tiandytmd

interactive_calibrator.py

@@ -284,12 +284,14 @@ def candidate_deltas(axis: str) -> list[int]:
     return [25, 40, 60, 90, 130, 190, 280, 420, 620, 850, 1150]
 
 
-def fov_guided_deltas(delta: int, overlap: float, axis: str) -> list[int]:
+def fov_guided_deltas(actual_delta: int, overlap: float, axis: str) -> list[int]:
     """Choose probes that retain enough shared image for robust matching."""
     shift = 1.0 - overlap
-    if not 0.04 <= shift <= 0.92:
+    # Tiny shifts amplify PTZ quantization and image-matching error. Wait for a
+    # 15%..75% real image shift before replacing the generic probe sequence.
+    if not 0.15 <= shift <= 0.75:
         return []
-    estimated_fov = delta / shift
+    estimated_fov = actual_delta / shift
     minimum = 20 if axis == "pan" else 12
     # Fractions are image displacement/FOV, hence target overlaps are roughly
     # 82%, 72%, 60%, 48% and 35%.  The middle probes provide the strongest
@@ -300,6 +302,15 @@ def fov_guided_deltas(delta: int, overlap: float, axis: str) -> list[int]:
     })
 
 
+def safe_probe_cap(actual_delta: int, overlap: float) -> int | None:
+    """Keep later probes inside the FOV already observed by the camera."""
+    shift = 1.0 - overlap
+    if actual_delta <= 0 or not 0.03 <= shift <= 0.85:
+        return None
+    estimated_fov = actual_delta / shift
+    return max(1, round(estimated_fov * 0.85))
+
+
 def choose_direction(axis: str, origin: dict[str, int], points: dict) -> int:
     if axis == "pan":
         # Pan is circular. The direction changes only the sign, not the FOV estimate.
@@ -437,12 +448,12 @@ def configured_image_aspect_ratio() -> float:
 def failure_detail(result: dict) -> str:
     reason = str(result.get("reason") or "unknown")
     labels = {
-        "ptz_motion_shortfall": "云台受限，实际移动量不足",
-        "not_enough_features": "两张图片可检测特征不足",
-        "not_enough_matches": "两张图片的公共特征不足",
-        "homography_failed": "公共特征无法形成可靠几何变换",
-        "axis_motion_too_small": "匹配到的主轴画面位移过小",
-        "axis_motion_inconsistent": "匹配位移方向异常或串轴过大",
+        "ptz_motion_shortfall": "摄像头实际移动小于请求值，本样本自动跳过",
+        "not_enough_features": "画面纹理太少，无法测量，本样本自动跳过",
+        "not_enough_matches": "移动前后相同画面太少，本样本自动跳过",
+        "homography_failed": "移动前后相同画面太少或纹理重复，本样本自动跳过",
+        "axis_motion_too_small": "画面位移太小，本样本自动跳过",
+        "axis_motion_inconsistent": "画面同时出现过大横纵位移，本样本自动跳过",
     }
     fields = []
     if result.get("actual_axis_motion") is not None:
@@ -476,6 +487,7 @@ def estimate_axis(axis: str, origin: dict[str, int], points: dict,
     pending = candidate_deltas(axis)
     tested: set[int] = set()
     adaptive_seeded = False
+    direction_switched = False
     while pending:
         delta = pending.pop(0)
         if delta in tested:
@@ -485,14 +497,20 @@ def estimate_axis(axis: str, origin: dict[str, int], points: dict,
             axis, delta, direction, 1.0, baseline=baseline, origin=origin
         )
         snapshots.add(str(result.get("candidate_file", "")))
+        actual_motion = int(result.get("actual_axis_motion") or 0)
+        switch_threshold = 150 if axis == "pan" else 90
         if (
-            axis == "tilt"
-            and not reliable
+            not reliable
+            and not direction_switched
             and result.get("reason") == "ptz_motion_shortfall"
+            and delta >= switch_threshold
+            and actual_motion < max(2, round(delta * 0.15))
         ):
             direction *= -1
+            direction_switched = True
             say(
-                f"  step={delta}: 原方向受云台限位，自动改用相反方向继续标定"
+                f"  step={delta}: {axis}在原方向基本没有移动，"
+                "可能接近限位；程序只切换一次反方向再试"
             )
             result = core.measure_delta(
                 axis, delta, direction, 1.0, baseline=baseline, origin=origin
@@ -501,7 +519,20 @@ def estimate_axis(axis: str, origin: dict[str, int], points: dict,
         if not result.get("valid"):
             reason = str(result.get("reason") or "unknown")
             failure_reasons[reason] = failure_reasons.get(reason, 0) + 1
-            say(f"  step={delta}: {failure_detail(result)}，继续尝试")
+            stop_expanding = (
+                bool(reliable)
+                and reason in {"not_enough_matches", "homography_failed"}
+            )
+            say(
+                f"  step={delta}: {failure_detail(result)}"
+                f"，{'停止扩大步长' if stop_expanding else '继续尝试'}"
+            )
+            if stop_expanding:
+                say(
+                    "  移动前后已没有足够相同画面；"
+                    "更大step只会移得更远，现在停止扩大步长。"
+                )
+                break
             continue
         overlap = float(result["overlap"])
         inliers = int(result.get("inliers") or 0)
@@ -511,8 +542,12 @@ def estimate_axis(axis: str, origin: dict[str, int], points: dict,
         else:
             quality = f"有效特征={inliers}，内点率={ratio*100:.1f}%"
         say(f"  step={delta}: 重叠约 {overlap*100:.1f}%，{quality}")
+        actual_delta = int(result.get("actual_axis_motion") or delta)
+        cap = safe_probe_cap(actual_delta, overlap)
+        if cap is not None:
+            pending = [value for value in pending if value <= max(delta, cap)]
         if not adaptive_seeded:
-            guided = fov_guided_deltas(delta, overlap, axis)
+            guided = fov_guided_deltas(actual_delta, overlap, axis)
             if guided:
                 # Keep only a small safety tail beyond the guided range. Very
                 # large fixed probes cannot match once the current optical FOV
@@ -533,11 +568,9 @@ def estimate_axis(axis: str, origin: dict[str, int], points: dict,
             and float(result.get("phase_response") or 0) >= core.PHASE_MIN_RESPONSE
         )
         if (feature_reliable or phase_reliable) and 0.08 <= overlap <= 0.90:
-            # Hikvision absolute PTZ movement is quantized and can also have
-            # backlash.  At high optical zoom, using the requested delta
-            # instead of the SDK-reported actual movement creates a large,
-            # systematic FOV error.  Shortfall samples have already been
-            # rejected above, so the actual movement is authoritative here.
+            # Absolute PTZ movement may be quantized or affected by backlash on
+            # either vendor. Use the adapter-reported motion, not the request.
+            # Shortfall samples have already been rejected above.
             actual_delta = int(result.get("actual_axis_motion") or delta)
             reliable.append((
                 actual_delta, overlap,
@@ -564,7 +597,10 @@ def estimate_axis(axis: str, origin: dict[str, int], points: dict,
         )
         core.fail(
             f"{axis}方向只得到{len(reliable)}个可靠样本，至少需要2个不同移动量互相验证。"
-            f"失败统计：{summary or '无'}。请根据上方每个step的具体原因处理后重试"
+            f"失败统计：{summary or '无'}。\n"
+            "现场处理：1. 把镜头移到扫描区域中部；"
+            "2. 画面中保留岸线、树木、建筑等固定纹理；"
+            "3. 不要操作Web云台；4. 回复1重试。"
         )
 
