config/dd06-ov.json

@@ -0,0 +1,101 @@
+{
+  "name": "dd06-ov",
+  "type": "single_camera",
+  "version": "1.0",
+  "camera": {
+    "resolution_raw": [
+      1280,
+      720
+    ],
+    "fps": 30,
+    "resolution_stitch": [
+      390,
+      550
+    ],
+    "source_scale": 0.4,
+    "old": [
+      672,
+      728,
+      1,
+      0.5
+    ],
+    "work": [
+      504,
+      546,
+      1
+    ],
+    "work2": [
+      420,
+      450,
+      0.8
+    ],
+    "work3": [
+      350,
+      375,
+      4,
+      0.7
+    ],
+    "work4": [
+      280,
+      300,
+      4,
+      0.4,
+      0.2
+    ]
+  },
+  "tracker": {
+    "adaptive": true,
+    "lower_threshold": 12.0,
+    "upper_threshold": 18.0,
+    "loop_closure_interval": 1,
+    "algorithm": "dis",
+    "dis_preset": "medium",
+    "dis_mode": 3,
+    "algorithm_list": [
+      "raft",
+      "dis"
+    ],
+    "hhd_downsample": 1
+  },
+  "contact": {
+    "min_contour_area": 3000,
+    "flow_threshold": 0.2,
+    "div_threshold": 0.022,
+    "expansion_threshold": 0.01,
+    "kernel_size": [
+      5,
+      5
+    ],
+    "denoise_sigma": 12
+  },
+  "roi": {
+    "type": "polygon",
+    "image_size": [
+      1280,
+      720
+    ],
+    "created_at": "2026-07-26T11:56:15",
+    "points": [
+      [
+        242,
+        1
+      ],
+      [
+        402,
+        597
+      ],
+      [
+        799,
+        606
+      ],
+      [
+        976,
+        2
+      ]
+    ],
+    "mask_path": "dd06-ov_mask.png",
+    "metadata": {
+      "source": "./data/dd06/0726.mp4"
+    }
+  }
+}

examples/gui/__init__.py

@@ -1,20 +1,29 @@
-"""Public GUI entry points for finger examples."""
+"""Public GUI entry points for Orisys example apps.
 
-from .dashboard import FingerDashboardWindow, run_dashboard
+Two apps live under ``examples/gui``:
-from .layout import (
+
-    LOG_CONFIG,
+- Finger 3D dashboard: ``from gui import run_dashboard`` (also ``gui.viewer3d``)
-    LOG_PANEL,
+- 2D sensor monitor: ``from gui.viewer2d import run_viewer``
+
+Acquisition adapters (no widgets) live in ``gui.sensors``.
+Shared bootstrap: ``gui.app``, ``gui.app_paths``, ``gui.log_config``, ``gui.widgets``.
+"""
+
+from .log_config import LOG_CONFIG, LogConfig
+from .viewer3d import (
+    FingerDashboardWindow,
     LAYOUT,
+    LOG_PANEL,
     MESH_CONTACT_ARROW,
     MESH_LIGHTING,
     PANEL_SETUP,
     TOP_ROW,
     DashboardLayout,
-    LogConfig,
     MeshLighting,
     PanelRow,
     PanelSetup,
     PanelSlot,
+    run_dashboard,
     top_row_splitter_sizes,
     top_row_slot_index,
 )

examples/gui/log_config.py

@@ -0,0 +1,52 @@
+"""Shared log-panel configuration for Qt viewers (2D and 3D)."""
+
+from __future__ import annotations
+
+from dataclasses import dataclass
+
+
+@dataclass(frozen=True)
+class LogConfig:
+    """Log panel — edit LOG_CONFIG or DashboardLayout.log_config."""
+
+    status_enabled: bool = True
+    max_lines: int = 2000
+    font_family: str = "Cascadia Mono"
+    font_pt: int = 12
+    show_flow: bool = True
+    show_mask: bool = True
+
+    def format_status(
+        self,
+        *,
+        fps: float,
+        fnormal: float,
+        fshearx: float,
+        fsheary: float,
+        flow_rms: float = 0.0,
+        mask_coverage: float = 0.0,
+        wall_fps: float | None = None,
+        contact_xyz_mm: tuple[float, float, float] | None = None,
+    ) -> str:
+        shear_mag = float((fshearx**2 + fsheary**2) ** 0.5)
+        if wall_fps is not None:
+            parts = [f"FPS={wall_fps:.1f}", f"sdk={fps:.1f}"]
+        else:
+            parts = [f"FPS={fps:.1f}"]
+        parts.extend(
+            [
+                f"Fn={fnormal:.1f}",
+                f"|(Fx,Fy)|={shear_mag:.1f}",
+                f"Fx, Fy=({fshearx:.1f}, {fsheary:.1f})",
+            ]
+        )
+        force_line = "  ".join(parts)
+        if contact_xyz_mm is None:
+            contact_line = "contact=---"
+        else:
+            cx, cy, cz = contact_xyz_mm
+            contact_line = f"contact=({cx:.1f}, {cy:.1f}, {cz:.1f}) mm"
+        return f"{force_line}\n{contact_line}"
+
+
+LOG_CONFIG = LogConfig()

examples/gui/preference.json

@@ -1,5 +1,5 @@
 {
-  "video_source": "0",
+  "video_source": "D:/repo/orisys-sdk/data/dd02-0703/1.mp4",
   "config_path": "./config/dd02-ov.json",
   "finger_assets_dir": "D:/repo/orisys-sdk/assets/finger/30fps-0703",
   "csv_save_dir": "./outputs/csv",

examples/gui/sensors/__init__.py

@@ -0,0 +1,23 @@
+"""Sensor acquisition adapters for Qt / multi-sensor viewers (no Qt widgets)."""
+
+from .adapter import (
+    Dd06RoiAdapter,
+    FrameSnapshot,
+    OrisysSensorAdapter,
+    SensorAdapter,
+    calibrate_normal_force,
+    create_sensor_adapter,
+    _snapshot_from_sensor,
+)
+from . import roi_geometry
+
+__all__ = [
+    "Dd06RoiAdapter",
+    "FrameSnapshot",
+    "OrisysSensorAdapter",
+    "SensorAdapter",
+    "calibrate_normal_force",
+    "create_sensor_adapter",
+    "roi_geometry",
+    "_snapshot_from_sensor",
+]

examples/gui/sensors/adapter.py

@@ -0,0 +1,330 @@
+"""Sensor adapters that normalize frames for Qt / multi-sensor viewers."""
+
+from __future__ import annotations
+
+import time
+from abc import ABC, abstractmethod
+from dataclasses import dataclass
+from pathlib import Path
+from typing import Any, Optional
+
+import cv2
+import numpy as np
+import orisys
+
+from .roi_geometry import (
+    build_roi_warp,
+    load_json_config,
+    load_roi_polygon,
+    open_video_source,
+    rectified_output_size,
+    warp_roi_to_rectangle,
+)
+
+
+NORMAL_FORCE_CAL_SLOPE = 3.92685554668795e-05
+NORMAL_FORCE_CAL_OFFSET = 0.0217596967278535
+
+
+@dataclass
+class FrameSnapshot:
+    """Normalized per-frame payload consumed by the Qt viewer."""
+
+    image: Optional[np.ndarray] = None
+    flow: Optional[np.ndarray] = None
+    depth: Optional[np.ndarray] = None
+    contour: Optional[np.ndarray] = None
+    centroid: Any = None
+    # Raw SDK force channels used for curves (same units for FN/FX/FY).
+    normal_force: float = 0.0
+    shear_x: float = 0.0
+    shear_y: float = 0.0
+    # Optional calibrated FN in Newtons for export/display overlays.
+    normal_force_calibrated: float = 0.0
+    fps: float = 0.0
+    timestamp: float = 0.0
+    raw_image: Optional[np.ndarray] = None
+    processed_image: Optional[np.ndarray] = None
+    flow_overlay: Optional[np.ndarray] = None
+    record_frame: Optional[np.ndarray] = None
+
+
+def calibrate_normal_force(raw_value: float) -> float:
+    """Convert raw normal-force reading to Newtons using y = mx + c."""
+    return NORMAL_FORCE_CAL_SLOPE * float(raw_value) + NORMAL_FORCE_CAL_OFFSET
+
+
+class SensorAdapter(ABC):
+    """Common interface between Qt and concrete sensor backends."""
+
+    @abstractmethod
+    def start(self) -> None:
+        raise NotImplementedError
+
+    @abstractmethod
+    def read(self) -> Optional[FrameSnapshot]:
+        raise NotImplementedError
+
+    @abstractmethod
+    def reset(self) -> None:
+        raise NotImplementedError
+
+    @abstractmethod
+    def close(self) -> None:
+        raise NotImplementedError
+
+
+def _bgr_from_gray_or_bgr(img: np.ndarray) -> np.ndarray:
+    if img is None:
+        return None
+    if img.ndim == 2:
+        return cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
+    if img.ndim == 3 and img.shape[2] == 1:
+        return cv2.cvtColor(img[:, :, 0], cv2.COLOR_GRAY2BGR)
+    return img
+
+
+def _snapshot_from_sensor(
+    sensor,
+    *,
+    raw_image=None,
+    processed_image=None,
+) -> Optional[FrameSnapshot]:
+    """Build a FrameSnapshot with HHD/forces refreshed every frame."""
+    if sensor is None or sensor.img is None:
+        return None
+
+    # Always decompose so FN/FX/FY update every frame (motion gating freezes forces).
+    sensor.compute_deformation(decompose=True, check_motion=False)
+    sensor.compute_contact()
+
+    fps, flow, vnormal, img, contour, centroid, depth_map, fnormal, fshearx, fsheary = (
+        sensor.read_info(
+            sensor.info.FPS,
+            sensor.info.VRAW,
+            sensor.info.VNORMAL,
+            sensor.info.IMG,
+            sensor.info.CONTOUR,
+            sensor.info.CENTROID,
+            sensor.info.DEPTH,
+            sensor.info.FNORMAL,
+            sensor.info.FSHEARX,
+            sensor.info.FSHEARY,
+        )
+    )
+
+    image_bgr = _bgr_from_gray_or_bgr(img)
+    processed = processed_image if processed_image is not None else image_bgr
+    record = None
+    if getattr(sensor, "frame", None) is not None:
+        record = _bgr_from_gray_or_bgr(sensor.frame)
+    elif processed is not None:
+        record = processed
+
+    flow_overlay = None
+    if image_bgr is not None and flow is not None:
+        flow_overlay = orisys.util.draw_arrows(
+            image_bgr,
+            flow,
+            threshold=2,
+            grid_spacing=20,
+            arrow_scale=0.5,
+            below_threshold_color=(160, 160, 160),
+        )
+
+    fn_raw = float(fnormal)
+    return FrameSnapshot(
+        image=image_bgr,
+        flow=flow,
+        depth=depth_map,
+        contour=contour,
+        centroid=centroid,
+        normal_force=fn_raw,
+        shear_x=float(fshearx),
+        shear_y=float(fsheary),
+        normal_force_calibrated=calibrate_normal_force(fn_raw),
+        fps=float(fps),
+        timestamp=time.time(),
+        raw_image=raw_image,
+        processed_image=processed,
+        flow_overlay=flow_overlay,
+        record_frame=record,
+    )
+
+
+class OrisysSensorAdapter(SensorAdapter):
+    """Direct orisys.Sensor capture path (compound-eye / single-camera)."""
+
+    def __init__(
+        self,
+        video,
+        config_name,
+        cal_path=None,
+        verbose=True,
+        *,
+        rotate_ccw90=False,
+        motion_threshold=1,
+    ):
+        self.video = video
+        self.config_name = config_name
+        self.cal_path = cal_path
+        self.verbose = verbose
+        self.rotate_ccw90 = bool(rotate_ccw90)
+        self.motion_threshold = motion_threshold
+        self.sensor = None
+
+    def start(self) -> None:
+        src = self.video
+        try:
+            src = int(str(src).strip())
+        except (TypeError, ValueError):
+            pass
+        self.sensor = orisys.Sensor(
+            src,
+            config_name=self.config_name,
+            cal_path=self.cal_path,
+            verbose=self.verbose,
+        )
+
+    def read(self) -> Optional[FrameSnapshot]:
+        if self.sensor is None:
+            return None
+        img = self.sensor.get_img()
+        if img is None:
+            return None
+
+        if self.rotate_ccw90:
+            self.sensor.img = cv2.rotate(self.sensor.img, cv2.ROTATE_90_COUNTERCLOCKWISE)
+            if self.sensor.frame is not None:
+                self.sensor.frame = cv2.rotate(
+                    self.sensor.frame, cv2.ROTATE_90_COUNTERCLOCKWISE
+                )
+
+        return _snapshot_from_sensor(
+            self.sensor,
+            raw_image=_bgr_from_gray_or_bgr(self.sensor.frame)
+            if self.sensor.frame is not None
+            else None,
+            processed_image=_bgr_from_gray_or_bgr(self.sensor.img),
+        )
+
+    def reset(self) -> None:
+        if self.sensor is not None:
+            self.sensor.reset()
+
+    def close(self) -> None:
+        if self.sensor is not None:
+            self.sensor.disconnect()
+            self.sensor = None
+
+
+class Dd06RoiAdapter(SensorAdapter):
+    """DD06 path: external capture + polygon ROI rectify + already_processed Sensor."""
+
+    def __init__(self, video, config_name, verbose=True, *, motion_threshold=0):
+        self.video = video
+        self.config_name = config_name
+        self.verbose = verbose
+        self.motion_threshold = motion_threshold
+        self.sensor = None
+        self.cap = None
+        self.roi_points = None
+        self.roi_image_size = None
+        self.out_size = None
+        self.warp_matrix = None
+        self.warp_src = None
+        self.last_frame_size = None
+        self._source = None
+
+    def start(self) -> None:
+        config = load_json_config(self.config_name)
+        self.roi_points, self.roi_image_size = load_roi_polygon(config)
+        self.out_size = rectified_output_size(config, self.roi_points)
+        self.sensor = orisys.Sensor(
+            "external",
+            config_name=self.config_name,
+            verbose=self.verbose,
+        )
+        self.cap, self._source = open_video_source(self.video)
+        self.warp_matrix = None
+        self.last_frame_size = None
+        if self.verbose:
+            print(
+                f"DD06 adapter: ROI points={len(self.roi_points)} "
+                f"source_size={self.roi_image_size} output={self.out_size} "
+                f"video={self._source}"
+            )
+
+    def read(self) -> Optional[FrameSnapshot]:
+        if self.sensor is None or self.cap is None:
+            return None
+
+        ok, frame = self.cap.read()
+        if not ok or frame is None:
+            return None
+
+        frame_h, frame_w = frame.shape[:2]
+        frame_size = (frame_w, frame_h)
+        if self.warp_matrix is None or self.last_frame_size != frame_size:
+            self.warp_matrix, self.warp_src, _ = build_roi_warp(
+                self.roi_points,
+                self.roi_image_size,
+                frame_size,
+                self.out_size,
+            )
+            self.last_frame_size = frame_size
+            if self.verbose:
+                print(f"Built ROI warp for frame {frame_w}x{frame_h}")
+
+        rectified = warp_roi_to_rectangle(frame, self.warp_matrix, self.out_size)
+        self.sensor.get_img(frame=rectified, already_processed=True)
+        return _snapshot_from_sensor(
+            self.sensor,
+            raw_image=frame,
+            processed_image=rectified,
+        )
+
+    def reset(self) -> None:
+        if self.sensor is not None:
+            self.sensor.reset()
+
+    def close(self) -> None:
+        if self.cap is not None:
+            self.cap.release()
+            self.cap = None
+        if self.sensor is not None:
+            self.sensor.disconnect()
+            self.sensor = None
+
+
+def create_sensor_adapter(
+    sensor_type: str,
+    *,
+    video,
+    config_name,
+    cal_path=None,
+    verbose=True,
+) -> SensorAdapter:
+    """Factory for Qt / demo viewers."""
+    kind = str(sensor_type or "orisys").strip().lower()
+    if kind in ("orisys", "direct", "default", "compound_eye", "single_camera"):
+        # Preserve historical Wuxi viewer rotation for compound-eye demos.
+        rotate = kind in ("orisys", "direct", "default", "compound_eye")
+        return OrisysSensorAdapter(
+            video,
+            config_name,
+            cal_path=cal_path,
+            verbose=verbose,
+            rotate_ccw90=rotate,
+            motion_threshold=1,
+        )
+    if kind in ("dd06", "dd06-ov", "roi", "polygon_roi"):
+        return Dd06RoiAdapter(
+            video,
+            config_name,
+            verbose=verbose,
+            motion_threshold=0,
+        )
+    raise ValueError(
+        f"Unknown sensor_type={sensor_type!r}; expected 'orisys' or 'dd06'"
+    )

