108 lines
4.1 KiB
Python
108 lines
4.1 KiB
Python
import struct
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import math
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import os
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def merge_stls(input_files, output_path):
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try:
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from stl import mesh
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import numpy as np
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meshes = []
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for path, matrix in input_files:
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try:
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# 重新换回轻量级的 numpy-stl 以防内存溢出 (OOM)
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m = mesh.Mesh.from_file(path)
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mat = np.array(matrix, dtype=np.float64).reshape((4, 4)).T
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vectors = m.vectors.reshape(-1, 3)
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hom_vectors = np.hstack((vectors, np.ones((len(vectors), 1), dtype=np.float32)))
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transformed = (mat @ hom_vectors.T).T
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m.vectors = transformed[:, :3].reshape(-1, 3, 3)
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# 检测缩放矩阵是否引发镜像翻转 (行列式为负数)
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det = np.linalg.det(mat[:3, :3])
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if det < 0:
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# 发生镜像反转，不仅法线会反向，三角形三个顶点的顺逆时针（Winding Order）也会错乱
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# 强行交换每个三角形的顶点2和顶点3以纠正渲染正反面
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m.vectors[:, [1, 2]] = m.vectors[:, [2, 1]]
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m.update_normals()
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meshes.append(m)
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except Exception as e:
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print(f"Error processing path {path} with stl mesh: {e}")
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if not meshes:
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return
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if len(meshes) == 1:
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meshes[0].save(output_path)
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return
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merged_data = np.concatenate([m.data for m in meshes])
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merged_mesh = mesh.Mesh(merged_data)
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merged_mesh.save(output_path)
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return
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except Exception as e:
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print(f"Mesh fast-merge failed: {e}. Falling back to struct parsing.")
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# Extreme fallback just in case no stl libraries work
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total_faces = 0
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meshes_data = []
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for path, matrix in input_files:
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with open(path, 'rb') as f:
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f.read(80)
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faces = struct.unpack('<I', f.read(4))[0]
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data = f.read(faces * 50)
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def apply_m(_x, _y, _z):
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w = _x * matrix[3] + _y * matrix[7] + _z * matrix[11] + matrix[15]
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nx = (_x * matrix[0] + _y * matrix[4] + _z * matrix[8] + matrix[12]) / w
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ny = (_x * matrix[1] + _y * matrix[5] + _z * matrix[9] + matrix[13]) / w
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nz = (_x * matrix[2] + _y * matrix[6] + _z * matrix[10] + matrix[14]) / w
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return nx, ny, nz
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new_data = bytearray(faces * 50)
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src_offset = 0
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dst_offset = 0
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for _ in range(faces):
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n_x, n_y, n_z, v1x, v1y, v1z, v2x, v2y, v2z, v3x, v3y, v3z, attr = struct.unpack_from('<12fH', data, src_offset)
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nv1x, nv1y, nv1z = apply_m(v1x, v1y, v1z)
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nv2x, nv2y, nv2z = apply_m(v2x, v2y, v2z)
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nv3x, nv3y, nv3z = apply_m(v3x, v3y, v3z)
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# Recalculate normal properly using cross product to fix flipped/sheared surfaces
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Ux = nv2x - nv1x
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Uy = nv2y - nv1y
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Uz = nv2z - nv1z
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Vx = nv3x - nv1x
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Vy = nv3y - nv1y
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Vz = nv3z - nv1z
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nnx = Uy * Vz - Uz * Vy
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nny = Uz * Vx - Ux * Vz
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nnz = Ux * Vy - Uy * Vx
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l = math.sqrt(nnx**2 + nny**2 + nnz**2)
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if l > 1e-8:
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nnx, nny, nnz = nnx/l, nny/l, nnz/l
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else:
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nnx, nny, nnz = 0.0, 0.0, 0.0
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struct.pack_into('<12fH', new_data, dst_offset, nnx, nny, nnz, nv1x, nv1y, nv1z, nv2x, nv2y, nv2z, nv3x, nv3y, nv3z, attr)
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src_offset += 50
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dst_offset += 50
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meshes_data.append(new_data)
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total_faces += faces
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with open(output_path, 'wb') as f:
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f.write(b'\0' * 80)
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f.write(struct.pack('<I', total_faces))
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for d in meshes_data:
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f.write(d)
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