     # Fixed OSD text and repeated scenery can yield a convincing false
@@ -575,7 +611,9 @@ def estimate_axis(axis: str, origin: dict[str, int], points: dict,
         values = ", ".join(f"{sample[2]:.0f}" for sample in reliable)
         core.fail(
             f"{axis}方向不同移动量反算的视场不一致（{values}），疑似重复图案误匹配；"
-            "本次结果不写入配置，请更换标定画面"
+            "本次结果不写入配置。\n"
+            "现场处理：把镜头移到扫描区域中部，对准距离较远、"
+            "整幅都有不重复固定纹理的场景，然后回复1重试。"
         )
 
     estimated_fov, spread = fov_statistics(consistent)
@@ -1003,10 +1041,72 @@ def reusable_step_axes(state: dict, points: dict) -> set[str]:
     return reusable
 
 
+def acquire_calibration_control() -> bool:
+    """Pause an active patrol and wait for its in-flight PTZ command to end."""
+    status, camera = core.get_control_status()
+    host = str(camera["camera"].get("sdk_host") or "").strip()
+    detail = f"，摄像头={host}" if host else ""
+    say(
+        f"已识别摄像头适配层：vendor={camera['vendor']}{detail}；"
+        "PTZ位置读取和绝对移动能力正常。"
+    )
+    control = status.get("control", {})
+    if not isinstance(control, dict):
+        core.fail("scan HTTP未返回合法的control状态")
+    if bool(control.get("scan_active")):
+        core.fail("当前正在执行完整扫图，请等待扫图结束后再运行标定向导")
+
+    should_resume = bool(
+        control.get("patrol_active")
+        and not control.get("patrol_paused_by_operator")
+    )
+    if should_resume:
+        core.api(
+            "POST", "/api/v1/patrol/stop",
+            {"source": "scan_calibrator"}, timeout=15,
+        )
+        say("已临时暂停巡航；标定结束或正常中断时会自动恢复。", color=YELLOW)
+
+    try:
+        # This is a synchronization barrier: GET waits behind any PTZ command
+        # already in flight when patrol was paused, then claims manual control.
+        core.get_ptz()
+    except BaseException:
+        if should_resume:
+            try:
+                core.api(
+                    "POST", "/api/v1/patrol/start",
+                    {"source": "scan_calibrator"}, timeout=15,
+                )
+            except BaseException as resume_error:
+                core.warn(f"标定准备失败后未能自动恢复巡航：{resume_error}")
+        raise
+    return should_resume
+
+
+def release_calibration_control(should_resume: bool) -> None:
+    if not should_resume:
+        return
+    try:
+        core.api(
+            "POST", "/api/v1/patrol/start",
+            {"source": "scan_calibrator"}, timeout=15,
+        )
+        say("已恢复进入向导前的巡航状态。", color=YELLOW)
+    except BaseException as exc:
+        core.warn(
+            f"未能自动恢复巡航：{exc}；请执行 "
+            "docker exec smart-cam curl -sS -X POST "
+            "http://127.0.0.1:18080/api/v1/patrol/start"
+        )
+
+
 def main() -> None:
     snapshots: set[str] = set()
+    resume_patrol = False
     try:
         say("您好！我们现在开始配置扫图参数！", color=GREEN)
+        resume_patrol = acquire_calibration_control()
         say(
             "标定进度会逐步保存；中途回复 3 或按 Ctrl+C 退出后，"
             "下次运行仍可选择本次记录继续。"
@@ -1150,6 +1250,7 @@ def main() -> None:
         say(f"\n向导失败：{exc}", color=RED)
     finally:
         remove_session_snapshots(snapshots)
+        release_calibration_control(resume_patrol)
 
 
 if __name__ == "__main__":