examples/gui/sensors/roi_geometry.py

@@ -0,0 +1,140 @@
+"""Polygon ROI geometry helpers for rectifying tactile sensor frames."""
+
+from __future__ import annotations
+
+import json
+from pathlib import Path
+
+import cv2
+import numpy as np
+
+
+def load_json_config(path):
+    path = Path(path)
+    with path.open("r", encoding="utf-8") as f:
+        return json.load(f)
+
+
+def load_roi_polygon(config):
+    """Return (points Nx2 float32, image_size [w,h]) from nested or legacy ROI fields."""
+    roi = config.get("roi") if isinstance(config.get("roi"), dict) else config
+    if not isinstance(roi, dict):
+        raise ValueError("Config has no usable ROI section")
+
+    image_size = roi.get("image_size") or config.get("camera", {}).get("resolution_raw")
+    if image_size is None:
+        raise ValueError("ROI image_size is missing")
+
+    points = roi.get("points") or roi.get("polygon") or roi.get("roi_polygon")
+    if points is None and roi.get("xyxy") is not None:
+        x1, y1, x2, y2 = [int(v) for v in roi["xyxy"]]
+        points = [[x1, y1], [x2, y1], [x2, y2], [x1, y2]]
+    if not points:
+        raise ValueError("ROI points are missing")
+
+    pts = np.asarray(points, dtype=np.float32).reshape(-1, 2)
+    if pts.shape[0] < 4:
+        raise ValueError(f"ROI needs at least 4 points, got {pts.shape[0]}")
+    return pts, [int(image_size[0]), int(image_size[1])]
+
+
+def scale_points(points, source_size, target_size):
+    source_w, source_h = float(source_size[0]), float(source_size[1])
+    target_w, target_h = float(target_size[0]), float(target_size[1])
+    pts = np.asarray(points, dtype=np.float32).reshape(-1, 2).copy()
+    if source_w > 0 and source_h > 0 and (source_w, source_h) != (target_w, target_h):
+        pts[:, 0] *= target_w / source_w
+        pts[:, 1] *= target_h / source_h
+    return pts
+
+
+def order_quad_points(points):
+    """Order 4 points as TL, TR, BR, BL for perspective transforms."""
+    pts = np.asarray(points, dtype=np.float32).reshape(-1, 2)
+    if pts.shape[0] != 4:
+        hull = cv2.convexHull(pts.astype(np.float32))
+        rect = cv2.minAreaRect(hull)
+        pts = cv2.boxPoints(rect).astype(np.float32)
+
+    s = pts.sum(axis=1)
+    diff = np.diff(pts, axis=1).reshape(-1)
+    ordered = np.zeros((4, 2), dtype=np.float32)
+    ordered[0] = pts[np.argmin(s)]  # top-left
+    ordered[2] = pts[np.argmax(s)]  # bottom-right
+    ordered[1] = pts[np.argmin(diff)]  # top-right
+    ordered[3] = pts[np.argmax(diff)]  # bottom-left
+    return ordered
+
+
+def rectified_output_size(config, points=None):
+    """Prefer camera.resolution_stitch; fall back to ROI bounding box size."""
+    stitch = config.get("camera", {}).get("resolution_stitch")
+    if stitch is not None and len(stitch) >= 2:
+        return int(stitch[0]), int(stitch[1])
+    if points is not None:
+        pts = np.asarray(points, dtype=np.float32).reshape(-1, 2)
+        width = max(
+            int(np.linalg.norm(pts[1] - pts[0])),
+            int(np.linalg.norm(pts[2] - pts[3])),
+            1,
+        )
+        height = max(
+            int(np.linalg.norm(pts[3] - pts[0])),
+            int(np.linalg.norm(pts[2] - pts[1])),
+            1,
+        )
+        return width, height
+    raise ValueError("Cannot determine rectified output size")
+
+
+def build_roi_warp(points, source_image_size, frame_size, output_size):
+    """
+    Build a perspective transform that maps the ROI polygon in frame coords
+    onto a rectangle of ``output_size`` (width, height).
+    """
+    frame_w, frame_h = int(frame_size[0]), int(frame_size[1])
+    scaled = scale_points(points, source_image_size, (frame_w, frame_h))
+    src = order_quad_points(scaled)
+    out_w, out_h = int(output_size[0]), int(output_size[1])
+    dst = np.array(
+        [
+            [0.0, 0.0],
+            [out_w - 1.0, 0.0],
+            [out_w - 1.0, out_h - 1.0],
+            [0.0, out_h - 1.0],
+        ],
+        dtype=np.float32,
+    )
+    matrix = cv2.getPerspectiveTransform(src, dst)
+    return matrix, src, (out_w, out_h)
+
+
+def warp_roi_to_rectangle(frame, matrix, output_size):
+    out_w, out_h = int(output_size[0]), int(output_size[1])
+    return cv2.warpPerspective(
+        frame,
+        matrix,
+        (out_w, out_h),
+        flags=cv2.INTER_LINEAR,
+        borderMode=cv2.BORDER_REPLICATE,
+    )
+
+
+def open_video_source(video):
+    """Open a camera index or video file. Returns (cap, resolved_source)."""
+    text = str(video).strip()
+    if text.isdigit():
+        source = int(text)
+        cap = cv2.VideoCapture(source, cv2.CAP_DSHOW)
+        if not cap.isOpened():
+            cap.release()
+            cap = cv2.VideoCapture(source)
+    else:
+        path = Path(text)
+        if not path.exists():
+            raise FileNotFoundError(f"Video not found: {path}")
+        source = str(path)
+        cap = cv2.VideoCapture(source)
+    if not cap.isOpened():
+        raise RuntimeError(f"Failed to open video source: {video}")
+    return cap, source

examples/gui/viewer2d/__init__.py

@@ -0,0 +1,24 @@
+"""2D Qt sensor monitor (image + force curves; no finger 3D mesh)."""
+
+from .backend import (
+    ForceHistory,
+    ForcePlotState,
+    QtViewerBackend,
+    ViewerFrame,
+    image_shape_meta,
+    panel_width_for_aspect,
+    select_display_image,
+)
+from .window import QtViewerWindow, run_viewer
+
+__all__ = [
+    "ForceHistory",
+    "ForcePlotState",
+    "QtViewerBackend",
+    "QtViewerWindow",
+    "ViewerFrame",
+    "image_shape_meta",
+    "panel_width_for_aspect",
+    "run_viewer",
+    "select_display_image",
+]

examples/gui/viewer2d/backend.py

@@ -0,0 +1,312 @@
+"""Qt-facing display backend for sensor viewer snapshots.
+
+Separates acquisition (`gui.sensors.FrameSnapshot`) from Qt display state:
+normalized images, force history / filtering, and aspect-ratio metadata.
+Does not import camera, ROI, or `orisys.Sensor`.
+"""
+
+from __future__ import annotations
+
+from dataclasses import dataclass
+from typing import Optional, Sequence, Tuple
+
+import cv2
+import numpy as np
+from scipy.signal import butter, filtfilt
+
+FORCE_SAMPLE_RATE_HZ = 30.0
+PLOT_BUFFER_POINTS = 120
+PLOT_WINDOW_SEC = PLOT_BUFFER_POINTS / FORCE_SAMPLE_RATE_HZ
+Y_AXIS_MIN_SPAN = 20000.0
+
+
+@dataclass
+class ViewerFrame:
+    """Normalized display payload for one UI tick."""
+
+    display_image: np.ndarray
+    image_height: int
+    image_width: int
+    aspect_ratio: float  # width / height
+    depth: Optional[np.ndarray]
+    normal_force: float
+    shear_x: float
+    shear_y: float
+    normal_force_calibrated: float
+    fps: float
+    timestamp: float
+    record_frame: Optional[np.ndarray]
+
+
+@dataclass
+class ForcePlotState:
+    """Filtered force series ready for pyqtgraph curves."""
+
+    times: np.ndarray  # shape (n,)
+    values: np.ndarray  # shape (n, 3)  FN, FX, FY
+    sample_count: int
+    x_range: Tuple[float, float]
+    y_ranges: Tuple[Tuple[float, float], Tuple[float, float], Tuple[float, float]]
+
+
+def lowpass_filter(
+    data,
+    cutoff_hz: float,
+    sample_rate_hz: float = FORCE_SAMPLE_RATE_HZ,
+    order: int = 2,
+) -> np.ndarray:
+    """Zero-phase Butterworth low-pass for uniformly sampled 1-D data."""
+    y = np.asarray(data, dtype=np.float64)
+    if cutoff_hz == 0:
+        return y.copy()
+    if y.size == 0:
+        return y
+
+    nyquist = 0.5 * sample_rate_hz
+    if cutoff_hz < 0 or cutoff_hz >= nyquist:
+        raise ValueError(
+            f"cutoff_hz must be in (0, {nyquist}) for sample_rate_hz={sample_rate_hz}"
+        )
+
+    b, a = butter(order, cutoff_hz / nyquist, btype="low")
+    padlen = 3 * (max(len(b), len(a)) - 1)
+    if y.size <= padlen:
+        return y.copy()
+    return filtfilt(b, a, y)
+
+
+def ensure_bgr(img: Optional[np.ndarray]) -> Optional[np.ndarray]:
+    if img is None:
+        return None
+    if img.ndim == 2:
+        return cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
+    if img.ndim == 3 and img.shape[2] == 1:
+        return cv2.cvtColor(img[:, :, 0], cv2.COLOR_GRAY2BGR)
+    return img
+
+
+def image_shape_meta(img: np.ndarray) -> Tuple[int, int, float]:
+    """Return (height, width, width/height) from a display image."""
+    h, w = int(img.shape[0]), int(img.shape[1])
+    aspect = float(w) / float(h) if h > 0 else 1.0
+    return h, w, aspect
+
+
+def select_display_image(snapshot) -> np.ndarray:
+    """Pick flow overlay / processed / raw image for the left panel."""
+    arrows = getattr(snapshot, "flow_overlay", None)
+    if arrows is not None:
+        out = ensure_bgr(arrows)
+        if out is not None:
+            return out
+
+    for attr in ("processed_image", "image", "raw_image"):
+        base = getattr(snapshot, attr, None)
+        out = ensure_bgr(base)
+        if out is not None:
+            return out
+
+    return np.zeros((400, 400, 3), dtype=np.uint8)
+
+
+def bgr_to_rgb_bytes(img_bgr: np.ndarray) -> Tuple[np.ndarray, int, int]:
+    """Convert BGR uint8 image to contiguous RGB for QImage."""
+    rgb = cv2.cvtColor(img_bgr, cv2.COLOR_BGR2RGB)
+    if not rgb.flags["C_CONTIGUOUS"]:
+        rgb = np.ascontiguousarray(rgb)
+    h, w = rgb.shape[:2]
+    return rgb, h, w
+
+
+def scale_bgr_to_fit(
+    img_bgr: np.ndarray,
+    max_w: int,
+    max_h: int,
+) -> np.ndarray:
+    """Resize preserving aspect ratio to fit inside (max_w, max_h)."""
+    if max_w <= 0 or max_h <= 0:
+        return img_bgr
+    h, w = img_bgr.shape[:2]
+    if h <= 0 or w <= 0:
+        return img_bgr
+    scale = min(max_w / float(w), max_h / float(h))
+    if abs(scale - 1.0) < 1e-6:
+        return img_bgr
+    nw = max(1, int(round(w * scale)))
+    nh = max(1, int(round(h * scale)))
+    return cv2.resize(img_bgr, (nw, nh), interpolation=cv2.INTER_AREA)
+
+
+def panel_width_for_aspect(
+    available_height: int,
+    aspect_ratio: float,
+    *,
+    min_size: int = 160,
+) -> int:
+    """Preferred left-panel width given available height and image aspect."""
+    h = max(int(available_height), min_size)
+    w = int(round(h * float(aspect_ratio)))
+    return max(w, min_size)
+
+
+class ForceHistory:
+    """Ring-style force history buffer with filtering and y-range smoothing."""
+
+    def __init__(
+        self,
+        npoints: int = PLOT_BUFFER_POINTS,
+        *,
+        sample_rate_hz: float = FORCE_SAMPLE_RATE_HZ,
+        lowpass_cutoff_hz: float = 10.0,
+        y_axis_min_span: float = Y_AXIS_MIN_SPAN,
+        y_range_alpha: float = 0.5,
+    ):
+        self.npoints = int(npoints)
+        self.sample_rate_hz = float(sample_rate_hz)
+        self.lowpass_cutoff_hz = float(lowpass_cutoff_hz)
+        self.y_axis_min_span = float(y_axis_min_span)
+        self.y_range_alpha = float(y_range_alpha)
+        self.window_sec = self.npoints / self.sample_rate_hz
+        self.reset()
+
+    def reset(self) -> None:
+        self.data = np.full((self.npoints, 2, 3), np.nan, dtype=np.float64)
+        self.sample_count = 0
+        self._y_range_smooth = [None, None, None]
+
+    def push(self, t: float, fn: float, fx: float, fy: float) -> None:
+        values = (float(fn), float(fx), float(fy))
+        if self.sample_count < self.npoints:
+            idx = self.sample_count
+            self.data[idx, 0, :] = t
+            self.data[idx, 1, :] = values
+            self.sample_count += 1
+            return
+
+        self.data[:-1, 0, :] = self.data[1:, 0, :]
+        self.data[:-1, 1, :] = self.data[1:, 1, :]
+        self.data[-1, 0, :] = t
+        self.data[-1, 1, :] = values
+
+    def _smooth_y_range(self, channel: int, ymin: float, ymax: float) -> Tuple[float, float]:
+        if self._y_range_smooth[channel] is None:
+            smoothed = (ymin, ymax)
+        else:
+            prev_min, prev_max = self._y_range_smooth[channel]
+            alpha = self.y_range_alpha
+            ymin = alpha * ymin + (1.0 - alpha) * prev_min
+            ymax = alpha * ymax + (1.0 - alpha) * prev_max
+            smoothed = (ymin, ymax)
+
+        span = smoothed[1] - smoothed[0]
+        if span < self.y_axis_min_span:
+            mid = 0.5 * (smoothed[0] + smoothed[1])
+            half = self.y_axis_min_span / 2.0
+            smoothed = (mid - half, mid + half)
+
+        self._y_range_smooth[channel] = smoothed
+        pad = max((smoothed[1] - smoothed[0]) * 0.12, 0.01)
+        return smoothed[0] - pad, smoothed[1] + pad
+
+    def plot_state(self) -> Optional[ForcePlotState]:
+        n = self.sample_count
+        if n == 0:
+            return None
+
+        data_plot = self.data[:n].copy()
+        for i in range(3):
+            data_plot[:, 1, i] = lowpass_filter(
+                data_plot[:, 1, i],
+                self.lowpass_cutoff_hz,
+                sample_rate_hz=self.sample_rate_hz,
+            )
+
+        times = data_plot[:, 0, 0].copy()
+        values = data_plot[:, 1, :].copy()
+        y_ranges = tuple(
+            self._smooth_y_range(i, float(values[:, i].min()), float(values[:, i].max()))
+            for i in range(3)
+        )
+
+        if n < self.npoints:
+            x_range = (0.0, self.window_sec)
+        else:
+            x0 = float(times[0])
+            x1 = float(times[-1])
+            if x1 <= x0:
+                x1 = x0 + self.window_sec
+            x_range = (x0, x1)
+
+        return ForcePlotState(
+            times=times,
+            values=values,
+            sample_count=n,
+            x_range=x_range,
+            y_ranges=y_ranges,  # type: ignore[arg-type]
+        )
+
+
+class QtViewerBackend:
+    """Normalize FrameSnapshot into display images + force history."""
+
+    def __init__(
+        self,
+        *,
+        npoints: int = PLOT_BUFFER_POINTS,
+        lowpass_cutoff_hz: float = 10.0,
+        y_axis_min_span: float = Y_AXIS_MIN_SPAN,
+    ):
+        self.force_history = ForceHistory(
+            npoints=npoints,
+            lowpass_cutoff_hz=lowpass_cutoff_hz,
+            y_axis_min_span=y_axis_min_span,
+        )
+        self._start_time: Optional[float] = None
+        self.last_viewer_frame: Optional[ViewerFrame] = None
+
+    def reset(self) -> None:
+        self.force_history.reset()
+        self._start_time = None
+        self.last_viewer_frame = None
+
+    def ingest(self, snapshot, *, now: Optional[float] = None) -> ViewerFrame:
+        """Convert a FrameSnapshot into ViewerFrame and update force history."""
+        display = select_display_image(snapshot)
+        h, w, aspect = image_shape_meta(display)
+
+        fn = float(getattr(snapshot, "normal_force", 0.0))
+        fx = float(getattr(snapshot, "shear_x", 0.0))
+        fy = float(getattr(snapshot, "shear_y", 0.0))
+        fn_cal = float(getattr(snapshot, "normal_force_calibrated", 0.0))
+        fps = float(getattr(snapshot, "fps", 0.0))
+        ts = float(getattr(snapshot, "timestamp", 0.0) or 0.0)
+        if now is None:
+            now = ts if ts > 0 else 0.0
+
+        if self._start_time is None:
+            self._start_time = now
+        t = now - self._start_time
+        self.force_history.push(t, fn, fx, fy)
+
+        record = ensure_bgr(getattr(snapshot, "record_frame", None))
+        depth = getattr(snapshot, "depth", None)
+
+        frame = ViewerFrame(
+            display_image=display,
+            image_height=h,
+            image_width=w,
+            aspect_ratio=aspect,
+            depth=depth,
+            normal_force=fn,
+            shear_x=fx,
+            shear_y=fy,
+            normal_force_calibrated=fn_cal,
+            fps=fps,
+            timestamp=ts,
+            record_frame=record,
+        )
+        self.last_viewer_frame = frame
+        return frame
+
+    def plot_state(self) -> Optional[ForcePlotState]:
+        return self.force_history.plot_state()

