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feat: update algorithm integrations and point cloud overlays

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This commit is contained in:
lipan
2026-06-30 16:46:36 +08:00
parent ddca7e5436
commit 7e2e56a50d
64 changed files with 4356 additions and 2781 deletions
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179
server/plugins/adapters/train_measurement_run.py
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@@ -5,14 +5,14 @@
v2.2 变更：
- 算法路径从 alg/点云测距v1.1 → alg/train_measurement_system_v2.2
- 新增孔中心拟合（hole_center_fitter）、测量日志、性能日志
- 内置配置文件改为 config/measurements_0618.yaml
- TRAIN_MEAS_ROOT 指向 train_measurement_system_v2.2/（用于定位 config/）
- 内置配置文件改为 config/measurements.yaml（v3.2）
- TRAIN_MEAS_ROOT 指向 train_measurement_system_v3.2_0629/（用于定位 config/）
- 算法内置 _read_binary_ply，直接支持二进制 PLY，无需 ASCII 转换
约定：
- 第一个点云路径作为 pointcloud_file 注入到测量配置 YAML 中；
- 若用户在 UI 选择「自定义 YAML」并提供 customYaml，则使用之；
否则使用算法仓库自带的 config/measurements_0618.yaml 作为模板。
否则使用算法仓库自带的 config/measurements.yaml（v3）作为模板。
- 所有任务结果合成成 measurements[] 列表，附带可视化 PLY 路径到 extra。
"""
@@ -33,6 +33,57 @@ from _plugin_io import (
)
def _to_float(value):
if value is None:
return None
if isinstance(value, (int, float)):
return float(value)
try:
return float(str(value).strip())
except (TypeError, ValueError):
return None
def _load_excel_measurement_rows(out_dir: Path) -> dict[str, dict]:
"""读取算法导出的 Excel 结论，作为前端 measurements 的权威来源。"""
try:
from openpyxl import load_workbook
excel_files = sorted(
out_dir.glob("measurement_results_*.xlsx"),
key=lambda p: p.stat().st_mtime,
)
if not excel_files:
return {}
wb = load_workbook(excel_files[-1], data_only=True, read_only=True)
ws = wb.active
rows: dict[str, dict] = {}
for row in ws.iter_rows(min_row=2, values_only=True):
name = str(row[0] or "").strip()
if not name:
continue
conclusion = str(row[6] or "").strip()
status = None
if conclusion == "通过":
status = "pass"
elif conclusion in ("不通过", "失败"):
status = "fail"
elif conclusion == "未配置":
status = "info"
rows[name] = {
"value": _to_float(row[3]),
"toleranceLabel": str(row[2]) if row[2] is not None else None,
"status": status,
}
return rows
except Exception as exc:
print(f"读取 Excel 结论失败，继续使用适配器判定：{exc}", file=sys.stderr)
return {}
def main() -> int:
payload = load_input(sys.argv)
inputs = payload.get("inputs") or {}
@@ -41,14 +92,13 @@ def main() -> int:
out_dir.mkdir(parents=True, exist_ok=True)
try:
emit_progress(0.05, "加载 train_measurement v2.2 算法包")
emit_progress(0.05, "加载 train_measurement v3.2 算法包")
# TRAIN_MEAS_ROOT 由 manifest envExtra 注入，指向 train_measurement_system_v2.2/
# TRAIN_MEAS_ROOT 由 manifest envExtra 注入，指向 train_measurement_system_v3.2_0629/
train_root = Path(os.environ.get("TRAIN_MEAS_ROOT") or "")
if not train_root.exists():
# 回退：从 ALG_ROOT 推导
alg_root = Path(os.environ.get("ALG_ROOT") or "/alg")
train_root = alg_root / "train_measurement_system_v2.2" / "train_measurement_system_v2.2"
train_root = alg_root / "train_measurement_system_v3.2_0629"
if not train_root.exists():
raise RuntimeError(
@@ -78,8 +128,8 @@ def main() -> int:
# 已经是 YAML 格式，直接写盘
yaml_path.write_text(custom_yaml_str, encoding="utf-8")
else:
# 使用算法仓库内置的 config/measurements_0618.yaml
yaml_path = train_root / "config" / "measurements_0618.yaml"
# 使用算法仓库内置的 config/measurements.yaml（v3）
yaml_path = train_root / "config" / "measurements.yaml"
if not yaml_path.exists():
raise RuntimeError(f"内置配置文件不存在：{yaml_path}")
@@ -87,16 +137,25 @@ def main() -> int:
# ── 初始化 TaskManager ────────────────────────────────────────────────
tm = TaskManager()
# 先注入点云路径，让 load_config 跳过 YAML 里的 pointcloud_file（开发测试路径）
tm.pointcloud_path_override = pc_path
# 把输出目录重定向到 outDir，避免写到只读的 /alg 目录
tm.output_dir_override = str(out_dir)
emit_progress(0.25, f"读取点云（{os.path.basename(pc_path)}，可能需要 1~2 分钟）")
if not tm.load_config(str(yaml_path)):
