lipan
29f1d45d66
算法更新: delivery v1.2.1、平整度v1.5、测距v2.2、整车配准v1.3 适配器: vehicle-registration 新增、各算法 manifest 和 adapter 更新 后端: taskCadFiles/source 字段迁移、derivedPointClouds 注册、取消任务联动 前端: ElapsedTime 时长显示、两步算法流程、canRun 逻辑修复 文档: 新增5份算法性能分析报告
283 lines
9.6 KiB
Python
283 lines
9.6 KiB
Python
"""算法插件适配器共用 I/O 工具。
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约定（与 server/plugins/types.ts 对齐）：
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- 子进程入口的唯一参数是 ``input.json`` 的绝对路径；
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- 子进程通过 stdout 单行 JSON 上报进度：``{"type":"progress","percent":42,"message":"..."}``
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- 子进程在 ``outDir/result.json`` 写最终结果；
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- stderr 仅做日志（runner 会原样转发）。
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所有适配器都很薄：解析 input.json → 调真实算法 API → 写 result.json。
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"""
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from __future__ import annotations
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import json
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import os
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import sys
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import time
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import traceback
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from pathlib import Path
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from typing import Any
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def load_input(argv: list[str]) -> dict[str, Any]:
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"""读取 input.json。"""
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if len(argv) < 2:
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emit_error("usage: <adapter>.py <input.json>", exit_code=2)
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path = Path(argv[1])
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if not path.exists():
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emit_error(f"input.json 不存在: {path}", exit_code=2)
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return json.loads(path.read_text(encoding="utf-8"))
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def emit_progress(percent: float, message: str = "") -> None:
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"""以单行 JSON 上报进度。runner 解析后写入数据库。
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percent 接受 0~1 或 0~100，runner 端会归一化。
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"""
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line = {"type": "progress", "percent": float(percent), "message": message}
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sys.stdout.write(json.dumps(line, ensure_ascii=False) + "\n")
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sys.stdout.flush()
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def write_result(out_dir: str | os.PathLike, payload: dict[str, Any]) -> Path:
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"""写 result.json 到 outDir，并强制 schemaVersion / status 字段存在。
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NaN/Infinity 会被替换为 null，确保输出合法 JSON。
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自动发现 outDir 下的 Excel 产物（*.xlsx / *.xls），以相对路径写入
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payload["files"]，前端据此展示下载入口（适配器也可自行预置 files）。
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"""
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import math
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def _sanitize(obj: Any) -> Any:
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# numpy 标量 → Python 原生类型
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try:
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import numpy as np # type: ignore
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if isinstance(obj, np.ndarray):
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return _sanitize(obj.tolist())
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if isinstance(obj, (np.floating,)):
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f = float(obj)
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return None if (math.isnan(f) or math.isinf(f)) else f
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if isinstance(obj, (np.integer,)):
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return int(obj)
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if isinstance(obj, (np.bool_,)):
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return bool(obj)
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except ImportError:
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pass
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if isinstance(obj, float) and (math.isnan(obj) or math.isinf(obj)):
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return None
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if isinstance(obj, dict):
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return {k: _sanitize(v) for k, v in obj.items()}
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if isinstance(obj, list):
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return [_sanitize(v) for v in obj]
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if isinstance(obj, tuple):
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return [_sanitize(v) for v in obj]
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return obj
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out_dir = Path(out_dir)
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excel_files: list[str] = list(payload.get("files") or [])
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for pattern in ("*.xlsx", "*.xls"):
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for f in sorted(out_dir.rglob(pattern)):
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rel = str(f.relative_to(out_dir))
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if rel not in excel_files:
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excel_files.append(rel)
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if excel_files:
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payload["files"] = excel_files
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out_path = out_dir / "result.json"
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payload.setdefault("schemaVersion", 1)
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payload.setdefault("status", "completed")
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out_path.write_text(json.dumps(_sanitize(payload), ensure_ascii=False, indent=2), encoding="utf-8")
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return out_path
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def write_error_result(out_dir: str | os.PathLike, message: str, extra: dict | None = None) -> None:
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"""统一错误写出：result.json 仍然存在，runner 据此把数据库改成 error。"""
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payload: dict[str, Any] = {
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"schemaVersion": 1,
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"status": "error",
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"message": message,
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}
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if extra:
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payload["extra"] = extra
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Path(out_dir).mkdir(parents=True, exist_ok=True)
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(Path(out_dir) / "result.json").write_text(
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json.dumps(payload, ensure_ascii=False, indent=2), encoding="utf-8"
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)
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def emit_error(message: str, exit_code: int = 1) -> None:
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sys.stderr.write(f"[adapter-error] {message}\n")
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sys.exit(exit_code)
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def first_pointcloud(input_payload: dict[str, Any]) -> str:
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"""取 inputs.pointCloudPaths 的第一个；无则报错。"""
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paths = (input_payload.get("inputs") or {}).get("pointCloudPaths") or []
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if not paths:
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raise RuntimeError("inputs.pointCloudPaths 为空，请确认任务已上传点云。")
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return str(paths[0])
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def now() -> float:
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return time.time()
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# ─── Binary PLY → ASCII PLY 转换 ─────────────────────────────────────────────
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def ensure_ascii_ply(src: str | os.PathLike, cache_dir: str | os.PathLike) -> str:
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"""如果 src 是二进制 PLY，把它转成 ASCII PLY 写到 cache_dir 并返回新路径。
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如果已经是 ASCII PLY 或其他格式，直接返回原路径。
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不依赖 open3d / plyfile，只用 numpy + struct（标准库）。
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"""
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src = Path(src)
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suffix = src.suffix.lower()
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if suffix != ".ply":
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return str(src)
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# 读文件头（最多 16 KB）
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HEADER_MAX = 16 * 1024
