wild_test
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@@ -62,18 +62,19 @@ cd /home/zhangw/scan-calibrator
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① 当前是【野外部署阶段】（回复 1）还是【办公室测试阶段】（回复 2）？
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> 2
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② 请在Web界面中固定本次扫描使用的zoom，再手动把摄像头移到扫描区域的【左上角】。
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② 请在Web界面中设置左上角zoom，再手动把摄像头移到扫描区域的【左上角】。
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到位后回复 1；回复 3 随时退出。
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> 1
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已读取: pan=19120 (191.20°), tilt=990 (9.90°), zoom=810 (8.10×)
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③ 请保持zoom不变，手动把摄像头移到扫描区域的【右下角】。
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③ 请手动把摄像头移到扫描区域的【右下角】。
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右下角可以使用不同zoom，程序会取两个角点zoom的平均值作为最终扫描zoom。
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到位后回复 1；回复 3 随时退出。
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> 1
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已读取: pan=13420 (134.20°), tilt=-340 (-3.40°), zoom=810 (8.10×)
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④ 这一步用于测量当前zoom下的水平/垂直视场。
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请保持zoom不变，优先把摄像头移到扫描区域内部、距离较远且纹理分布在整幅画面的位置。
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请把摄像头移到扫描区域内部、距离较远且纹理分布在整幅画面的位置。
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请避开纯天空、纯墙面、水面、玻璃、近距离物体和重复图案；
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回复1后不要再操作Web云台，程序会自动移动、拍照并返回起点。
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到位后回复 1；回复 3 随时退出。
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@@ -156,7 +157,7 @@ cd /home/zhangw/scan-calibrator
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### ② 记录左上角
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现场人员先在Web界面设置固定zoom，并移动到扫描区域左上角。回复`1`后，向导通过
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现场人员先在Web界面设置左上角zoom，并移动到扫描区域左上角。回复`1`后，向导通过
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smart-cam的HTTP接口读取PTZ并记录，等价于：
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```bash
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@@ -168,22 +169,24 @@ smart-cam的HTTP接口读取PTZ并记录，等价于：
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### ③ 记录右下角
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保持zoom不变，移动到右下角。回复`1`后等价于：
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移动到右下角；这里允许根据覆盖范围使用不同zoom。回复`1`后等价于：
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```bash
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./calibrate.sh ptz
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./calibrate.sh mark bottom-right
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```
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向导会比较两个角点的zoom；不一致时立即停止，避免用不同视场计算网格。
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向导会显示两个角点的zoom，并取算术平均值作为最终扫描zoom。第四步开始测量前，
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程序会自动把镜头切换到该平均zoom，因此视场标定与最终配置使用同一焦段。
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### ④ 自动计算pan_step和tilt_step
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现场人员保持zoom不变，把镜头移到扫描区域内部、距离较远且纹理丰富的位置。
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现场人员把镜头移到扫描区域内部、距离较远且纹理丰富的位置。
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回复`1`后，向导会：
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1. 抓取基准图；
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2. 沿pan方向尝试若干候选角度，每次抓图后回到起点；
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2. 沿pan方向先从小角度探测；取得首个有效样本后立即反算当前zoom的视场，
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并自适应补测约82%、72%、60%、48%、35%重叠附近的候选角度，每次抓图后回到起点；
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3. 用ORB特征、RANSAC和单轴画面位移求水平视场；
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4. 沿tilt方向重复测量；
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5. 每个方向统一筛选相互一致的视场样本；获得4个覆盖充分、离散度不超过8%的
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@@ -203,8 +206,9 @@ smart-cam的HTTP接口读取PTZ并记录，等价于：
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这一步不能省略。两个角点只能确定扫描范围，无法确定当前摄像头型号和zoom下的一幅画面
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覆盖多少角度。
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不要把画面对准纯天空、纯墙、水面、玻璃、近距离物体或重复图案，否则无法可靠匹配。
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这一步不能改变zoom；自动对焦不影响zoom。标定失败时可以只更换第四步的位置重试，
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不要把画面对准纯天空、纯墙、纯水面、玻璃、近距离物体或重复图案。水面场景应让岸线、
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浮标等固定物体横向分布在画面中，不能只依赖不断变化的水纹。
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测量过程中程序会锁定两个角点的平均zoom；自动对焦不影响zoom。标定失败时可以只更换第四步的位置重试，
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不需要重新记录左上角和右下角。
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### ⑤ 显示最终参数
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+76
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@@ -72,9 +72,32 @@ def remove_session_snapshots(paths: set[str]) -> None:
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def candidate_deltas(axis: str) -> list[int]:
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"""Coarse probes from narrow to wide FOV.
