmark 結果。
+
+        Args:
+            seq_result: 循序模式的 BenchmarkResult。
+            par_result: 平行模式的 BenchmarkResult。
+            speedup: 加速倍數（par.fps / seq.fps）。
+        """
+        self.seq_result = seq_result
+        self.par_result = par_result
+
+        font = self.speedup_label.font()
+        font.setPointSize(20)
+        font.setBold(True)
+        self.speedup_label.setFont(font)
+        self.speedup_label.setText(f"{speedup:.1f}x FASTER")
+        self._populate_table(seq_result, par_result)
+
+    def _populate_table(self, seq_result: Any, par_result: Any) -> None:
+        rows = [
+            ("循序", seq_result),
+            ("平行", par_result),
+        ]
+        for row_idx, (mode_label, result) in enumerate(rows):
+            self.result_table.setItem(row_idx, 0, QTableWidgetItem(mode_label))
+            try:
+                self.result_table.setItem(row_idx, 1, QTableWidgetItem(f"{result.fps:.1f}"))
+                self.result_table.setItem(
+                    row_idx, 2, QTableWidgetItem(f"{result.avg_latency_ms:.1f}")
+                )
+            except (AttributeError, TypeError):
+                pass
+
+    def _on_result_ready(
+        self,
+        seq_result: Any,
+        par_result: Any,
+        speedup: float,
+    ) -> None:
+        self.show_result(seq_result, par_result, speedup)
+
+    def _on_error(self, message: str) -> None:
+        self.info_label.setText(f"Benchmark 失敗：{message}")
+        self.progress_bar.setValue(0)
+        self._worker = None
+        self.start_button.setEnabled(True)

ui/dialogs/export_report_dialog.py

@@ -0,0 +1,238 @@
+"""
+ui/dialogs/export_report_dialog.py — 效能報告匯出對話框。
+
+提供 ExportReportDialog(QDialog)，讓使用者選擇報告格式（PDF/CSV）與儲存路徑，
+然後觸發 ReportExporter 執行匯出。
+
+設計重點：
+- _collect_report_data() 從各模組收集資料，每個來源都用 try/except 保護。
+- 不在此模組執行實際 benchmark，只使用 history 的最新一筆作為 parallel_result。
+- chart_image_bytes 留 None（截圖整合留未來）。
+"""
+
+from __future__ import annotations
+
+from typing import TYPE_CHECKING, List, Optional
+
+from PyQt5.QtWidgets import (
+    QDialog,
+    QFileDialog,
+    QHBoxLayout,
+    QLabel,
+    QPushButton,
+    QRadioButton,
+    QVBoxLayout,
+    QWidget,
+    QLineEdit,
+    QGroupBox,
+    QProgressBar,
+)
+from PyQt5.QtCore import Qt
+
+from core.performance.report_exporter import DeviceSummary, ReportData, ReportExporter
+
+if TYPE_CHECKING:
+    from core.performance.benchmarker import PerformanceBenchmarker
+    from core.performance.history import PerformanceHistory
+
+
+class ExportReportDialog(QDialog):
+    """
+    效能報告匯出對話框。
+
+    使用者可選擇格式（PDF / CSV），指定儲存路徑後按匯出，
+    對話框會呼叫 ReportExporter 產出檔案並顯示結果。
+    """
+
+    def __init__(
+        self,
+        parent: Optional[QWidget],
+        benchmarker,                # PerformanceBenchmarker | None
+        history,                    # PerformanceHistory | None
+        device_manager,             # DeviceManager | None
+        dashboard,                  # PerformanceDashboard | None
+    ) -> None:
+        super().__init__(parent)
+
+        self._benchmarker = benchmarker
+        self._history = history
+        self._device_manager = device_manager
+        self._dashboard = dashboard
+        self._exporter = ReportExporter()
+
+        # 預設格式為 PDF
+        self._selected_format: str = "pdf"
+
+        self._setup_ui()
+
+    # ------------------------------------------------------------------
+    # UI 建立
+    # ------------------------------------------------------------------
+
+    def _setup_ui(self) -> None:
+        """建立對話框 UI。"""
+        self.setWindowTitle("匯出效能報告")
+
+        main_layout = QVBoxLayout()
+
+        # 格式選擇
+        format_group = QGroupBox("匯出格式")
+        format_layout = QHBoxLayout()
+
+        self._pdf_radio = QRadioButton("PDF")
+        self._csv_radio = QRadioButton("CSV")
+        self._pdf_radio.setChecked(True)
+        self._pdf_radio.clicked.connect(lambda: self._set_format("pdf"))
+        self._csv_radio.clicked.connect(lambda: self._set_format("csv"))
+
+        format_layout.addWidget(self._pdf_radio)
+        format_layout.addWidget(self._csv_radio)
+        format_group.setLayout(format_layout)
+        main_layout.addWidget(format_group)
+
+        # 儲存路徑
+        path_layout = QHBoxLayout()
+        self._path_input = QLineEdit()
+        self._path_input.setPlaceholderText("儲存路徑…")
+        self._browse_btn = QPushButton("瀏覽")
+        self._browse_btn.clicked.connect(self._on_browse)
+        path_layout.addWidget(self._path_input)
+        path_layout.addWidget(self._browse_btn)
+        main_layout.addLayout(path_layout)
+
+        # 進度條
+        self._progress_bar = QProgressBar()
+        self._progress_bar.setVisible(False)
+        main_layout.addWidget(self._progress_bar)
+
+        # 匯出按鈕
+        self._export_btn = QPushButton("匯出")