raise RuntimeError(f"TaskManager 加载配置失败：{yaml_path}")
# 注入点云路径（覆盖 YAML 中的 pointcloud_file）
tm.config["pointcloud_file"] = pc_path
# 过滤 enabled=False 的任务（v3 TaskManager 不处理 enabled 字段）
import yaml as _yaml_check
_raw = _yaml_check.safe_load(yaml_path.read_text(encoding="utf-8"))
_enabled_names = {
t["name"] for t in (_raw.get("tasks") or _raw.get("measurements") or [])
if t.get("enabled", True)
}
tm.tasks = [t for t in tm.tasks if t.name in _enabled_names]
# 注入可视化输出目录
viz_dir = out_dir / "visualizations"
viz_dir.mkdir(parents=True, exist_ok=True)
@@ -104,10 +163,37 @@ def main() -> int:
if hasattr(task, "visualization_dir"):
task.visualization_dir = str(viz_dir)
emit_progress(0.30, "加载点云（已在 load_config 中完成）")
emit_progress(0.40, f"点云已加载，开始执行 {len(tm.tasks)} 个测量任务")
emit_progress(0.40, f"执行 {len(tm.tasks)} 个测量任务")
# ── 从 YAML 构建公差映射（name → {theoretical, upper, lower}） ─────────
import yaml as _yaml
try:
raw_yaml = _yaml.safe_load(yaml_path.read_text(encoding="utf-8"))
# v3 用 'tasks' key，v2 用 'measurements' key，兼容两者
task_cfgs = raw_yaml.get("tasks") or raw_yaml.get("measurements") or []
tol_map: dict[str, dict] = {}
for tc in task_cfgs:
tname = tc.get("name")
if not tname:
continue
tol = tc.get("tolerance")
theoretical = tc.get("theoretical_dimension")
if isinstance(tol, dict):
tol_map[tname] = {
"theoretical": theoretical,
"upper": float(tol.get("upper", 0)),
"lower": float(tol.get("lower", 0)),
}
elif tol is not None:
tol_map[tname] = {
"theoretical": theoretical,
"upper": float(tol),
"lower": float(tol),
}
except Exception:
tol_map = {}
results = tm.run_all_tasks()
report_rows = _load_excel_measurement_rows(out_dir)
emit_progress(0.92, "整理结果")
measurements: list[dict] = []
@@ -133,39 +219,41 @@ def main() -> int:
value = clean_data.get("mean_distance")
if value is None:
value = clean_data.get("distance")
fval = float(value) if isinstance(value, (int, float)) else None
# v3.2 data 里直接有 is_qualified 判定结果（line_to_plane/line_to_line 也支持）
data_pass = clean_data.get("is_qualified")
if data_pass is None:
data_pass = clean_data.get("pass") # 兼容旧字段名
tol_cfg = tol_map.get(name)
tolerance = None
meas_status = "info"
if data_pass is not None:
# 算法已判定，直接用
meas_status = "pass" if data_pass else "fail"
if tol_cfg:
tolerance = tol_cfg.get("upper")
elif tol_cfg and fval is not None:
theoretical = tol_cfg.get("theoretical")
upper = tol_cfg["upper"]
lower = tol_cfg["lower"]
tolerance = upper
if theoretical is not None:
error = fval - float(theoretical)
meas_status = "pass" if (-lower <= error <= upper) else "fail"
measurements.append(
{
"name": name,
"value": float(value) if isinstance(value, (int, float)) else float("nan"),
"value": fval if fval is not None else float("nan"),
"unit": "mm",
"status": "info",
"tolerance": tolerance,
"status": meas_status,
"passLabel": "通过",
"failLabel": "不通过",
}
)
std = clean_data.get("std_distance")
if isinstance(std, (int, float)):
measurements.append(
{
"name": f"{name} · 标准差",
"value": float(std),
"unit": "mm",
"status": "info",
}
)
# v1.1 新增字段：min/max distance
for field_name, label in [
("min_distance", "最小距离"),
("max_distance", "最大距离"),
]:
v = clean_data.get(field_name)
if isinstance(v, (int, float)):
measurements.append(
{
"name": f"{name} · {label}",
"value": float(v),
"unit": "mm",
"status": "info",
}
)
else:
measurements.append(
{
@@ -176,6 +264,17 @@ def main() -> int:
}
)
for measurement in measurements:
report_row = report_rows.get(measurement["name"])
if not report_row:
continue
if report_row.get("value") is not None:
measurement["value"] = report_row["value"]
if report_row.get("toleranceLabel"):
measurement["toleranceLabel"] = report_row["toleranceLabel"]
if report_row.get("status"):
measurement["status"] = report_row["status"]
success_count = sum(1 for r in results if r.get("status") == "success")
payload_out = {
"schemaVersion": 1,