examples/gui/viewer2d/styles.py

@@ -0,0 +1,120 @@
+"""Styles for the 2D Qt sensor monitor."""
+
+CURVE_THEME_COLOR = "#00E5FF"
+
+STYLE = """
+QMainWindow {
+    background-color: #000000;
+}
+
+/* ---- 图像面板 ---- */
+QLabel#arrowsLabel {
+    border: 1px solid #262626;
+    border-radius: 4px;
+    background-color: #0b0b0b;
+}
+
+/* ---- 顶栏按钮 & 输入 ---- */
+QPushButton {
+    background-color: #1a1a1a;
+    color: #999999;
+    border: 1px solid #333333;
+    border-radius: 4px;
+    padding: 6px 16px;
+    font-family: "SimHei";
+    font-size: 13px;
+}
+QPushButton:hover {
+    background-color: #262626;
+    color: #cccccc;
+    border: 1px solid #555555;
+}
+QPushButton#btnStart {
+    background-color: #0d2818;
+    color: #4caf84;
+    border: 1px solid #1a4d30;
+}
+QPushButton#btnStart:hover {
+    background-color: #143d24;
+    color: #6fd4a0;
+}
+QPushButton#btnStart:disabled {
+    background-color: #0f0f0f;
+    color: #333333;
+    border: 1px solid #222222;
+}
+QPushButton#btnStop {
+    background-color: #2b1010;
+    color: #e05555;
+    border: 1px solid #4d1a1a;
+}
+QPushButton#btnStop:hover {
+    background-color: #3d1818;
+    color: #f07070;
+}
+QPushButton#btnStop:disabled {
+    background-color: #0f0f0f;
+    color: #333333;
+    border: 1px solid #222222;
+}
+QLineEdit {
+    background-color: #0d0d0d;
+    color: #999999;
+    border: 1px solid #333333;
+    border-radius: 4px;
+    padding: 5px 10px;
+    font-size: 13px;
+}
+
+/* ---- 力曲线容器 ---- */
+GraphicsLayoutWidget {
+    border: 1px solid #262626;
+    border-radius: 4px;
+}
+
+/* ---- 日志面板 ---- */
+QPlainTextEdit {
+    background-color: #0b0b0b;
+    color: #777777;
+    border: 1px solid #262626;
+    border-radius: 4px;
+    font-family: "Cascadia Code", "Consolas", "Courier New", monospace;
+    font-size: 13px;
+    padding: 8px;
+    selection-background-color: #1a3a4a;
+    selection-color: #cccccc;
+}
+
+QPlainTextEdit QScrollBar:vertical {
+    background-color: #0b0b0b;
+    width: 6px;
+    margin: 1px;
+    border-radius: 3px;
+}
+QPlainTextEdit QScrollBar::handle:vertical {
+    background-color: #262626;
+    border-radius: 3px;
+    min-height: 30px;
+}
+QPlainTextEdit QScrollBar::handle:vertical:hover {
+    background-color: #3a3a3a;
+}
+QPlainTextEdit QScrollBar::add-line:vertical,
+QPlainTextEdit QScrollBar::sub-line:vertical {
+    height: 0px;
+}
+QPlainTextEdit QScrollBar::add-page:vertical,
+QPlainTextEdit QScrollBar::sub-page:vertical {
+    background: none;
+}
+
+QSplitter::handle {
+    background-color: #1a1a1a;
+}
+QSplitter::handle:vertical {
+    height: 1px;
+}
+QSplitter::handle:horizontal {
+    width: 1px;
+}
+"""

