首次提交: OnebotCatalog 项目代码与文档（含 NX 按需生成服务二期、后台、一键启动）

onebot-data/tools/simplify-stl.py

@@ -0,0 +1,93 @@
+# -*- coding: utf-8 -*-
+"""
+simplify-stl.py —— 简化过大的 STL 网格 (窗口内 3D 预览用, 纯 numpy 顶点聚类, 零额外依赖)
+
+用途: 屏幕预览不需要几十 MB 的精细网格; 本脚本把 mesh\\ 里 > 阈值的 STL
+     按网格边长 (GRID_MM) 做顶点聚类, 体积缩小 3~10 倍, 外形基本不变。
+
+用法: python simplify-stl.py   (处理 mesh\\ 下所有 > 5MB 的 .stl, 就地覆盖)
+"""
+import os
+import re
+import struct
+
+import numpy as np
+
+BASE = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
+MESH_DIR = os.path.join(BASE, 'catalog', 'mesh')
+SIZE_MIN = 2 * 1024 * 1024    # 只处理 2MB 以上的网格 (控制窗口内渲染内存)
+GRID_MM = 0.75                # 聚类网格边长 (mm): 越大越简 (0.5~1.0 预览合适)
+
+
+def read_stl(path):
+    """自动识别二进制/ASCII STL, 返回 (N,3,3) 三角顶点数组"""
+    with open(path, 'rb') as f:
+        head = f.read(5)
+    if head[:5] == b'solid':
+        # ASCII STL: 正则抽出所有 vertex 行
+        with open(path, 'r', errors='ignore') as f:
+            txt = f.read()
+        arr = np.array(re.findall(r'vertex\s+([-\deE+.]+)\s+([-\deE+.]+)\s+([-\deE+.]+)', txt),
+                       dtype=np.float32)
+        return arr.reshape(-1, 3, 3)
+    with open(path, 'rb') as f:
+        f.read(80)
+        (n,) = struct.unpack('<I', f.read(4))
+        raw = np.frombuffer(f.read(n * 50), dtype=np.uint8).reshape(n, 50)
+        # 每条记录 50 字节: 12 个 float (48B) + 2B 属性; 截取前 48B 再按 float 视图
+        f32 = np.ascontiguousarray(raw[:, :48]).view('<f4').reshape(n, 12)
+        return f32[:, 3:].reshape(n, 3, 3)
+
+
+def write_binary_stl(path, tris):
+    n = len(tris)
+    with open(path, 'wb') as f:
+        f.write(b'ONEBOT simplified mesh'.ljust(80, b'\0'))
+        f.write(struct.pack('<I', n))
+        for tri in tris:
+            p0, p1, p2 = tri[0], tri[1], tri[2]
+            nrm = np.cross(p1 - p0, p2 - p0)
+            norm = np.linalg.norm(nrm)
+            nrm = nrm / norm if norm > 1e-12 else np.array([0.0, 0.0, 1.0])
+            f.write(struct.pack('<12f', nrm[0], nrm[1], nrm[2],
+                                p0[0], p0[1], p0[2], p1[0], p1[1], p1[2], p2[0], p2[1], p2[2]))
+            f.write(struct.pack('<H', 0))
+
+
+def simplify(path):
+    tris = read_stl(path)
+    n_in = len(tris)
+    verts = tris.reshape(-1, 3)
+    # 顶点聚类: 落到同一网格单元的顶点合并为均值点
+    cell = np.floor(verts / GRID_MM).astype(np.int64)
+    _, inv, counts = np.unique(cell, axis=0, return_inverse=True, return_counts=True)
+    sums = np.zeros((counts.shape[0], 3))
+    np.add.at(sums, inv, verts)
+    new_verts = sums / counts[:, None]
+    # 重映射三角形, 丢弃退化 (两顶点落入同一单元)
+    idx = inv.reshape(-1, 3)
+    keep = (idx[:, 0] != idx[:, 1]) & (idx[:, 1] != idx[:, 2]) & (idx[:, 0] != idx[:, 2])
+    out = new_verts[idx[keep]]
+    write_binary_stl(path, out)
+    return n_in, len(out)
+
+
+def main():
+    if not os.path.isdir(MESH_DIR):
+        print('mesh 目录不存在')
+        return
+    for name in sorted(os.listdir(MESH_DIR)):
+        if not name.lower().endswith('.stl'):
+            continue
+        p = os.path.join(MESH_DIR, name)
+        size_in = os.path.getsize(p)
+        if size_in < SIZE_MIN:
+            continue
+        n_in, n_out = simplify(p)
+        print('%s: %d → %d 三角面 (%.1fMB → %.1fMB)' % (
+            name, n_in, n_out, size_in / 1048576.0, os.path.getsize(p) / 1048576.0))
+    print('完成')
+
+
+if __name__ == '__main__':
+    main()