+        self._export_btn.clicked.connect(self._on_export)
+        main_layout.addWidget(self._export_btn)
+
+        # 狀態標籤
+        self._status_label = QLabel("")
+        main_layout.addWidget(self._status_label)
+
+        self.setLayout(main_layout)
+
+    # ------------------------------------------------------------------
+    # 格式設定
+    # ------------------------------------------------------------------
+
+    def _set_format(self, fmt: str) -> None:
+        """設定匯出格式（'pdf' 或 'csv'）。"""
+        self._selected_format = fmt
+
+    # ------------------------------------------------------------------
+    # 事件處理
+    # ------------------------------------------------------------------
+
+    def _on_browse(self) -> None:
+        """開啟 QFileDialog 讓使用者選擇儲存路徑。"""
+        if self._selected_format == "pdf":
+            file_filter = "PDF 檔案 (*.pdf)"
+            default_suffix = ".pdf"
+        else:
+            file_filter = "CSV 檔案 (*.csv)"
+            default_suffix = ".csv"
+
+        path, _ = QFileDialog.getSaveFileName(
+            self,
+            "選擇儲存位置",
+            f"performance_report{default_suffix}",
+            file_filter,
+        )
+        if path:
+            self._path_input.setText(path)
+
+    def _on_export(self) -> None:
+        """執行匯出：收集資料 -> 呼叫 ReportExporter。"""
+        output_path = self._path_input.text().strip()
+        if not output_path:
+            self._status_label.setText("請先指定儲存路徑。")
+            return
+
+        data = self._collect_report_data()
+
+        try:
+            if self._selected_format == "pdf":
+                result = self._exporter.export_pdf(data, output_path)
+            else:
+                result = self._exporter.export_csv(data, output_path)
+            self._status_label.setText(f"匯出成功：{result}")
+        except ImportError as e:
+            self._status_label.setText(f"匯出失敗（缺少函式庫）：{e}")
+        except ValueError as e:
+            self._status_label.setText(f"匯出失敗（資料不足）：{e}")
+        except Exception as e:
+            self._status_label.setText(f"匯出失敗：{e}")
+
+    # ------------------------------------------------------------------
+    # 資料收集
+    # ------------------------------------------------------------------
+
+    def _collect_report_data(self) -> ReportData:
+        """
+        從各模組收集資料，組裝 ReportData。
+        每個來源都用 try/except 保護，失敗時使用 None / 空值。
+        不實際執行 benchmark，只使用 history 的最新一筆作為 parallel_result。
+        """
+        # 歷史記錄，同時從中取最近一筆 sequential / parallel 作為 result
+        history_records: list = []
+        seq_result = None
+        par_result = None
+        try:
+            records = self._history.get_history(limit=20) if self._history else []
+            history_records = list(records) if records else []
+            seq_result = next((r for r in history_records if r.mode == "sequential"), None)
+            par_result = next((r for r in history_records if r.mode == "parallel"), None)
+        except Exception:
+            history_records, seq_result, par_result = [], None, None
+
+        # 從 benchmarker.history 取最新一筆作為 parallel_result（fallback，不執行新的 benchmark）
+        if par_result is None:
+            try:
+                if self._benchmarker is not None:
+                    hist = self._benchmarker.history
+                    if hist:
+                        par_result = hist[-1]
+            except Exception:
+                par_result = None
+
+        # 裝置資訊
+        devices: List[DeviceSummary] = []
+        try:
+            if self._device_manager is not None:
+                raw_devices = self._device_manager.scan_devices() or []
+                devices = self._convert_devices(raw_devices)
+        except Exception:
+            devices = []
+
+        return ReportData(
+            sequential_result=seq_result,
+            parallel_result=par_result,
+            speedup=None,
+            history_records=history_records,
+            devices=devices,
+            chart_image_bytes=None,          # 截圖整合留未來
+        )
+
+    @staticmethod
+    def _convert_devices(raw_devices: list) -> List[DeviceSummary]:
+        """
+        將 DeviceManager 回傳的裝置列表轉換為 DeviceSummary 列表。
+        若轉換失敗，略過該裝置。
+        """
+        result: List[DeviceSummary] = []
+        for dev in raw_devices:
+            try:
+                result.append(DeviceSummary(
+                    device_id=str(getattr(dev, "device_id", getattr(dev, "id", "unknown"))),
+                    product_name=str(getattr(dev, "product_name", getattr(dev, "model", "unknown"))),
+                    firmware_version=str(getattr(dev, "firmware_version", "unknown")),
+                    is_active=bool(getattr(dev, "is_active", True)),
+                ))
+            except Exception:
+                continue
+        return result