examples/gui/viewer2d/window.py

@@ -0,0 +1,491 @@
+"""2D Qt sensor monitor window (image + force curves)."""
+
+from __future__ import annotations
+
+import os
+import sys
+import time
+from datetime import datetime
+from pathlib import Path
+
+import cv2
+from PyQt5.QtCore import Qt, QTimer
+from PyQt5.QtGui import QFont, QIcon
+from PyQt5.QtWidgets import (
+    QApplication,
+    QFileDialog,
+    QHBoxLayout,
+    QLabel,
+    QLineEdit,
+    QMainWindow,
+    QPushButton,
+    QSplitter,
+    QVBoxLayout,
+    QWidget,
+)
+
+try:
+    import pyqtgraph as pg
+except Exception as exc:  # pragma: no cover
+    raise ImportError(
+        "PyQtGraph is not installed. Please install it using 'pip install pyqt5 pyqtgraph'."
+    ) from exc
+
+from gui.sensors import create_sensor_adapter
+from gui.widgets.log_panel import TeeStream, WidgetLogHandler, make_log_widget
+from gui.widgets.qt_pixmap import ndarray_to_pixmap, pixmap_keep_aspect
+
+from .backend import PLOT_BUFFER_POINTS, PLOT_WINDOW_SEC, QtViewerBackend, panel_width_for_aspect
+from .styles import CURVE_THEME_COLOR, STYLE
+
+
+class QtViewerWindow(QMainWindow):
+    """2D monitor: flow/image panel + FN/FX/FY curves driven by QtViewerBackend."""
+
+    def __init__(self, args, log_file):
+        super().__init__()
+        self.setWindowTitle("Orisys SDK")
+        self.setStyleSheet(STYLE)
+
+        logo_path = Path(__file__).resolve().parents[3] / "logo.png"
+        if logo_path.exists():
+            self.setWindowIcon(QIcon(str(logo_path)))
+
+        self.sensor_adapter = None
+        self._last_snapshot = None
+        self._last_viewer_frame = None
+        self._display_aspect = 1.0
+        self._source_pixmap = None
+        self.args = args
+
+        self.is_save = False
+        self.frame_count = 0
+        self.writer = None
+        self.save_path = None
+
+        self.viewer_backend = QtViewerBackend(
+            npoints=PLOT_BUFFER_POINTS,
+            lowpass_cutoff_hz=getattr(args, "cutoff", 10.0),
+        )
+
+        self._setup_ui()
+        self._create_plots()
+
+        self.camera_edit.setText(args.video)
+        self.config_edit.setText(args.config)
+        self.cal_edit.setText(args.cal)
+
+        self.log_handler = WidgetLogHandler(self.log_widget)
+        sys.stdout = TeeStream(log_file, self.log_handler)
+        sys.stderr = sys.stdout
+
+        self.timer = QTimer()
+        self.timer.timeout.connect(self._on_timer)
+        self._running = False
+
+    def _setup_ui(self):
+        central = QWidget()
+        self.setCentralWidget(central)
+        root_layout = QVBoxLayout(central)
+        root_layout.setContentsMargins(6, 6, 6, 6)
+        root_layout.setSpacing(6)
+
+        bar = QHBoxLayout()
+        bar.setSpacing(8)
+
+        self.btn_camera = QPushButton("摄像机")
+        self.btn_camera.setObjectName("btnCamera")
+        self.btn_camera.clicked.connect(self._select_camera)
+        bar.addWidget(self.btn_camera)
+        self.camera_edit = QLineEdit("1")
+        self.camera_edit.setPlaceholderText("摄像头编号 或 视频路径")
+        bar.addWidget(self.camera_edit, 1)
+
+        self.btn_config = QPushButton("配置")
+        self.btn_config.setObjectName("btnConfig")
+        self.btn_config.clicked.connect(self._select_config)
+        bar.addWidget(self.btn_config)
+        self.config_edit = QLineEdit("./config/ddjx01.json")
+        bar.addWidget(self.config_edit, 1)
+
+        self.btn_reset = QPushButton("重置")
+        self.btn_reset.setObjectName("btnReset")
+        self.btn_reset.setEnabled(False)
+        self.btn_reset.clicked.connect(self._on_reset)
+        bar.addWidget(self.btn_reset)
+        self.cal_edit = QLineEdit("./config/ddjx01.npy")
+        bar.addWidget(self.cal_edit, 1)
+
+        self.btn_start = QPushButton("启动")
+        self.btn_start.setObjectName("btnStart")
+        self.btn_start.clicked.connect(self._on_start)
+        bar.addWidget(self.btn_start)
+
+        self.btn_stop = QPushButton("暂停")
+        self.btn_stop.setObjectName("btnStop")
+        self.btn_stop.setEnabled(False)
+        self.btn_stop.clicked.connect(self._on_stop)
+        bar.addWidget(self.btn_stop)
+
+        root_layout.addLayout(bar)
+
+        v_splitter = QSplitter(Qt.Vertical)
+        h_splitter = QSplitter(Qt.Horizontal)
+
+        left = QWidget()
+        left_layout = QVBoxLayout(left)
+        left_layout.setContentsMargins(0, 0, 0, 0)
+        left_layout.setSpacing(6)
+
+        self.arrows_label = QLabel()
+        self.arrows_label.setObjectName("arrowsLabel")
+        self.arrows_label.setMinimumSize(160, 160)
+        self.arrows_label.setScaledContents(False)
+        self.arrows_label.setAlignment(Qt.AlignCenter)
+        left_layout.addWidget(self.arrows_label)
+
+        h_splitter.addWidget(left)
+
+        pg.setConfigOption("background", "#000000")
+        pg.setConfigOption("foreground", "#777777")
+        pg.setConfigOptions(antialias=True)
+        self.graph_widget = pg.GraphicsLayoutWidget()
+        self.graph_widget.setMinimumWidth(300)
+        h_splitter.addWidget(self.graph_widget)
+
+        self.h_splitter = h_splitter
+        v_splitter.addWidget(h_splitter)
+
+        from gui.log_config import LOG_CONFIG
+
+        self.log_widget = make_log_widget(LOG_CONFIG)
+        v_splitter.addWidget(self.log_widget)
+
+        v_splitter.setStretchFactor(0, 4)
+        v_splitter.setStretchFactor(1, 1)
+        root_layout.addWidget(v_splitter)
+
+    def _create_plots(self):
+        titles = ["法向力 (raw)", "切向力 X", "切向力 Y"]
+        self.plots = []
+        self.curves = []
+        self.dot_glows = []
+        self.dot_cores = []
+
+        axis_pen = pg.mkPen(color=(38, 38, 38), width=1)
+        label_font = QFont("SimHei", 9)
+
+        for i, title in enumerate(titles):
+            p = self.graph_widget.addPlot(title=None)
+            p.setTitle(title, color="#999999", size="14pt")
+            p.titleLabel.setFont(QFont("SimHei", 14))
+            p.setLabel("bottom", "时间", units="s")
+            p.getAxis("bottom").label.setFont(label_font)
+            p.showAxis("top", False)
+            p.showAxis("right", False)
+            p.getAxis("left").setPen(axis_pen)
+            p.getAxis("bottom").setPen(axis_pen)
+            p.showGrid(x=False, y=True, alpha=0.12)
+
+            tick_font = QFont("Consolas", 11)
+            tick_font.setStyleHint(QFont.Monospace)
+            p.getAxis("left").setTickFont(tick_font)
+            p.getAxis("bottom").setTickFont(tick_font)
+
+            line_pen = pg.mkPen(color=CURVE_THEME_COLOR, width=2)
+            curve = p.plot(pen=line_pen, fillLevel=0)
+            dot_glow = p.plot(
+                [],
+                [],
+                pen=None,
+                symbol="o",
+                symbolSize=8,
+                symbolPen=None,
+                symbolBrush=(0, 229, 255, 76),
+            )
+            dot_core = p.plot(
+                [],
+                [],
+                pen=None,
+                symbol="o",
+                symbolSize=4,
+                symbolPen=None,
+                symbolBrush=(255, 255, 255, 255),
+            )
+
+            p.setXRange(0, PLOT_WINDOW_SEC, padding=0)
+            p.enableAutoRange(x=False, y=False)
+
+            self.plots.append(p)
+            self.curves.append(curve)
+            self.dot_glows.append(dot_glow)
+            self.dot_cores.append(dot_core)
+
+            if i < 2:
+                self.graph_widget.nextRow()
+
+    def adjust_image_panel(self):
+        """Size the left panel from the current image aspect ratio."""
+        top_bar_h = 48
+        log_h = self.log_widget.height()
+        spacing = 20
+        available = max(self.height() - top_bar_h - log_h - spacing, 160)
+        image_w = panel_width_for_aspect(available, self._display_aspect, min_size=160)
+        max_w = max(self.width() // 2, 160)
+        image_w = min(image_w, max_w)
+        self.h_splitter.setSizes([image_w, max(self.width() - image_w, 200)])
+        self._render_display_pixmap()
+
+    def resizeEvent(self, event):
+        super().resizeEvent(event)
+        self._render_display_pixmap()
+
+    def _render_display_pixmap(self):
+        if self._source_pixmap is None or self._source_pixmap.isNull():
+            return
+        target = self.arrows_label.size()
+        if target.width() < 2 or target.height() < 2:
+            return
+        self.arrows_label.setPixmap(pixmap_keep_aspect(self._source_pixmap, target))
+
+    def _on_timer(self):
+        if self.sensor_adapter is None:
+            return
+
+        snapshot = self.sensor_adapter.read()
+        if snapshot is None:
+            print("Failed to get image")
+            return
+        self._last_snapshot = snapshot
+
+        viewer_frame = self.viewer_backend.ingest(snapshot, now=time.time())
+        self._last_viewer_frame = viewer_frame
+        first_image = self._source_pixmap is None
+        aspect_changed = abs(viewer_frame.aspect_ratio - self._display_aspect) > 1e-3
+        self._display_aspect = viewer_frame.aspect_ratio
+
+        if self.is_save and self.writer is not None and snapshot.record_frame is not None:
+            self.frame_count += 1
+            save_img = snapshot.record_frame
+            if len(save_img.shape) == 2 or (
+                len(save_img.shape) == 3 and save_img.shape[2] == 1
+            ):
+                if len(save_img.shape) == 3:
+                    save_img = save_img.squeeze(2)
+                save_img = cv2.cvtColor(save_img, cv2.COLOR_GRAY2BGR)
+            self.writer.write(save_img)
+
+        print(
+            f"FPS={viewer_frame.fps:.2f}, "
+            f"法向力(raw)={viewer_frame.normal_force:.4f}, "
+            f"切向力X={viewer_frame.shear_x:.4f}, "
+            f"切向力Y={viewer_frame.shear_y:.4f}, "
+            f"法向力(N)={viewer_frame.normal_force_calibrated:.6f}"
+        )
+
+        self._source_pixmap = ndarray_to_pixmap(viewer_frame.display_image, bgr=True)
+        if first_image or aspect_changed:
+            self.adjust_image_panel()
+        else:
+            self._render_display_pixmap()
+
+        plot_state = self.viewer_backend.plot_state()
+        if plot_state is None:
+            return
+
+        for i, curve in enumerate(self.curves):
+            x = plot_state.times
+            y = plot_state.values[:, i]
+            curve.setData(x, y)
+            ymin, ymax = plot_state.y_ranges[i]
+            self.plots[i].setYRange(ymin, ymax)
+            self.dot_glows[i].setData(x[-1:], y[-1:])
+            self.dot_cores[i].setData(x[-1:], y[-1:])
+
+        x0, x1 = plot_state.x_range
+        for p in self.plots:
+            p.setXRange(x0, x1, padding=0)
+
+    def _on_start(self):
+        if self._running:
+            return
+        self.btn_start.setText("启动中...")
+        self.btn_start.setEnabled(False)
+        QApplication.processEvents()
+
+        try:
+            src = self.camera_edit.text()
+            cfg = self.config_edit.text()
+            cal = self.cal_edit.text()
+            verbose = getattr(self.args, "verbose", True)
+            sensor_type = getattr(self.args, "sensor_type", "orisys")
+            self.sensor_adapter = create_sensor_adapter(
+                sensor_type,
+                video=src,
+                config_name=cfg,
+                cal_path=cal,
+                verbose=verbose,
+            )
+            self.sensor_adapter.start()
+        except Exception as e:
+            self.btn_start.setText("启动")
+            self.btn_start.setEnabled(True)
+            self.sensor_adapter = None
+            print(f"启动失败: {e}")
+            return
+
+        self.viewer_backend.reset()
+        self._running = True
+        self.timer.start(10)
+        self.btn_start.setText("启动")
+        self.btn_stop.setEnabled(True)
+        self.btn_reset.setEnabled(True)
+        print(
+            f"▶ 启动 — sensor_type={getattr(self.args, 'sensor_type', 'orisys')}, "
+            f"摄像机={src}, 配置={cfg}, 标定={cal}"
+        )
+
+    def _on_stop(self):
+        if not self._running:
+            return
+        self._running = False
+        self.timer.stop()
+        self.btn_stop.setText("停止中...")
+        self.btn_stop.setEnabled(False)
+        QApplication.processEvents()
+
+        if self.sensor_adapter is not None:
+            self.sensor_adapter.close()
+            self.sensor_adapter = None
+        self._last_snapshot = None
+
+        self.btn_start.setEnabled(True)
+        self.btn_stop.setText("暂停")
+        self.btn_reset.setEnabled(False)
+        print("⏸ 已暂停")
+
+    def _select_camera(self):
+        path, _ = QFileDialog.getOpenFileName(
+            self,
+            "选择视频文件",
+            "data",
+            "视频 (*.mp4 *.avi *.mov);;所有文件 (*)",
+        )
+        if path:
+            self.camera_edit.setText(path)
+
+    def _select_config(self):
+        path, _ = QFileDialog.getOpenFileName(
+            self,
+            "选择配置文件",
+            "config",
+            "JSON (*.json);;所有文件 (*)",
+        )
+        if path:
+            self.config_edit.setText(path)
+
+    def _on_reset(self):
+        if self.sensor_adapter is None or not self._running:
+            print("请先启动传感器后再重置追踪器。")
+            return
+        self.sensor_adapter.reset()
+        print("追踪器已重置。")
+
+    def keyPressEvent(self, event):
+        key = event.key()
+        if key == Qt.Key_Escape:
+            if self.isFullScreen():
+                self.showNormal()
+            else:
+                self.showFullScreen()
+        elif key == Qt.Key_Q:
+            print("\n正在退出示例程序...")
+            self.close()
+        elif key == Qt.Key_S:
+            self._start_recording()
+        elif key == Qt.Key_E:
+            self._stop_recording()
+        elif key == Qt.Key_R:
+            self._on_reset()
+        else:
+            super().keyPressEvent(event)
+
+    def _start_recording(self):
+        if self.sensor_adapter is None:
+            print("请先启动采集")
+            return
+        self.save_path = "./data/pulse_test.mp4"
+        os.makedirs(os.path.dirname(self.save_path), exist_ok=True)
+
+        save_img = None
+        if self._last_snapshot is not None:
+            save_img = self._last_snapshot.record_frame
+        if save_img is None:
+            print("当前没有可用帧，无法确定录像尺寸。")
+            return
+
+        temp_img = save_img.copy()
+        if len(temp_img.shape) == 2 or (
+            len(temp_img.shape) == 3 and temp_img.shape[2] == 1
+        ):
+            if len(temp_img.shape) == 3:
+                temp_img = temp_img.squeeze(2)
+            temp_img = cv2.cvtColor(temp_img, cv2.COLOR_GRAY2BGR)
+
+        fh, fw = temp_img.shape[:2]
+        self.writer = cv2.VideoWriter(
+            self.save_path,
+            cv2.VideoWriter_fourcc(*"mp4v"),
+            30,
+            (fw, fh),
+        )
+        if self.writer.isOpened():
+            self.is_save = True
+            print(f"开始录像：{self.save_path}")
+        else:
+            print(f"无法创建录像文件：{self.save_path}")
+            self.writer = None
+
+    def _stop_recording(self):
+        self.is_save = False
+        if self.writer is not None:
+            self.writer.release()
+            self.writer = None
+        if self.save_path is not None:
+            print(f"录像结束：{self.save_path}，总帧数：{self.frame_count}")
+        else:
+            print(f"录像结束，总帧数：{self.frame_count}")
+        self.frame_count = 0
+
+    def closeEvent(self, event):
+        self.timer.stop()
+        if self.writer is not None:
+            self.writer.release()
+        if self.sensor_adapter is not None:
+            self.sensor_adapter.close()
+            self.sensor_adapter = None
+        event.accept()
+
+
+def run_viewer(args, *, log_dir: str | Path | None = None) -> int:
+    """Launch the 2D Qt viewer and block until the window closes."""
+    from gui.app import get_or_create_qapp
+
+    if log_dir is None:
+        log_dir = Path(__file__).resolve().parents[3] / "scripts" / "logs"
+    else:
+        log_dir = Path(log_dir)
+    log_dir.mkdir(parents=True, exist_ok=True)
+    log_path = log_dir / f"qt_viewer_{datetime.now().strftime('%Y%m%d_%H%M%S')}.log"
+    log_file = open(log_path, "w", encoding="utf-8")
+    sys.stdout = log_file
+    sys.stderr = sys.stdout
+
+    print("\n按键说明：Q 退出 | R 重置追踪器 | S 开始录像 | E 结束录像 | ESC 全屏")
+
+    app = get_or_create_qapp("Orisys SDK")
+    window = QtViewerWindow(args, log_file)
+    window.showFullScreen()
+    QApplication.processEvents()
+    window.adjust_image_panel()
+    return app.exec_()

examples/gui/viewer3d/__init__.py

@@ -0,0 +1,36 @@
+"""Finger 3D Qt dashboard (mesh + UV arrows + force charts)."""
+
+from .dashboard import FingerDashboardWindow, run_dashboard
+from .layout import (
+    LOG_PANEL,
+    LAYOUT,
+    MESH_CONTACT_ARROW,
+    MESH_LIGHTING,
+    PANEL_SETUP,
+    TOP_ROW,
+    DashboardLayout,
+    MeshLighting,
+    PanelRow,
+    PanelSetup,
+    PanelSlot,
+    top_row_splitter_sizes,
+    top_row_slot_index,
+)
+
+__all__ = [
+    "DashboardLayout",
+    "FingerDashboardWindow",
+    "LAYOUT",
+    "LOG_PANEL",
+    "MESH_CONTACT_ARROW",
+    "MESH_LIGHTING",
+    "MeshLighting",
+    "PANEL_SETUP",
+    "TOP_ROW",
+    "PanelRow",
+    "PanelSetup",
+    "PanelSlot",
+    "run_dashboard",
+    "top_row_splitter_sizes",
+    "top_row_slot_index",
+]

examples/gui/viewer3d/dashboard.py

@@ -21,7 +21,7 @@ from pipeline.config import PipelineConfig
 from pipeline.csv_recorder import CsvRecorder
 from pipeline.service import FingerPipeline
 
-from .app_paths import resource_path
+from gui.app_paths import resource_path
 from .camera_discovery import list_cameras, pick_default_camera
 from .preferences import get_preferred_video_source, load_preferences, save_preferences
 from .layout import (
@@ -33,14 +33,12 @@ from .layout import (
 )
 from .mesh_view_state import MeshViewState
 from .styles import STYLE
+from gui.widgets import TeeStream, WidgetLogHandler, make_log_widget
 from .widgets import (
     ArrowPanelWidget,
     ForceChartWidget,
     MeshViewportWidget,
     SettingsPanelWidget,
-    TeeStream,
-    WidgetLogHandler,
-    make_log_widget,
 )
 
 
@@ -689,7 +687,7 @@ class FingerDashboardWindow(QMainWindow):
 
 def run_dashboard(config: PipelineConfig, *, layout: DashboardLayout = LAYOUT) -> int:
     """Launch the unified finger dashboard and block until the window closes."""
-    from .app import get_or_create_qapp
+    from gui.app import get_or_create_qapp
 
     print("\n按键说明：Q 退出 | R 重置追踪器 | S 开始录像 | E 结束录像 | ESC 全屏")
     print("GUI：Record CSV / Stop CSV 写入接触点与力到所选目录。")

examples/gui/viewer3d/layout.py

@@ -47,6 +47,7 @@ import math
 from dataclasses import dataclass
 from typing import Literal
 
+from gui.log_config import LOG_CONFIG, LogConfig
 from viz.contact_arrow import ContactArrowStyle, DEFAULT_CONTACT_ARROW_STYLE
 from viz.flow_arrow import FlowArrowStyle
 from viz.render_2d import ArrowBackground, ArrowCanvasColors
@@ -193,53 +194,6 @@ ARROW_CANVAS_COLORS = ArrowCanvasColors(
 )
 
 
-@dataclass(frozen=True)
-class LogConfig:
-    """Log panel — edit LOG_CONFIG or DashboardLayout.log_config."""
-
-    status_enabled: bool = True
-    max_lines: int = 2000
-    font_family: str = "Cascadia Mono"
-    font_pt: int = 12
-    show_flow: bool = True
-    show_mask: bool = True
-
-    def format_status(
-        self,
-        *,
-        fps: float,
-        fnormal: float,
-        fshearx: float,
-        fsheary: float,
-        flow_rms: float = 0.0,
-        mask_coverage: float = 0.0,
-        wall_fps: float | None = None,
-        contact_xyz_mm: tuple[float, float, float] | None = None,
-    ) -> str:
-        shear_mag = float((fshearx**2 + fsheary**2) ** 0.5)
-        if wall_fps is not None:
-            parts = [f"FPS={wall_fps:.1f}", f"sdk={fps:.1f}"]
-        else:
-            parts = [f"FPS={fps:.1f}"]
-        parts.extend(
-            [
-                f"Fn={fnormal:.1f}",
-                f"|(Fx,Fy)|={shear_mag:.1f}",
-                f"Fx, Fy=({fshearx:.1f}, {fsheary:.1f})",
-            ]
-        )
-        force_line = "  ".join(parts)
-        if contact_xyz_mm is None:
-            contact_line = "contact=---"
-        else:
-            cx, cy, cz = contact_xyz_mm
-            contact_line = f"contact=({cx:.1f}, {cy:.1f}, {cz:.1f}) mm"
-        return f"{force_line}\n{contact_line}"
-
-
-LOG_CONFIG = LogConfig()
-
-
 @dataclass(frozen=True)
 class DashboardLayout:
     """Window chrome, chart styling, and panel hierarchy."""

examples/gui/viewer3d/preferences.py

@@ -1,4 +1,4 @@
-"""Load/save dashboard user preferences near this module."""
+"""Load/save dashboard user preferences for the finger 3D viewer."""
 
 from __future__ import annotations
 
@@ -6,15 +6,16 @@ import json
 from pathlib import Path
 from typing import Any
 
-from .app_paths import resource_path
+from gui.app_paths import resource_path
 
 PREFERENCE_FILE = "preference.json"
 LEGACY_CAMERA_SELECTION_FILE = "camera_selection.json"
-_GUI_DIR = Path(__file__).resolve().parent
+# Keep preference.json at examples/gui/ for backward compatibility.
+_GUI_DIR = Path(__file__).resolve().parents[1]
 
 
 def preference_path() -> Path:
-    # Keep preference file beside this module: examples/gui/preference.json
+    # Keep preference file at examples/gui/preference.json
     return _GUI_DIR / PREFERENCE_FILE
 