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with open(src, "rb") as fh:
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raw = fh.read(HEADER_MAX)
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try:
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header_text = raw.decode("ascii", errors="replace")
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except Exception:
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return str(src) # 无法解析，原样返回
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if not header_text.startswith("ply"):
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return str(src)
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end_marker = "end_header"
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end_idx = header_text.find(end_marker)
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if end_idx == -1:
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return str(src)
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# 找 end_header 后的换行
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data_start = end_idx + len(end_marker)
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if header_text[data_start : data_start + 2] == "\r\n":
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data_start += 2
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elif header_text[data_start] in ("\r", "\n"):
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data_start += 1
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header_lines = header_text[:end_idx].splitlines()
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# 解析 format
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fmt = "ascii"
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for line in header_lines:
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parts = line.strip().split()
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if parts and parts[0] == "format":
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fmt = parts[1] if len(parts) > 1 else "ascii"
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break
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if fmt == "ascii":
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return str(src) # 已经是 ASCII，无需转换
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# 解析 vertex 属性
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import struct as _struct
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import numpy as _np
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_PLY_DTYPE: dict[str, tuple[str, int]] = {
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"char": ("b", 1), "int8": ("b", 1),
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"uchar": ("B", 1), "uint8": ("B", 1),
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"short": ("h", 2), "int16": ("h", 2),
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"ushort": ("H", 2), "uint16": ("H", 2),
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"int": ("i", 4), "int32": ("i", 4),
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"uint": ("I", 4), "uint32": ("I", 4),
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"float": ("f", 4), "float32": ("f", 4),
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"double": ("d", 8), "float64": ("d", 8),
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}
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vertex_count = 0
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props: list[tuple[str, str, int]] = [] # (name, fmt_char, byte_size)
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in_vertex = False
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for line in header_lines:
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parts = line.strip().split()
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if not parts:
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continue
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if parts[0] == "element":
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in_vertex = parts[1] == "vertex" if len(parts) > 1 else False
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if in_vertex and len(parts) > 2:
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vertex_count = int(parts[2])
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elif parts[0] == "property" and in_vertex:
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if parts[1] == "list":
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in_vertex = False
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continue
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ptype = parts[1] if len(parts) > 1 else "float"
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pname = parts[2] if len(parts) > 2 else ""
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fc, bs = _PLY_DTYPE.get(ptype, ("f", 4))
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props.append((pname, fc, bs))
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if vertex_count == 0 or not props:
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return str(src)
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# Find x, y, z offsets
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x_off = y_off = z_off = -1
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x_fc = y_fc = z_fc = "f"
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byte_off = 0
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for pname, fc, bs in props:
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n = pname.lower()
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if n == "x":
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x_off, x_fc = byte_off, fc
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elif n == "y":
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y_off, y_fc = byte_off, fc
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elif n == "z":
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z_off, z_fc = byte_off, fc
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byte_off += bs
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if x_off < 0 or y_off < 0 or z_off < 0:
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return str(src) # 找不到 xyz，原样返回
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bytes_per_vertex = sum(bs for _, _, bs in props)
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little_endian = fmt != "binary_big_endian"
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endian = "<" if little_endian else ">"
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# 读整个数据区
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file_size = src.stat().st_size
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data_bytes = file_size - data_start
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expected = vertex_count * bytes_per_vertex
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with open(src, "rb") as fh:
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fh.seek(data_start)
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data = fh.read(expected)
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if len(data) < expected:
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return str(src) # 文件截断，原样返回
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# 用 numpy structured array 解析
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dtype_fields = []
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for pname, fc, bs in props:
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np_type = endian + fc
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dtype_fields.append((pname or f"_f{len(dtype_fields)}", np_type))
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try:
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arr = _np.frombuffer(data, dtype=_np.dtype(dtype_fields))
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xs = arr[props[0][0] if props[0][0] else "_f0"] # fallback
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# 直接按名字取
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x_name = props[[i for i, (n, _, _) in enumerate(props) if n.lower() == "x"][0]][0]
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y_name = props[[i for i, (n, _, _) in enumerate(props) if n.lower() == "y"][0]][0]
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z_name = props[[i for i, (n, _, _) in enumerate(props) if n.lower() == "z"][0]][0]
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xs = arr[x_name].astype(_np.float64)
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ys = arr[y_name].astype(_np.float64)
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zs = arr[z_name].astype(_np.float64)
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except Exception:
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return str(src)
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# 写 ASCII PLY
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cache_dir = Path(cache_dir)
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cache_dir.mkdir(parents=True, exist_ok=True)
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out_path = cache_dir / (src.stem + "_ascii.ply")
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with open(out_path, "w", encoding="ascii") as fh:
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fh.write("ply\nformat ascii 1.0\n")
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fh.write(f"element vertex {vertex_count}\n")
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fh.write("property double x\nproperty double y\nproperty double z\n")
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fh.write("end_header\n")
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for x, y, z in zip(xs, ys, zs):
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fh.write(f"{x:.10g} {y:.10g} {z:.10g}\n")
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return str(out_path)
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