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Once any probe provides a usable FOV estimate, estimate_axis replaces the
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wide tail with scene/camera-specific deltas. Dense small values are
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important at high optical zoom, where a jump from 150 to 250 PTZ units can
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go directly from useful overlap to no common image.
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"""
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if axis == "pan":
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return [150, 250, 350, 450, 600, 800, 1100, 1500, 2100]
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return [80, 120, 170, 220, 280, 350, 450, 600, 850, 1150]
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return [50, 75, 110, 150, 220, 320, 470, 700, 1050, 1500, 2100]
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return [25, 40, 60, 90, 130, 190, 280, 420, 620, 850, 1150]
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def fov_guided_deltas(delta: int, overlap: float, axis: str) -> list[int]:
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"""Choose probes that retain enough shared image for robust matching."""
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shift = 1.0 - overlap
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if not 0.04 <= shift <= 0.92:
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return []
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estimated_fov = delta / shift
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minimum = 20 if axis == "pan" else 12
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# Fractions are image displacement/FOV, hence target overlaps are roughly
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# 82%, 72%, 60%, 48% and 35%. The middle probes provide the strongest
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# cross-check, while the last one confirms the wider displacement model.
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return sorted({
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max(minimum, round(estimated_fov * fraction))
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for fraction in (0.18, 0.28, 0.40, 0.52, 0.65)
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})
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def choose_direction(axis: str, origin: dict[str, int], points: dict) -> int:
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@@ -239,7 +262,14 @@ def estimate_axis(axis: str, origin: dict[str, int], points: dict,
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failure_reasons: dict[str, int] = {}
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say(f"\n正在标定 {axis}_step，摄像头会自动移动并回到起点……")
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for delta in candidate_deltas(axis):
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pending = candidate_deltas(axis)
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tested: set[int] = set()
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adaptive_seeded = False
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while pending:
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delta = pending.pop(0)
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if delta in tested:
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continue
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tested.add(delta)
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result = core.measure_delta(
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axis, delta, direction, 1.0, baseline=baseline, origin=origin
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)
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@@ -270,6 +300,22 @@ def estimate_axis(axis: str, origin: dict[str, int], points: dict,
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else:
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quality = f"有效特征={inliers}，内点率={ratio*100:.1f}%"
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say(f" step={delta}: 重叠约 {overlap*100:.1f}%，{quality}")
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if not adaptive_seeded:
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guided = fov_guided_deltas(delta, overlap, axis)
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if guided:
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# Keep only a small safety tail beyond the guided range. Very
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# large fixed probes cannot match once the current optical FOV
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# has been measured and only waste time.
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cap = round(max(guided) * 1.15)
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pending = sorted({
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value for value in guided + pending
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if value not in tested and value <= cap
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})
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adaptive_seeded = True
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say(
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f" 已根据首个有效样本自适应生成后续step："
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f"{', '.join(str(value) for value in pending)}"
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)
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feature_reliable = inliers >= 50 and ratio >= 0.45
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phase_reliable = (
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result.get("match_method") == "phase_correlation"
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@@ -423,8 +469,19 @@ def estimate_axis(axis: str, origin: dict[str, int], points: dict,
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def calculate_steps(points: dict, snapshots: set[str], mount: str) -> None:
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origin = camera_ptz()
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zooms = [int(points[name]["zoom"]) for name in ("top-left", "bottom-right")]
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if max(zooms + [origin["zoom"]]) - min(zooms + [origin["zoom"]]) > 10:
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core.fail("三个位置的zoom不一致；请固定焦段后重新开始")
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target_zoom = round(sum(zooms) / len(zooms))
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if origin["zoom"] != target_zoom:
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say(
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f"两个角点zoom的平均值为{target_zoom}（{target_zoom/100:.2f}×）；"
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"正在自动切换到该zoom后再测量视场……"
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)
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origin = core.move({**origin, "zoom": target_zoom})
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time.sleep(1.0)
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if abs(int(origin["zoom"]) - target_zoom) > 10:
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core.fail(
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f"摄像头未能到达平均zoom：目标={target_zoom}，实际={origin['zoom']}"
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)
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core.print_ptz(origin, "平均zoom到位")
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top_left = points["top-left"]
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bottom_right = points["bottom-right"]
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# This check is only advisory and runs before signed pan direction has
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@@ -624,7 +681,7 @@ def main() -> None:
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mount = "hanging" if stage == "1" else "desktop"
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confirm_position(
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"② 请在Web界面中固定本次扫描使用的zoom，"
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"② 请在Web界面中设置左上角需要的zoom，"
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"再手动把摄像头移到扫描区域的【左上角】。"
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)
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top_left = camera_ptz()
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@@ -633,11 +690,16 @@ def main() -> None:
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core.save_state(state)
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confirm_position(
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"③ 请保持zoom不变，手动把摄像头移到扫描区域的【右下角】。"
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"③ 请手动把摄像头移到扫描区域的【右下角】。\n"
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"右下角可以使用不同zoom，程序会取两个角点zoom的平均值作为最终扫描zoom。"
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)
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bottom_right = camera_ptz()
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if abs(top_left["zoom"] - bottom_right["zoom"]) > 10:
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core.fail("左右角的zoom不一致，请固定焦段后重新运行")
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average_zoom = round((top_left["zoom"] + bottom_right["zoom"]) / 2)
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say(
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f"两个角点zoom：左上={top_left['zoom']/100:.2f}×，"
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f"右下={bottom_right['zoom']/100:.2f}×；"
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f"最终取平均={average_zoom/100:.2f}×。"
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)
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state = core.load_state()
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state["points"]["bottom-right"] = bottom_right
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core.save_state(state)
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@@ -646,10 +708,12 @@ def main() -> None:
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while True:
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confirm_position(
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"④ 这一步用于测量当前zoom下的水平/垂直视场。\n"
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"请保持zoom不变，优先把摄像头移到扫描区域内部、"
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"请优先把摄像头移到扫描区域内部、"
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"距离较远且纹理分布在整幅画面的位置。\n"
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"请避开纯天空、纯墙面、水面、玻璃、近距离物体和重复图案；"
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"回复1后不要再操作Web云台，程序会自动移动、拍照并返回起点。"
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"请避开纯天空、纯墙面、纯水面、玻璃、近距离物体和重复图案；"
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"水面场景需要让岸线、浮标或其他固定物体横向分布在画面中；"
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"回复1后不要再操作Web云台，程序会先切换到两个角点的平均zoom，"
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"再自动移动、拍照并返回起点。"
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)
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say("\n正在计算，请不要操作摄像头或Web控制页面……")
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try:
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@@ -422,8 +422,6 @@ def command_generate(args: argparse.Namespace) -> None:
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f"相位响应={phase_response:.2f}）；"
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f"请在纹理丰富且尽量远离摄像头的位置重新执行calibrate {axis}"
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)
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if abs(int(top_left["zoom"]) - int(bottom_right["zoom"])) > 10:
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fail("左上角和右下角zoom不一致，请固定zoom后重新记录两个角点")
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zoom = round((int(top_left["zoom"]) + int(bottom_right["zoom"])) / 2)
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pan_start, pan_end, pan_span, visual_pan_direction = scan_pan_range(
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int(top_left["pan"]),
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+3
-3
@@ -99,8 +99,8 @@ cd /home/zhangw/scan-calibrator
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### 第一步：固定zoom和焦点
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先通过Web界面把摄像头调到准备扫描时使用的zoom。整个标定过程、左上角、右下角和
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step测量必须使用同一个zoom。
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左上角和右下角可以按现场覆盖需要分别设置zoom。最终扫描zoom取两个角点读数的算术平均值，
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step测量必须在这个平均zoom下进行；交互式向导会在第四步自动切换到平均zoom。
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注意：zoom是焦段/视场角；focus是对焦清晰度，两者不是同一个参数。
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@@ -120,7 +120,7 @@ step测量必须使用同一个zoom。
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### 第三步：记录右下角
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手动移动到扫描区域右下角，zoom保持不变：
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手动移动到扫描区域右下角；zoom可以与左上角不同：
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```bash
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./calibrate.sh ptz
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Reference in new issue
Block a user