 

examples/gui/viewer3d/widgets/__init__.py

@@ -0,0 +1,15 @@
+"""Finger-specific Qt widgets for the 3D dashboard."""
+
+from .arrow_image import ArrowPanelWidget
+from .force_charts import ForceChartWidget
+from .image_panel import ImagePanel
+from .mesh_viewport import MeshViewportWidget
+from .settings_panel import SettingsPanelWidget
+
+__all__ = [
+    "ArrowPanelWidget",
+    "ForceChartWidget",
+    "ImagePanel",
+    "MeshViewportWidget",
+    "SettingsPanelWidget",
+]

examples/gui/viewer3d/widgets/arrow_image.py

@@ -9,7 +9,7 @@ from viz.render_2d import ArrowBackground, ArrowCanvasColors, render_uv_arrows
 
 from ..layout import DashboardLayout, LAYOUT
 from .image_panel import ImagePanel
-from .qt_pixmap import ndarray_to_pixmap
+from gui.widgets.qt_pixmap import ndarray_to_pixmap
 
 
 class ArrowPanelWidget(ImagePanel):

examples/gui/viewer3d/widgets/force_charts.py

@@ -6,8 +6,8 @@ import numpy as np
 from PyQt5.QtGui import QFont
 from PyQt5.QtWidgets import QSizePolicy
 
-from gui.layout import DashboardLayout, LAYOUT
+from ..layout import DashboardLayout, LAYOUT
-from gui.styles import LOG_FONT_PRIMARY, UI_FONT_PRIMARY
+from ..styles import LOG_FONT_PRIMARY, UI_FONT_PRIMARY
 from pipeline.frame import FingerFrameView
 from viz.signal_filters import lowpass_filter
 

examples/gui/viewer3d/widgets/image_panel.py

@@ -6,7 +6,7 @@ from PyQt5.QtCore import Qt
 from PyQt5.QtGui import QPixmap
 from PyQt5.QtWidgets import QLabel, QSizePolicy, QVBoxLayout, QWidget
 
-from .qt_pixmap import pixmap_keep_aspect
+from gui.widgets.qt_pixmap import pixmap_keep_aspect
 
 
 class ImagePanel(QWidget):

examples/gui/viewer3d/widgets/mesh_viewport.py

@@ -11,7 +11,7 @@ from viz.offscreen_mesh import OffscreenFingerMeshRenderer
 from ..layout import DashboardLayout, LAYOUT
 from ..mesh_view_state import MeshViewState
 from ..mesh_render_worker import MeshRenderWorker
-from .qt_pixmap import ndarray_to_pixmap
+from gui.widgets.qt_pixmap import ndarray_to_pixmap
 from .image_panel import ImagePanel
 
 _VIEW_ROTATE_SENSITIVITY = 0.35

examples/gui/widgets/__init__.py

@@ -1,19 +1,9 @@
-"""Qt widgets for the finger dashboard."""
+"""Shared Qt widgets used by 2D and 3D viewers."""
 
-from .settings_panel import SettingsPanelWidget
-from .force_charts import ForceChartWidget
 from .log_panel import TeeStream, WidgetLogHandler, make_log_widget
-from .mesh_viewport import MeshViewportWidget
-from .arrow_image import ArrowPanelWidget
 from .qt_pixmap import ndarray_to_pixmap, pixmap_keep_aspect
-from .image_panel import ImagePanel
 
 __all__ = [
-    "ArrowPanelWidget",
-    "SettingsPanelWidget",
-    "ForceChartWidget",
-    "MeshViewportWidget",
-    "ImagePanel",
     "TeeStream",
     "WidgetLogHandler",
     "make_log_widget",

examples/gui/widgets/log_panel.py

@@ -86,7 +86,7 @@ class WidgetLogHandler:
 
 def make_log_widget(config=None) -> QPlainTextEdit:
     if config is None:
-        from ..layout import LOG_CONFIG
+        from ..log_config import LOG_CONFIG
 
         config = LOG_CONFIG
     widget = QPlainTextEdit()

scripts/qt_viewer_2.py

@@ -1,794 +1,31 @@
-"""
+#!/usr/bin/env python3
-Orisys SDK 实时监控 — Qt 统一界面
+"""Shim for the Orisys 2D Qt sensor monitor (see examples/gui/viewer2d/)."""
-
-将所有可视化和曲线整合到一个窗口中，适合销售演示使用。
-SDK version: 0.3.1
-"""
 
 import os
 import sys
-os.environ["OPENCV_VIDEOIO_MSMF_ENABLE_HW_TRANSFORMS"] = "0"
+from pathlib import Path
-import cv2
-def _fix_qt_plugin_path():
-    """OpenCV redirects Qt to cv2/qt/plugins; use PyQt5's plugins instead."""
-    try:
-        from PyQt5.QtCore import QLibraryInfo
-        os.environ["QT_QPA_PLATFORM_PLUGIN_PATH"] = QLibraryInfo.location(
-            QLibraryInfo.PluginsPath
-        )
-    except Exception:
-        path = os.environ.get("QT_QPA_PLATFORM_PLUGIN_PATH", "")
-        if "cv2" in path.replace("\\", "/"):
-            os.environ.pop("QT_QPA_PLATFORM_PLUGIN_PATH", None)
-_fix_qt_plugin_path()
-import orisys
-import numpy as np
-import time
-import argparse
-from datetime import datetime
-from scipy.signal import butter, filtfilt
 
-# Force curve sampling rate (Hz), matches typical sensor loop ~30 FPS.
+os.environ.setdefault("OPENCV_VIDEOIO_MSMF_ENABLE_HW_TRANSFORMS", "0")
-FORCE_SAMPLE_RATE_HZ = 30.0
-PLOT_BUFFER_POINTS = 120
-PLOT_WINDOW_SEC = PLOT_BUFFER_POINTS / FORCE_SAMPLE_RATE_HZ  # 4 s window
-# Minimum y-axis span so autoscale does not over-zoom on small fluctuations.
-Y_AXIS_MIN_SPAN = 20000
-CURVE_THEME_COLOR = '#00E5FF'
-NORMAL_FORCE_CAL_SLOPE = 3.92685554668795e-05
-NORMAL_FORCE_CAL_OFFSET = 0.0217596967278535
 
-from PyQt5.QtWidgets import (
+_EXAMPLES_DIR = Path(__file__).resolve().parents[1] / "examples"
-    QMainWindow, QWidget, QHBoxLayout, QVBoxLayout,
+if str(_EXAMPLES_DIR) not in sys.path:
-    QLabel, QApplication, QSplitter, QPlainTextEdit,
+    sys.path.insert(0, str(_EXAMPLES_DIR))
-    QPushButton, QFileDialog, QLineEdit,
-)
-from PyQt5.QtCore import Qt, QTimer
-from PyQt5 import QtGui
-from PyQt5.QtGui import QImage, QPixmap, QFont, QIcon
 
-try:
+from gui.viewer2d import run_viewer
-    import pyqtgraph as pg
-except Exception:
-    print("PyQtGraph is not installed. Please install it using 'pip install pyqt5 pyqtgraph'.")
-    sys.exit(1)
 
-# ---------------------------------------------------------------------------
-# 工具
-# ---------------------------------------------------------------------------
-
-def cv2_to_pixmap(img_bgr: np.ndarray) -> QPixmap:
-    rgb = cv2.cvtColor(img_bgr, cv2.COLOR_BGR2RGB)
-    h, w, ch = rgb.shape
-    qimg = QImage(rgb.data, w, h, ch * w, QImage.Format_RGB888)
-    return QPixmap.fromImage(qimg)
-
-def draw_magnitude_map(vfield, threshold=3, colormap=cv2.COLORMAP_JET) -> np.ndarray:
-    flow_field = vfield
-    magnitude = np.sqrt(flow_field[:, :, 0] ** 2 + flow_field[:, :, 1] ** 2)
-
-    downsample_factor = 10
-    h, w = magnitude.shape
-    magnitude_downsampled = magnitude[::downsample_factor, ::downsample_factor]
-    magnitude_smoothed = cv2.resize(magnitude_downsampled, (w, h), interpolation=cv2.INTER_CUBIC)
-
-    magnitude_thresholded = magnitude_smoothed.copy()
-    magnitude_thresholded[magnitude_smoothed < threshold] = 0
-
-    mag_min, mag_max = magnitude_thresholded.min(), magnitude_thresholded.max()
-    if mag_max > mag_min:
-        magnitude_norm = ((magnitude_thresholded - mag_min) / (mag_max - mag_min) * 255).astype(np.uint8)
-    else:
-        magnitude_norm = np.zeros_like(magnitude_thresholded, dtype=np.uint8)
-
-    magnitude_colored = cv2.applyColorMap(magnitude_norm, colormap)
-    out_img = cv2.resize(magnitude_colored, (400, 400), interpolation=cv2.INTER_CUBIC)
-    return out_img
-
-
-def lowpass_filter(data, cutoff_hz, sample_rate_hz=FORCE_SAMPLE_RATE_HZ, order=2):
-    """
-    Zero-phase Butterworth low-pass filter for uniformly sampled 1-D data.
-
-    Parameters
-    ----------
-    data : array-like
-        Input samples acquired at `sample_rate_hz` (default 30 Hz).
-    cutoff_hz : float
-        -3 dB cutoff frequency in Hz; use 0 to skip filtering (return raw data).
-        Otherwise must satisfy 0 < cutoff_hz < sample_rate_hz / 2.
-    sample_rate_hz : float
-        Sampling rate of `data` in Hz.
-    order : int
-        Butterworth filter order.
-
-    Returns
-    -------
-    np.ndarray
-        Filtered 1-D array with the same length as `data`.
-    """
-    y = np.asarray(data, dtype=np.float64)
-    if cutoff_hz == 0:
-        return y.copy()
-    if y.size == 0:
-        return y
-
-    nyquist = 0.5 * sample_rate_hz
-    if cutoff_hz < 0 or cutoff_hz >= nyquist:
-        raise ValueError(
-            f"cutoff_hz must be in (0, {nyquist}) for sample_rate_hz={sample_rate_hz}"
-        )
-
-    b, a = butter(order, cutoff_hz / nyquist, btype="low")
-    padlen = 3 * (max(len(b), len(a)) - 1)
-    if y.size <= padlen:
-        return y.copy()
-
-    return filtfilt(b, a, y)
-
-
-def calibrate_normal_force(raw_value):
-    """Convert raw normal-force reading to Newtons using y = mx + c."""
-    return NORMAL_FORCE_CAL_SLOPE * raw_value + NORMAL_FORCE_CAL_OFFSET
-
-
-class TeeStream:
-    """同时写入多个流"""
-    def __init__(self, *streams):
-        self.streams = streams
-
-    def write(self, text):
-        for s in self.streams:
-            s.write(text)
-
-    def flush(self):
-        for s in self.streams:
-            s.flush()
-
-
-class WidgetLogHandler:
-    """将 print 输出实时显示到 QPlainTextEdit"""
-    def __init__(self, widget: QPlainTextEdit):
-        self.widget = widget
-        self.buf = ""
-
-    def write(self, text: str):
-        self.buf += text
-        while "\n" in self.buf:
-            line, self.buf = self.buf.split("\n", 1)
-            if line:
-                self.widget.appendPlainText(line)
-
-    def flush(self):
-        if self.buf:
-            self.widget.appendPlainText(self.buf)
-            self.buf = ""
-
-# ---------------------------------------------------------------------------
-# 样式表
-# ---------------------------------------------------------------------------
-
-STYLE = """
-QMainWindow {
-    background-color: #000000;
-}
-
-/* ---- 图像面板 ---- */
-QLabel#arrowsLabel {
-    border: 1px solid #262626;
-    border-radius: 4px;
-    background-color: #0b0b0b;
-}
-
-/* ---- 顶栏按钮 & 输入 - — */
-QPushButton {
-    background-color: #1a1a1a;
-    color: #999999;
-    border: 1px solid #333333;
-    border-radius: 4px;
-    padding: 6px 16px;
-    font-family: "SimHei";
-    font-size: 13px;
-}
-QPushButton:hover {
-    background-color: #262626;
-    color: #cccccc;
-    border: 1px solid #555555;
-}
-QPushButton#btnStart {
-    background-color: #0d2818;
-    color: #4caf84;
-    border: 1px solid #1a4d30;
-}
-QPushButton#btnStart:hover {
-    background-color: #143d24;
-    color: #6fd4a0;
-}
-QPushButton#btnStart:disabled {
-    background-color: #0f0f0f;
-    color: #333333;
-    border: 1px solid #222222;
-}
-QPushButton#btnStop {
-    background-color: #2b1010;
-    color: #e05555;
-    border: 1px solid #4d1a1a;
-}
-QPushButton#btnStop:hover {
-    background-color: #3d1818;
-    color: #f07070;
-}
-QPushButton#btnStop:disabled {
-    background-color: #0f0f0f;
-    color: #333333;
-    border: 1px solid #222222;
-}
-QLineEdit {
-    background-color: #0d0d0d;
-    color: #999999;
-    border: 1px solid #333333;
-    border-radius: 4px;
-    padding: 5px 10px;
-    font-size: 13px;
-}
-
-/* ---- 力曲线容器 ---- */
-GraphicsLayoutWidget {
-    border: 1px solid #262626;
-    border-radius: 4px;
-}
-
-/* ---- 日志面板 ---- */
-QPlainTextEdit {
-    background-color: #0b0b0b;
-    color: #777777;
-    border: 1px solid #262626;
-    border-radius: 4px;
-    font-family: "Cascadia Code", "Consolas", "Courier New", monospace;
-    font-size: 13px;
-    padding: 8px;
-    selection-background-color: #1a3a4a;
-    selection-color: #cccccc;
-}
-
-QPlainTextEdit QScrollBar:vertical {
-    background-color: #0b0b0b;
-    width: 6px;
-    margin: 1px;
-    border-radius: 3px;
-}
-QPlainTextEdit QScrollBar::handle:vertical {
-    background-color: #262626;
-    border-radius: 3px;
-    min-height: 30px;
-}
-QPlainTextEdit QScrollBar::handle:vertical:hover {
-    background-color: #3a3a3a;
-}
-QPlainTextEdit QScrollBar::add-line:vertical,
-QPlainTextEdit QScrollBar::sub-line:vertical {
-    height: 0px;
-}
-QPlainTextEdit QScrollBar::add-page:vertical,
-QPlainTextEdit QScrollBar::sub-page:vertical {
-    background: none;
-}
-
-QSplitter::handle {
-    background-color: #1a1a1a;
-}
-QSplitter::handle:vertical {
-    height: 1px;
-}
-QSplitter::handle:horizontal {
-    width: 1px;
-}
-"""
-
-# ---------------------------------------------------------------------------
-# 主窗口
-# ---------------------------------------------------------------------------
-
-class MainWindow(QMainWindow):
-    def __init__(self, args, log_file):
-        super().__init__()
-        self.setWindowTitle("Orisys SDK")
-        self.setStyleSheet(STYLE)
-
-        logo_path = os.path.join(os.path.dirname(os.path.dirname(__file__)), "logo.png")
-        if os.path.exists(logo_path):
-            self.setWindowIcon(QIcon(logo_path))
-
-        self.sensor = None
-        self.start_time = None
-        self.args = args
-
-        # 录像状态
-        self.is_save = False
-        self.frame_count = 0
-        self.writer = None
-        self.save_path = None
-
-        # 曲线数据缓冲（先填满 npoints 再滚动；120 点 @ 30 Hz = 4 s）
-        self.npoints = PLOT_BUFFER_POINTS
-        self.lowpass_cutoff_hz = getattr(args, "cutoff", 5.0)
-        self._plot_sample_count = 0
-        self._init_plot_buffer()
-
-        self._setup_ui()
-        self._create_plots()
-
-        # 同步参数到 UI
-        self.camera_edit.setText(args.video)
-        self.config_edit.setText(args.config)
-        self.cal_edit.setText(args.cal)
-
-        # stdout → 日志文件 + 界面日志面板
-        self.log_handler = WidgetLogHandler(self.log_widget)
-        sys.stdout = TeeStream(log_file, self.log_handler)
-        sys.stderr = sys.stdout
-
-        self._y_range_alpha = 0.5
-
-        self.timer = QTimer()
-        self.timer.timeout.connect(self._on_timer)
-        self._running = False
-
-    def _init_plot_buffer(self):
-        """Empty buffer; x-axis grows until npoints real samples, then scrolls."""
-        self.data = np.full((self.npoints, 2, 3), np.nan, dtype=np.float64)
-        self._plot_sample_count = 0
-        self._y_range_smooth = [None, None, None]
-
-    # ---- UI 构建 ----
-
-    def _setup_ui(self):
-        central = QWidget()
-        self.setCentralWidget(central)
-        root_layout = QVBoxLayout(central)
-        root_layout.setContentsMargins(6, 6, 6, 6)
-        root_layout.setSpacing(6)
-
-        # ---- 顶栏 ----
-        bar = QHBoxLayout()
-        bar.setSpacing(8)
-
-        self.btn_camera = QPushButton("摄像机")
-        self.btn_camera.setObjectName("btnCamera")
-        self.btn_camera.clicked.connect(self._select_camera)
-        bar.addWidget(self.btn_camera)
-        self.camera_edit = QLineEdit("1")
-        self.camera_edit.setPlaceholderText("摄像头编号 或 视频路径")
-        bar.addWidget(self.camera_edit, 1)
-
-        self.btn_config = QPushButton("配置")
-        self.btn_config.setObjectName("btnConfig")
-        self.btn_config.clicked.connect(self._select_config)
-        bar.addWidget(self.btn_config)
-        self.config_edit = QLineEdit("./config/ddjx01.json")
-        bar.addWidget(self.config_edit, 1)
-
-        self.btn_reset = QPushButton("重置")
-        self.btn_reset.setObjectName("btnReset")
-        self.btn_reset.setEnabled(False)
-        self.btn_reset.clicked.connect(self._on_reset)
-        bar.addWidget(self.btn_reset)
-        self.cal_edit = QLineEdit("./config/ddjx01.npy")
-        bar.addWidget(self.cal_edit, 1)
-
-        self.btn_start = QPushButton("启动")
-        self.btn_start.setObjectName("btnStart")
-        self.btn_start.clicked.connect(self._on_start)
-        bar.addWidget(self.btn_start)
-
-        self.btn_stop = QPushButton("暂停")
-        self.btn_stop.setObjectName("btnStop")
-        self.btn_stop.setEnabled(False)
-        self.btn_stop.clicked.connect(self._on_stop)
-        bar.addWidget(self.btn_stop)
-
-        root_layout.addLayout(bar)
-
-        # ---- 外层纵向 splitter：主区域 / 日志 ----
-        v_splitter = QSplitter(Qt.Vertical)
-
-        # ---- 主区域：图像 (左) | 曲线 (右) ----
-        h_splitter = QSplitter(Qt.Horizontal)
-
-        # 左侧图像面板
-        left = QWidget()
-        left_layout = QVBoxLayout(left)
-        left_layout.setContentsMargins(0, 0, 0, 0)
-        left_layout.setSpacing(6)
-
-        self.arrows_label = QLabel()
-        self.arrows_label.setObjectName("arrowsLabel")
-        self.arrows_label.setMinimumSize(160, 160)
-        self.arrows_label.setScaledContents(True)
-        self.arrows_label.setAlignment(Qt.AlignCenter)
-        left_layout.addWidget(self.arrows_label)
-
-        h_splitter.addWidget(left)
-
-        # 右侧力曲线
-        pg.setConfigOption('background', '#000000')
-        pg.setConfigOption('foreground', '#777777')
-        pg.setConfigOptions(antialias=True)
-        self.graph_widget = pg.GraphicsLayoutWidget()
-        self.graph_widget.setMinimumWidth(300)
-        h_splitter.addWidget(self.graph_widget)
-
-        self.h_splitter = h_splitter
-
-        v_splitter.addWidget(h_splitter)
-
-        # ---- 底部日志面板 ----
-        self.log_widget = QPlainTextEdit()
-        self.log_widget.setReadOnly(True)
-        self.log_widget.setMaximumBlockCount(2000)
-        font = QFont("Consolas", 12)
-        font.setStyleHint(QFont.Monospace)
-        self.log_widget.setFont(font)
-        v_splitter.addWidget(self.log_widget)
-
-        v_splitter.setStretchFactor(0, 4)
-        v_splitter.setStretchFactor(1, 1)
-
-        root_layout.addWidget(v_splitter)
-
-    def _create_plots(self):
-        titles = ["法向力 (N)", "切向力 X", "切向力 Y"]
-        self.plots = []
-        self.curves = []
-        self.dot_glows = []
-        self.dot_cores = []
-
-        axis_pen = pg.mkPen(color=(38, 38, 38), width=1)  # #262626
-        label_font = QFont("SimHei", 9)
-
-        for i, title in enumerate(titles):
-            p = self.graph_widget.addPlot(title=None)
-
-            # 标题：黑体
-            p.setTitle(title, color='#999999', size='14pt')
-            p.titleLabel.setFont(QFont("SimHei", 14))
-
-            # X 轴标签
-            p.setLabel('bottom', '时间', units='s')
-            p.getAxis('bottom').label.setFont(label_font)
-
-            # 仅保留左 + 下轴线，隐藏右 + 上边框
-            p.showAxis('top', False)
-            p.showAxis('right', False)
-            p.getAxis('left').setPen(axis_pen)
-            p.getAxis('bottom').setPen(axis_pen)
-
-            # 仅横向网格，极淡
-            p.showGrid(x=False, y=True, alpha=0.12)
-
-            # 等宽刻度字体
-            tick_font = QFont("Consolas", 11)
-            tick_font.setStyleHint(QFont.Monospace)
-            p.getAxis('left').setTickFont(tick_font)
-            p.getAxis('bottom').setTickFont(tick_font)
-
-            # 曲线: 青色描边 + 向下渐变填充（与 demo_wuxi 一致）
-            line_pen = pg.mkPen(color=CURVE_THEME_COLOR, width=2)
-            # grad_brush = make_gradient_brush(CURVE_THEME_COLOR, max_alpha=120)
-            curve = p.plot(pen=line_pen, fillLevel=0)
-
-            # 终点光晕: #00e5ff 30% 透明，半径 8
-            dot_glow = p.plot([], [], pen=None, symbol='o', symbolSize=8,
-                              symbolPen=None, symbolBrush=(0, 229, 255, 76))
-            # 终点核心: 纯白，半径 4
-            dot_core = p.plot([], [], pen=None, symbol='o', symbolSize=4,
-                              symbolPen=None, symbolBrush=(255, 255, 255, 255))
-
-            p.setXRange(0, PLOT_WINDOW_SEC, padding=0)
-            p.enableAutoRange(x=False, y=False)
-
-            self.plots.append(p)
-            self.curves.append(curve)
-            self.dot_glows.append(dot_glow)
-            self.dot_cores.append(dot_core)
-
-            if i < 2:
-                self.graph_widget.nextRow()
-
-    def adjust_square_images(self):
-        """根据窗口高度调整左侧面板宽度，使左侧图像保持正方形"""
-        top_bar_h = 48
-        log_h = self.log_widget.height()
-        spacing = 20
-        available = self.height() - top_bar_h - log_h - spacing
-        image_w = max(available, 160)
-        self.h_splitter.setSizes([image_w, self.width() - image_w])
-
-    # ---- 帧处理 ----
-
-    def _on_timer(self):
-        if self.sensor is None:
-            return
-        sensor = self.sensor
-
-        isimg = sensor.get_img()
-        if isimg is None:
-            print("Failed to get image")
-            return
-
-        # 旋转原始图像，使力方向与实际物理方向对齐
-        sensor.img = cv2.rotate(sensor.img, cv2.ROTATE_90_COUNTERCLOCKWISE)
-        if sensor.frame is not None:
-            sensor.frame = cv2.rotate(sensor.frame, cv2.ROTATE_90_COUNTERCLOCKWISE)
-
-        # 录像写入
-        if self.is_save and self.writer is not None and sensor.frame is not None:
-            self.frame_count += 1
-            save_img = sensor.frame
-            if len(save_img.shape) == 2 or (len(save_img.shape) == 3 and save_img.shape[2] == 1):
-                if len(save_img.shape) == 3:
-                    save_img = save_img.squeeze(2)
-                save_img = cv2.cvtColor(save_img, cv2.COLOR_GRAY2BGR)
-            self.writer.write(save_img)
-
-        is_touched = sensor.compute_deformation(check_motion=True, threshold=1)
-        sensor.compute_contact()
-
-        fps, fn_raw, fx, fy, flow, vnormal, vshear, _ = sensor.read_info(
-            sensor.info.FPS, sensor.info.FNORMAL,
-            sensor.info.FSHEARX, sensor.info.FSHEARY,
-            sensor.info.VRAW, sensor.info.VNORMAL,
-            sensor.info.VSHEAR,
-            sensor.info.DEPTH
-        )
-        fn = calibrate_normal_force(fn_raw)
-
-
-        print(f"FPS={fps:.2f}, 法向力={fn:.4f}, 切向力X={fx:.4f}, 切向力Y={fy:.4f}")
-        # print(f"CUPY Available: {sensor.CUPY_AVAILABLE}")
-
-        # 图像
-        _bg_bgr = (22, 16, 11)
-        _img = sensor.img
-        _h, _w = _img.shape[:2]
-        black_img = np.empty((_h, _w, 3), dtype=_img.dtype)
-        black_img[:, :, 0] = _bg_bgr[0]
-        black_img[:, :, 1] = _bg_bgr[1]
-        black_img[:, :, 2] = _bg_bgr[2]
-
-        arrows = orisys.util.draw_arrows(
-            black_img, flow,
-            threshold=2, grid_spacing=20,
-            arrow_scale=0.5,
-            below_threshold_color=(160, 160, 160),
-        )
-        arrows = cv2.resize(arrows, (400, 400), interpolation=cv2.INTER_CUBIC)
-        self.arrows_label.setPixmap(cv2_to_pixmap(arrows))
-
-        # 曲线：先顺序写入 npoints 个真实样本，满后再左移滚动
-        current_time = time.time() - self.start_time
-        if self._plot_sample_count < self.npoints:
-            idx = self._plot_sample_count
-            self.data[idx, 0, :] = current_time
-            self.data[idx, 1, 0] = fn
-            self.data[idx, 1, 1] = fx
-            self.data[idx, 1, 2] = fy
-            self._plot_sample_count += 1
-        else:
-            for i in range(3):
-                self.data[:-1, 0, i] = self.data[1:, 0, i]
-                self.data[:-1, 1, i] = self.data[1:, 1, i]
-            self.data[-1, 0, :] = current_time
-            self.data[-1, 1, 0] = fn
-            self.data[-1, 1, 1] = fx
-            self.data[-1, 1, 2] = fy
-
-        n = self._plot_sample_count
-        if n == 0:
-            return
-
-        data_plot = self.data[:n].copy()
-        for i in range(3):
-            data_plot[:, 1, i] = lowpass_filter(
-                data_plot[:, 1, i],
-                self.lowpass_cutoff_hz,
-                sample_rate_hz=FORCE_SAMPLE_RATE_HZ,
-            )
-
-        for i, curve in enumerate(self.curves):
-            x = data_plot[:, 0, i]
-            y = data_plot[:, 1, i]
-            curve.setData(x, y)
-            ymin, ymax = y.min(), y.max()
-            if self._y_range_smooth[i] is None:
-                self._y_range_smooth[i] = (ymin, ymax)
-            else:
-                prev_min, prev_max = self._y_range_smooth[i]
-                alpha = self._y_range_alpha
-                ymin = alpha * ymin + (1 - alpha) * prev_min
-                ymax = alpha * ymax + (1 - alpha) * prev_max
-            span = ymax - ymin
-            if span < Y_AXIS_MIN_SPAN:
-                mid = (ymin + ymax) / 2
-                half = Y_AXIS_MIN_SPAN / 2
-                ymin = mid - half
-                ymax = mid + half
-            self._y_range_smooth[i] = (ymin, ymax)
-            pad = max((ymax - ymin) * 0.12, 0.01)
-            self.plots[i].setYRange(ymin - pad, ymax + pad)
-            last_x = x[-1:]
-            last_y = y[-1:]
-            self.dot_glows[i].setData(last_x, last_y)
-            self.dot_cores[i].setData(last_x, last_y)
-
-        if n < self.npoints:
-            for p in self.plots:
-                p.setXRange(0, PLOT_WINDOW_SEC, padding=0)
-        else:
-            x0 = float(data_plot[0, 0, 0])
-            x1 = float(data_plot[-1, 0, 0])
-            if x1 <= x0:
-                x1 = x0 + PLOT_WINDOW_SEC
-            for p in self.plots:
-                p.setXRange(x0, x1, padding=0)
-
-    # ---- 键盘 & 录像 ----
-
-    def _on_start(self):
-        if self._running:
-            return
-        self.btn_start.setText("启动中...")
-        self.btn_start.setEnabled(False)
-        QApplication.processEvents()
-
-        try:
-            src = self.camera_edit.text()
-            cfg = self.config_edit.text()
-            cal = self.cal_edit.text()
-            verbose = getattr(self.args, 'verbose', True)
-            try:
-                src = int(src)
-            except ValueError:
-                pass
-            self.sensor = orisys.Sensor(src, config_name=cfg, cal_path=cal, verbose=verbose)
-        except Exception as e:
-            self.btn_start.setText("启动")
-            self.btn_start.setEnabled(True)
-            print(f"启动失败: {e}")
-            return
-
-        self.start_time = time.time()
-        self._init_plot_buffer()
-        self._running = True
-        self.timer.start(10)
-        self.btn_start.setText("启动")
-        self.btn_stop.setEnabled(True)
-        self.btn_reset.setEnabled(True)
-        print(f"▶ 启动 — 摄像机={src}, 配置={cfg}, 标定={cal}")
-
-    def _on_stop(self):
-        if not self._running:
-            return
-        self._running = False
-        self.timer.stop()
-        self.btn_stop.setText("停止中...")
-        self.btn_stop.setEnabled(False)
-        QApplication.processEvents()
-
-        if self.sensor is not None:
-            self.sensor.disconnect()
-            self.sensor = None
-
-        self.btn_start.setEnabled(True)
-        self.btn_stop.setText("暂停")
-        self.btn_reset.setEnabled(False)
-        print("⏸ 已暂停")
-
-    def _select_camera(self):
-        text = self.camera_edit.text()
-        path, _ = QFileDialog.getOpenFileName(
-            self, "选择视频文件", "data", "视频 (*.mp4 *.avi *.mov);;所有文件 (*)",
-        )
-        if path:
-            self.camera_edit.setText(path)
-
-    def _select_config(self):
-        path, _ = QFileDialog.getOpenFileName(
-            self, "选择配置文件", "config", "JSON (*.json);;所有文件 (*)",
-        )
-        if path:
-            self.config_edit.setText(path)
-
-    def _on_reset(self):
-        """Reset optical flow tracker when drift occurs (same as basic_pipeline 'r' key)."""
-        if self.sensor is None or not self._running:
-            print("请先启动传感器后再重置追踪器。")
-            return
-        self.sensor.reset()
-        print("追踪器已重置。")
-
-    def keyPressEvent(self, event):
-        key = event.key()
-        if key == Qt.Key_Escape:
-            if self.isFullScreen():
-                self.showNormal()
-            else:
-                self.showFullScreen()
-        elif key == Qt.Key_Q:
-            print("\n正在退出示例程序...")
-            self.close()
-        elif key == Qt.Key_S:
-            self._start_recording()
-        elif key == Qt.Key_E:
-            self._stop_recording()
-        elif key == Qt.Key_R:
-            self._on_reset()
-        else:
-            super().keyPressEvent(event)
-
-    def _start_recording(self):
-        if self.sensor is None:
-            print("请先启动采集")
-            return
-        self.save_path = "./data/pulse_test.mp4"
-        os.makedirs(os.path.dirname(self.save_path), exist_ok=True)
-
-        save_img = self.sensor.frame
-        if save_img is None:
-            print("当前没有可用帧，无法确定录像尺寸。")
-            return
-
-        temp_img = save_img.copy()
-        if len(temp_img.shape) == 2 or (len(temp_img.shape) == 3 and temp_img.shape[2] == 1):
-            if len(temp_img.shape) == 3:
-                temp_img = temp_img.squeeze(2)
-            temp_img = cv2.cvtColor(temp_img, cv2.COLOR_GRAY2BGR)
-
-        fh, fw = temp_img.shape[:2]
-        self.writer = cv2.VideoWriter(
-            self.save_path, cv2.VideoWriter_fourcc(*'mp4v'), 30, (fw, fh),
-        )
-        if self.writer.isOpened():
-            self.is_save = True
-            print(f"开始录像：{self.save_path}")
-        else:
-            print(f"无法创建录像文件：{self.save_path}")
-            self.writer = None
-
-    def _stop_recording(self):
-        self.is_save = False
-        if self.writer is not None:
-            self.writer.release()
-            self.writer = None
-        if self.save_path is not None:
-            print(f"录像结束：{self.save_path}，总帧数：{self.frame_count}")
-        else:
-            print(f"录像结束，总帧数：{self.frame_count}")
-        self.frame_count = 0
-
-    def closeEvent(self, event):
-        self.timer.stop()
-        if self.writer is not None:
-            self.writer.release()
-        if self.sensor is not None:
-            self.sensor.disconnect()
-        event.accept()
-
-# ---------------------------------------------------------------------------
-# 入口
-# ---------------------------------------------------------------------------
 
 def main():
-    script_dir = os.path.dirname(os.path.abspath(__file__))
+    import argparse
-    log_dir = os.path.join(script_dir, "logs")
-    os.makedirs(log_dir, exist_ok=True)
-    log_path = os.path.join(log_dir, f"qt_viewer_{datetime.now().strftime('%Y%m%d_%H%M%S')}.log")
-    log_file = open(log_path, 'w', encoding='utf-8')
-    # stdout 到文件的临时重定向（创建 MainWindow 后会加上日志面板）
-    sys.stdout = log_file
-    sys.stderr = sys.stdout
 
-    parser = argparse.ArgumentParser()
+    parser = argparse.ArgumentParser(description="Orisys 2D Qt sensor monitor")
+    parser.add_argument(
+        "--sensor-type",
+        "-s",
+        type=str,
+        default="orisys",
+        choices=("orisys", "dd06"),
+        help="Sensor adapter: orisys (direct Sensor) or dd06 (polygon ROI rectify)",
+    )
     parser.add_argument("--video", "-v", type=str, default="0")
     parser.add_argument("--config", "-c", type=str, default="./config/ddjx01.json")
     parser.add_argument("--cal", "-cal", type=str, default="./config/ddjx01.npy")
@@ -801,18 +38,15 @@ def main():
     )
     args = parser.parse_args()
 
-    print("\n按键说明：Q 退出 | R 重置追踪器 | S 开始录像 | E 结束录像 | ESC 全屏")
+    # Sensible DD06 defaults when user only switches sensor type.
+    if args.sensor_type == "dd06":
+        if args.video in ("0", "1") and args.config.endswith("ddjx01.json"):
+            args.video = "./data/dd06/0726.mp4"
+            args.config = "./config/dd06-ov.json"
 
-    # 高 DPI 适配（笔记本高分屏）
+    log_dir = Path(__file__).resolve().parent / "logs"
-    QApplication.setAttribute(Qt.AA_EnableHighDpiScaling, True)
+    sys.exit(run_viewer(args, log_dir=log_dir))
-    QApplication.setAttribute(Qt.AA_UseHighDpiPixmaps, True)
-    app = QApplication(sys.argv)
-    window = MainWindow(args, log_file)
-    window.showFullScreen()
-    QApplication.processEvents()
-    window.adjust_square_images()
 
-    sys.exit(app.exec_())
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     main()

tests/dd06.py

@@ -0,0 +1,175 @@
+"""
+DD06 single-camera pipeline with polygon ROI rectification.
+
+Flow:
+1. Load sensor config + nested polygon ROI
+2. Capture raw frames from the video/camera source
+3. Perspective-warp the ROI into a rectangle sized to camera.resolution_stitch
+4. Feed the rectified frame into Sensor.get_img(..., already_processed=True)
+5. Compute deformation/contact and visualize
+
+SDK version: 0.3.1
+"""
+from __future__ import annotations
+
+import argparse
+import os
+import sys
+from pathlib import Path
+
+os.environ["OPENCV_VIDEOIO_MSMF_ENABLE_HW_TRANSFORMS"] = "0"
+
+import cv2
+import numpy as np
+import orisys
+
+_REPO_ROOT = Path(__file__).resolve().parents[1]
+_EXAMPLES_DIR = _REPO_ROOT / "examples"
+if str(_EXAMPLES_DIR) not in sys.path:
+    sys.path.insert(0, str(_EXAMPLES_DIR))
+
+from gui.sensors.roi_geometry import (  # noqa: E402
+    build_roi_warp,
+    load_json_config,
+    load_roi_polygon,
+    open_video_source,
+    rectified_output_size,
+    warp_roi_to_rectangle,
+)
+
+
+def main():
+    parser = argparse.ArgumentParser(
+        description="DD06 pipeline: polygon-ROI rectify -> Sensor.get_img(already_processed=True)"
+    )
+    parser.add_argument(
+        "--video",
+        "-v",
+        type=str,
+        default="./data/dd06/0726.mp4",
+        help="视频源：摄像头编号或视频文件路径",
+    )
+    parser.add_argument(
+        "--config",
+        "-c",
+        type=str,
+        default="./config/dd06-ov.json",
+        help="配置文件名称或路径",
+    )
+    parser.add_argument(
+        "--verbose",
+        "-verbose",
+        action="store_true",
+        default=True,
+        help="是否输出详细日志",
+    )
+    args = parser.parse_args()
+
+    config = load_json_config(args.config)
+    roi_points, roi_image_size = load_roi_polygon(config)
+    out_w, out_h = rectified_output_size(config, roi_points)
+
+    sensor = orisys.Sensor("external", config_name=args.config, verbose=args.verbose)
+    cap, source = open_video_source(args.video)
+
+    warp_matrix = None
+    warp_src = None
+    last_frame_size = None
+
+    print(
+        f"ROI points={len(roi_points)} source_size={roi_image_size} "
+        f"output={out_w}x{out_h} video={source}"
+    )
+    print("按键说明：'q' 退出程序，'r' 重置追踪器。")
+
+    try:
+        while True:
+            ok, frame = cap.read()
+            if not ok or frame is None:
+                print("Failed to read frame from video source.")
+                break
+
+            frame_h, frame_w = frame.shape[:2]
+            frame_size = (frame_w, frame_h)
+            if warp_matrix is None or last_frame_size != frame_size:
+                warp_matrix, warp_src, _ = build_roi_warp(
+                    roi_points,
+                    roi_image_size,
+                    frame_size,
+                    (out_w, out_h),
+                )
+                last_frame_size = frame_size
+                if args.verbose:
+                    print(f"Built ROI warp for frame {frame_w}x{frame_h}:\n{warp_src}")
+
+            rectified = warp_roi_to_rectangle(frame, warp_matrix, (out_w, out_h))
+            sensor.get_img(frame=rectified, already_processed=True)
+
+            is_contact_now = sensor.compute_deformation(check_motion=True, threshold=0)
+            _ = is_contact_now
+            sensor.compute_contact()
+
+            fps, flow, vnormal, img, contour, centroid, depth_map, fnormal, fshearx, fsheary = (
+                sensor.read_info(
+                    sensor.info.FPS,
+                    sensor.info.VRAW,
+                    sensor.info.VNORMAL,
+                    sensor.info.IMG,
+                    sensor.info.CONTOUR,
+                    sensor.info.CENTROID,
+                    sensor.info.DEPTH,
+                    sensor.info.FNORMAL,
+                    sensor.info.FSHEARX,
+                    sensor.info.FSHEARY,
+                )
+            )
+
+            preview = frame.copy()
+            cv2.polylines(
+                preview,
+                [np.rint(warp_src).astype(np.int32).reshape(-1, 1, 2)],
+                True,
+                (0, 255, 255),
+                2,
+                cv2.LINE_AA,
+            )
+
+            arrows = orisys.util.draw_arrows(
+                img,
+                flow,
+                threshold=1,
+                grid_spacing=20,
+                arrow_scale=1.0,
+            )
+            cv2.imshow("形变矢量场", arrows)
+
+            div_abs = depth_map
+            if div_abs.max() > div_abs.min():
+                div_normalized = (
+                    (div_abs - div_abs.min()) / (div_abs.max() - div_abs.min()) * 255
+                ).astype(np.uint8)
+            else:
+                div_normalized = np.zeros_like(div_abs, dtype=np.uint8)
+            cv2.imshow("depth", cv2.applyColorMap(div_normalized, cv2.COLORMAP_JET))
+
+            print(
+                f"FPS={fps:.2f}, 法向力={fnormal:.4f}, 切向力X={fshearx:.4f}, "
+                f"切向力Y={fsheary:.4f}, 深度图尺寸={depth_map.shape}, "
+                f"原始分辨率={sensor.img_size_raw}, 矫正={rectified.shape[1]}x{rectified.shape[0]}"
+            )
+
+            key = cv2.waitKey(1) & 0xFF
+            if key == ord("q"):
+                print("\n正在退出示例程序...")
+                break
+            if key == ord("r"):
+                sensor.reset()
+                print("追踪器已重置。")
+    finally:
+        cap.release()
+        sensor.disconnect()
+        cv2.destroyAllWindows()
+
+
+if __name__ == "__main__":
+    main()

tests/test_qt_viewer_backend.py

@@ -0,0 +1,165 @@
+"""Tests for Qt viewer backend force history and aspect-aware display helpers."""
+
+from __future__ import annotations
+
+import sys
+import types
+from pathlib import Path
+from unittest.mock import MagicMock
+
+import numpy as np
+import pytest
+
+_REPO_ROOT = Path(__file__).resolve().parents[1]
+_EXAMPLES_DIR = _REPO_ROOT / "examples"
+if str(_EXAMPLES_DIR) not in sys.path:
+    sys.path.insert(0, str(_EXAMPLES_DIR))
+
+from gui.viewer2d.backend import (  # noqa: E402
+    QtViewerBackend,
+    image_shape_meta,
+    panel_width_for_aspect,
+    scale_bgr_to_fit,
+    select_display_image,
+)
+from gui.sensors import (  # noqa: E402
+    FrameSnapshot,
+    _snapshot_from_sensor,
+    calibrate_normal_force,
+)
+
+
+class FakeForceAdapter:
+    """Minimal adapter that emits changing FN/FX/FY without a real sensor."""
+
+    def __init__(self):
+        self._i = 0
+
+    def read(self):
+        i = self._i
+        self._i += 1
+        return FrameSnapshot(
+            image=np.zeros((100, 200, 3), dtype=np.uint8),
+            normal_force=1000.0 + 50.0 * i,
+            shear_x=-200.0 + 10.0 * i,
+            shear_y=300.0 - 5.0 * i,
+            normal_force_calibrated=calibrate_normal_force(1000.0 + 50.0 * i),
+            fps=30.0,
+            timestamp=float(i) / 30.0,
+            flow_overlay=np.zeros((100, 200, 3), dtype=np.uint8),
+            record_frame=np.zeros((100, 200, 3), dtype=np.uint8),
+        )
+
+
+def test_backend_force_history_tracks_all_channels():
+    adapter = FakeForceAdapter()
+    backend = QtViewerBackend(npoints=32, lowpass_cutoff_hz=0.0)
+
+    for _ in range(8):
+        snap = adapter.read()
+        backend.ingest(snap, now=snap.timestamp)
+
+    state = backend.plot_state()
+    assert state is not None
+    assert state.sample_count == 8
+    assert state.values.shape == (8, 3)
+
+    # All three channels must change across frames (not stay flat).
+    fn_span = float(state.values[:, 0].max() - state.values[:, 0].min())
+    fx_span = float(state.values[:, 1].max() - state.values[:, 1].min())
+    fy_span = float(state.values[:, 2].max() - state.values[:, 2].min())
+    assert fn_span > 100.0
+    assert fx_span > 20.0
+    assert fy_span > 10.0
+
+    # Raw FN is used for curves, not the tiny calibrated Newton scale.
+    assert float(state.values[-1, 0]) == pytest.approx(1000.0 + 50.0 * 7)
+
+
+@pytest.mark.parametrize(
+    "shape,expected_aspect",
+    [
+        ((100, 200, 3), 2.0),  # wide
+        ((120, 120, 3), 1.0),  # square
+        ((200, 100, 3), 0.5),  # portrait
+    ],
+)
+def test_backend_image_aspect_metadata(shape, expected_aspect):
+    img = np.zeros(shape, dtype=np.uint8)
+    h, w, aspect = image_shape_meta(img)
+    assert (h, w) == (shape[0], shape[1])
+    assert aspect == pytest.approx(expected_aspect)
+
+    snap = FrameSnapshot(flow_overlay=img, normal_force=1.0, shear_x=2.0, shear_y=3.0)
+    backend = QtViewerBackend(lowpass_cutoff_hz=0.0)
+    frame = backend.ingest(snap, now=0.0)
+    assert frame.image_height == shape[0]
+    assert frame.image_width == shape[1]
+    assert frame.aspect_ratio == pytest.approx(expected_aspect)
+
+    fitted = scale_bgr_to_fit(img, max_w=80, max_h=80)
+    fh, fw = fitted.shape[:2]
+    assert fw <= 80 and fh <= 80
+    assert abs((fw / fh) - expected_aspect) < 0.05
+
+    panel_w = panel_width_for_aspect(200, expected_aspect, min_size=160)
+    assert panel_w >= 160
+    assert panel_w == pytest.approx(max(160, int(round(200 * expected_aspect))))
+
+
+def test_select_display_image_prefers_flow_overlay():
+    overlay = np.full((10, 20, 3), 7, dtype=np.uint8)
+    processed = np.full((10, 20, 3), 3, dtype=np.uint8)
+    snap = FrameSnapshot(flow_overlay=overlay, processed_image=processed, image=processed)
+    out = select_display_image(snap)
+    assert np.array_equal(out, overlay)
+
+
+def test_snapshot_requests_hhd_every_frame_without_motion_gate():
+    """Regression: force refresh must not use check_motion=True gating."""
+    sensor = MagicMock()
+    sensor.img = np.zeros((32, 32), dtype=np.uint8)
+    sensor.frame = np.zeros((32, 32), dtype=np.uint8)
+    sensor.info = types.SimpleNamespace(
+        FPS="FPS",
+        VRAW="VRAW",
+        VNORMAL="VNORMAL",
+        IMG="IMG",
+        CONTOUR="CONTOUR",
+        CENTROID="CENTROID",
+        DEPTH="DEPTH",
+        FNORMAL="FNORMAL",
+        FSHEARX="FSHEARX",
+        FSHEARY="FSHEARY",
+    )
+    sensor.read_info.return_value = (
+        30.0,
+        np.zeros((32, 32, 2), dtype=np.float32),
+        np.zeros((32, 32), dtype=np.float32),
+        sensor.img,
+        None,
+        None,
+        np.zeros((32, 32), dtype=np.float32),
+        12345.0,
+        -100.0,
+        50.0,
+    )
+
+    # Avoid depending on orisys.util.draw_arrows implementation details.
+    import gui.sensors.adapter as sa
+
+    original_util = sa.orisys.util
+    sa.orisys.util = types.SimpleNamespace(
+        draw_arrows=lambda *args, **kwargs: np.zeros((32, 32, 3), dtype=np.uint8)
+    )
+    try:
+        snap = _snapshot_from_sensor(sensor, raw_image=sensor.frame, processed_image=sensor.img)
+    finally:
+        sa.orisys.util = original_util
+
+    sensor.compute_deformation.assert_called_once_with(decompose=True, check_motion=False)
+    assert snap is not None
+    assert snap.normal_force == pytest.approx(12345.0)
+    assert snap.shear_x == pytest.approx(-100.0)
+    assert snap.shear_y == pytest.approx(50.0)
+    assert snap.normal_force_calibrated == pytest.approx(calibrate_normal_force(12345.0))

tools/ffc/roi_polygon_tool.py

@@ -1,6 +1,8 @@
 from __future__ import annotations
 
+import argparse
 import json
+import os
 from datetime import datetime
 from pathlib import Path
 
@@ -8,7 +10,8 @@ import cv2
 import numpy as np
 
 
-WINDOW_NAME = "ROI Polygon Editor"
+WINDOW_NAME = "ROI Editor"
+POLYGON_WINDOW_NAME = "ROI Polygon Editor"
 
 
 def to_uint8_image(image):
@@ -49,33 +52,6 @@ def polygon_to_mask(points, image_size):
     return mask
 
 
-def save_polygon_roi_config(path, points, image_size, mask_path=None, metadata=None):
-    path = Path(path)
-    path.parent.mkdir(parents=True, exist_ok=True)
-    data = {
-        "version": "1.0",
-        "type": "polygon",
-        "image_size": [int(image_size[0]), int(image_size[1])],
-        "points": [[int(x), int(y)] for x, y in points],
-        "created_at": datetime.now().isoformat(timespec="seconds"),
-    }
-    if mask_path is not None:
-        data["mask_path"] = str(mask_path)
-    if metadata:
-        data["metadata"] = metadata
-    with path.open("w", encoding="utf-8") as f:
-        json.dump(data, f, indent=2, ensure_ascii=False)
-    return data
-
-
-def load_roi_config(path):
-    path = Path(path)
-    with path.open("r", encoding="utf-8") as f:
-        data = json.load(f)
-    data["_config_path"] = str(path)
-    return data
-
-
 def scale_points(points, source_size, target_size):
     source_w, source_h = int(source_size[0]), int(source_size[1])
     target_w, target_h = int(target_size[0]), int(target_size[1])
@@ -97,20 +73,96 @@ def normalize_mask(mask, shape):
     return np.where(mask > 0, 255, 0).astype(np.uint8)
 
 
+def build_roi_payload(image_size, points, mask_path=None, metadata=None):
+    """Build the shared ``roi`` object written into sensor / FFC JSON configs."""
+    points = np.asarray(points, dtype=np.int32).reshape(-1, 2)
+    if len(points) < 3:
+        raise ValueError("polygon ROI requires at least 3 points")
+    payload = {
+        "type": "polygon",
+        "image_size": [int(image_size[0]), int(image_size[1])],
+        "points": [[int(x), int(y)] for x, y in points],
+        "created_at": datetime.now().isoformat(timespec="seconds"),
+    }
+
+    if mask_path is not None:
+        payload["mask_path"] = str(mask_path)
+    if metadata:
+        payload["metadata"] = metadata
+    return payload
+
+
+def extract_roi_section(data):
+    """Return the ROI dict from either a nested ``roi`` field or a legacy top-level ROI file."""
+    if not isinstance(data, dict):
+        raise TypeError("ROI config must be a JSON object")
+    if isinstance(data.get("roi"), dict):
+        return data["roi"]
+    return data
+
+
+def load_roi_config(path):
+    path = Path(path)
+    with path.open("r", encoding="utf-8") as f:
+        data = json.load(f)
+    data["_config_path"] = str(path)
+    return data
+
+
+def save_polygon_roi_config(path, points, image_size, mask_path=None, metadata=None):
+    """Backward-compatible standalone polygon ROI JSON writer."""
+    path = Path(path)
+    path.parent.mkdir(parents=True, exist_ok=True)
+    data = build_roi_payload(
+        image_size,
+        points,
+        mask_path=mask_path,
+        metadata=metadata,
+    )
+    data["version"] = "1.0"
+    with path.open("w", encoding="utf-8") as f:
+        json.dump(data, f, indent=2, ensure_ascii=False)
+    return data
+
+
+def upsert_roi_in_config(path, roi_payload, *, create_if_missing=True):
+    """Read-modify-write ``roi`` into an existing sensor config, preserving other fields."""
+    path = Path(path)
+    path.parent.mkdir(parents=True, exist_ok=True)
+    if path.exists():
+        with path.open("r", encoding="utf-8") as f:
+            data = json.load(f)
+        if not isinstance(data, dict):
+            raise ValueError(f"Config must be a JSON object: {path}")
+    elif create_if_missing:
+        data = {"version": "1.0"}
+    else:
+        raise FileNotFoundError(f"Config not found: {path}")
+
+    data["roi"] = roi_payload
+    with path.open("w", encoding="utf-8") as f:
+        json.dump(data, f, indent=2, ensure_ascii=False)
+        f.write("\n")
+    return data
+
+
 def load_roi_mask(config_path, frame_shape):
     config_path = Path(config_path)
     data = load_roi_config(config_path)
+    roi = extract_roi_section(data)
 
     height, width = frame_shape[:2]
-    points = data.get("points") or data.get("polygon") or data.get("roi_polygon")
+    target_size = (width, height)
+    source_size = roi.get("image_size") or data.get("image_size") or [width, height]
+    points = roi.get("points")
+    points = roi.get("points") or roi.get("polygon") or roi.get("roi_polygon")
     if points:
-        source_size = data.get("image_size", [width, height])
+        polygon = scale_points(points, source_size, target_size).reshape(-1, 1, 2)
-        polygon = scale_points(points, source_size, (width, height)).reshape(-1, 1, 2)
         output = np.zeros((height, width), dtype=np.uint8)
         cv2.fillPoly(output, [polygon], 255)
         return output
 
-    mask_path = data.get("mask_path") or data.get("roi_mask")
+    mask_path = roi.get("mask_path") or data.get("mask_path") or data.get("roi_mask")
     if mask_path:
         mask_path = Path(mask_path)
         if not mask_path.is_absolute():
@@ -123,6 +175,54 @@ def load_roi_mask(config_path, frame_shape):
     raise ValueError(f"Unsupported ROI config: {config_path}")
 
 
+def resolve_video_source(video):
+    """Accept camera index (int/str digit) or filesystem path."""
+    if isinstance(video, int):
+        return video
+    text = str(video).strip()
+    if text.isdigit():
+        return int(text)
+    return text
+
+
+def open_video_capture(video):
+    source = resolve_video_source(video)
+    # Avoid MSMF HW transform stalls on Windows camera capture.
+    os.environ.setdefault("OPENCV_VIDEOIO_MSMF_ENABLE_HW_TRANSFORMS", "0")
+    if isinstance(source, int):
+        cap = cv2.VideoCapture(source, cv2.CAP_DSHOW)
+        if not cap.isOpened():
+            cap.release()
+            cap = cv2.VideoCapture(source)
+    else:
+        path = Path(source)
+        if not path.exists():
+            raise FileNotFoundError(f"Video file not found: {path}")
+        cap = cv2.VideoCapture(str(path))
+    if not cap.isOpened():
+        raise RuntimeError(f"Failed to open video source: {video}")
+    return cap
+
+
+def capture_frame(cap, *, max_attempts=60):
+    """Grab the next readable frame from an opened capture."""
+    last_error = None
+    for _ in range(max_attempts):
+        ok, frame = cap.read()
+        if ok and frame is not None and getattr(frame, "size", 0) > 0:
+            return normalize_editor_frame(frame)
+        last_error = "empty frame" if ok else "read failed"
+    raise RuntimeError(f"Failed to capture frame from video source ({last_error})")
+
+
+def capture_frame_from_source(video):
+    cap = open_video_capture(video)
+    try:
+        return capture_frame(cap)
+    finally:
+        cap.release()
+
+
 class RoiPolygonEditor:
     def __init__(self, frame):
         self.frame = normalize_editor_frame(frame)
@@ -187,25 +287,85 @@ class RoiPolygonEditor:
         return view
 
 
-def build_roi_result(points, image_size, mask, config=None, config_path=None, mask_path=None):
+def build_roi_result(
-    return {
+    points,
-        "points": [[int(x), int(y)] for x, y in points],
+    image_size,
+    mask,
+    config=None,
+    config_path=None,
+    mask_path=None,
+):
+    result = {
+        "type": "polygon",
+        "points": [[int(x), int(y)] for x, y in points] if points is not None else None,
         "image_size": [int(image_size[0]), int(image_size[1])],
         "mask": mask,
         "config": config,
         "config_path": str(config_path) if config_path is not None else None,
         "mask_path": str(mask_path) if mask_path is not None else None,
     }
+    return result
+
+
+def _save_roi_outputs(
+    *,
+    image_size,
+    output,
+    points,
+    metadata=None,
+    save_mask=True,
+    nest_in_config=True,
+):
+    mask = polygon_to_mask(points, image_size)
+    config = None
+    config_path = None
+    mask_path = None
+
+    if output is not None:
+        config_path = Path(output)
+        config_path.parent.mkdir(parents=True, exist_ok=True)
+        saved_mask = None
+        if save_mask:
+            mask_path = config_path.with_name(config_path.stem + "_mask.png")
+            cv2.imwrite(str(mask_path), mask)
+            saved_mask = mask_path.name
+
+        roi_payload = build_roi_payload(
+            image_size,
+            points,
+            mask_path=saved_mask,
+            metadata=metadata,
+        )
+        if nest_in_config:
+            config = upsert_roi_in_config(config_path, roi_payload)
+        else:
+            # Standalone ROI file (legacy FFC polygon style).
+            standalone = dict(roi_payload)
+            standalone["version"] = "1.0"
+            with config_path.open("w", encoding="utf-8") as f:
+                json.dump(standalone, f, indent=2, ensure_ascii=False)
+                f.write("\n")
+            config = standalone
+
+    return build_roi_result(
+        points,
+        image_size,
+        mask,
+        config=config,
+        config_path=config_path,
+        mask_path=mask_path,
+    )
 
 
 def select_polygon_roi(
     frame,
     output=None,
-    window_name=WINDOW_NAME,
+    window_name=POLYGON_WINDOW_NAME,
     metadata=None,
     save_mask=True,
     destroy_window=True,
     recapture_callback=None,
+    nest_in_config=False,
 ):
     """Open an OpenCV window, draw a polygon ROI, and return points/mask/config info."""
     editor = RoiPolygonEditor(frame)
@@ -230,35 +390,95 @@ def select_polygon_roi(
                     continue
 
                 image_size = (editor.frame.shape[1], editor.frame.shape[0])
-                mask = polygon_to_mask(editor.points, image_size)
+                return _save_roi_outputs(
-                config = None
+                    image_size=image_size,
-                config_path = None
+                    output=output,
-                mask_path = None
+                    points=editor.points,
-
-                if output is not None:
-                    config_path = Path(output)
-                    config_path.parent.mkdir(parents=True, exist_ok=True)
-                    saved_mask = None
-                    if save_mask:
-                        mask_path = config_path.with_name(config_path.stem + "_mask.png")
-                        cv2.imwrite(str(mask_path), mask)
-                        saved_mask = mask_path.name
-                    config = save_polygon_roi_config(
-                        config_path,
-                        editor.points,
-                        image_size,
-                        mask_path=saved_mask,
                     metadata=metadata,
-                    )
+                    save_mask=save_mask,
-
+                    nest_in_config=nest_in_config,
-                return build_roi_result(
-                    editor.points,
-                    image_size,
-                    mask,
-                    config=config,
-                    config_path=config_path,
-                    mask_path=mask_path,
                 )
     finally:
         if destroy_window:
             cv2.destroyWindow(window_name)
+
+
+select_roi = select_polygon_roi
+
+
+def parse_args(argv=None):
+    parser = argparse.ArgumentParser(
+        description="Capture a frame from a camera/video and save a polygon ROI to JSON."
+    )
+    parser.add_argument(
+        "--video",
+        "-v",
+        required=True,
+        help="Camera index (e.g. 0) or path to a video file",
+    )
+    parser.add_argument(
+        "--config",
+        "-c",
+        required=True,
+        help="Output JSON config path (existing sensor configs are updated in place)",
+    )
+    parser.add_argument(
+        "--frame-output",
+        default=None,
+        help="Optional path to save the captured reference frame (PNG/JPG)",
+    )
+    parser.add_argument(
+        "--no-mask",
+        action="store_true",
+        help="Do not write a companion *_mask.png next to the config",
+    )
+    return parser.parse_args(argv)
+
+
+def main(argv=None):
+    args = parse_args(argv)
+    video = resolve_video_source(args.video)
+    cap = open_video_capture(video)
+
+    def recapture():
+        # For file sources, rewind so R always gets a usable frame.
+        if not isinstance(video, int):
+            cap.set(cv2.CAP_PROP_POS_FRAMES, 0)
+        return capture_frame(cap)
+
+    try:
+        frame = capture_frame(cap)
+        if args.frame_output:
+            frame_path = Path(args.frame_output)
+            frame_path.parent.mkdir(parents=True, exist_ok=True)
+            cv2.imwrite(str(frame_path), frame)
+            print(f"Saved reference frame: {frame_path}")
+
+        result = select_polygon_roi(
+            frame,
+            output=args.config,
+            metadata={"source": str(args.video)},
+            save_mask=not args.no_mask,
+            recapture_callback=recapture,
+            nest_in_config=True,
+        )
+    finally:
+        cap.release()
+        cv2.destroyAllWindows()
+
+    if result is None:
+        print("ROI capture cancelled.")
+        return 1
+
+    print(f"Saved ROI type={result['type']} image_size={result['image_size']}")
+    if result.get("points") is not None:
+        print(f"points={result['points']}")
+    if result.get("config_path"):
+        print(f"config={result['config_path']}")
+    if result.get("mask_path"):
+        print(f"mask={result['mask_path']}")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())