599 lines
20 KiB
Python
599 lines
20 KiB
Python
#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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#===================================== 1. Module Imports =====================================
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import maya.cmds as cmds
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import maya.mel as mel
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import sys
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import os
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#===================================== 2. Model Utils =====================================
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def load_model(lod_index, model_type, file_path):
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"""加载模型
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Args:
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lod_index: LOD级别(0-7)
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model_type: 模型类型(head/teeth/gums/eye_l/eye_r/iris/eyelash/eyelid/cartilage/body)
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file_path: 模型文件路径
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"""
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try:
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# 检查文件是否存在
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if not os.path.exists(file_path):
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raise FileNotFoundError(f"模型文件不存在: {file_path}")
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# 导入模型
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imported_nodes = cmds.file(
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file_path,
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i=True,
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returnNewNodes=True,
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namespace=f"LOD{lod_index}_{model_type}"
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)
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# 设置模型属性
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for node in imported_nodes:
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if cmds.objectType(node) == "transform":
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# 添加自定义属性
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cmds.addAttr(node, ln="LOD_INDEX", at="long", dv=lod_index)
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cmds.addAttr(node, ln="MODEL_TYPE", dt="string")
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cmds.setAttr(f"{node}.MODEL_TYPE", model_type, type="string")
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print(f"成功加载LOD{lod_index}_{model_type}模型")
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return imported_nodes
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except Exception as e:
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cmds.warning(f"加载模型失败: {str(e)}")
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return None
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def delete_lod(lod_index):
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"""删除指定LOD级别的所有模型"""
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try:
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# 查找指定LOD的所有模型
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lod_nodes = cmds.ls(f"LOD{lod_index}_*", long=True)
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if lod_nodes:
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cmds.delete(lod_nodes)
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print(f"成功删除LOD{lod_index}的所有模型")
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else:
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print(f"未找到LOD{lod_index}的模型")
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except Exception as e:
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cmds.warning(f"删除LOD{lod_index}失败: {str(e)}")
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# 模型工具功能
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def split_model():
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"""分离选中的模型"""
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try:
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selection = cmds.ls(sl=True, type="transform")
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if not selection:
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raise ValueError("请先选择要分离的模型")
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for obj in selection:
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# 获取模型的面数
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mesh = cmds.listRelatives(obj, shapes=True, type="mesh")
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if not mesh:
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continue
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# 分离每个面为独立的模型
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cmds.polySeparate(obj, ch=False)
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print("模型分离完成")
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except Exception as e:
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cmds.warning(f"模型分离失败: {str(e)}")
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def generate_facial_accessories():
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"""生成面部配件"""
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print("生成面部配件功能待实现")
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def repair_normals():
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"""修复法线"""
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try:
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selection = cmds.ls(sl=True, type="transform")
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if not selection:
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raise ValueError("请先选择要修复法线的模型")
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for obj in selection:
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mesh = cmds.listRelatives(obj, shapes=True, type="mesh")
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if not mesh:
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continue
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# 统一法线方向
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cmds.polyNormal(obj, normalMode=2, userNormalMode=0)
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# 解锁法线
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cmds.polyNormalPerVertex(obj, ufn=True)
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print("法线修复完成")
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except Exception as e:
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cmds.warning(f"修复法线失败: {str(e)}")
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def repair_vertex_order():
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"""修复点序"""
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try:
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selection = cmds.ls(sl=True, type="transform")
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if not selection:
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raise ValueError("请先选择要修复点序的模型")
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for obj in selection:
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# 重新排序顶点
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cmds.polyReorder(obj)
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print("点序修复完成")
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except Exception as e:
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cmds.warning(f"修复点序失败: {str(e)}")
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def repair_seams():
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"""修复接缝"""
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try:
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selection = cmds.ls(sl=True, type="transform")
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if not selection:
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raise ValueError("请先选择要修复接缝的模型")
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for obj in selection:
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# 合并重叠顶点
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cmds.polyMergeVertex(obj, d=0.001)
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# 删除重复面
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cmds.polyRemoveFace(obj, removeDuplicateFaces=True)
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print("接缝修复完成")
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except Exception as e:
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cmds.warning(f"修复接缝失败: {str(e)}")
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# LOD功能
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def load_custom_models():
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"""自定义加载模型"""
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print("自定义加载模型功能待实现")
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def standardize_naming():
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"""标准化命名"""
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try:
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selection = cmds.ls(sl=True, type="transform")
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if not selection:
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raise ValueError("请先选择要标准化命名的模型")
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for obj in selection:
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# 获取LOD信息
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if cmds.attributeQuery("LOD_INDEX", node=obj, exists=True):
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lod_index = cmds.getAttr(f"{obj}.LOD_INDEX")
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model_type = cmds.getAttr(f"{obj}.MODEL_TYPE")
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# 重命名为标准格式
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new_name = f"LOD{lod_index}_{model_type}"
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cmds.rename(obj, new_name)
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print("命名标准化完成")
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except Exception as e:
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cmds.warning(f"标准化命名失败: {str(e)}")
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def auto_group():
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"""自动分组"""
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try:
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# 创建LOD组
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for i in range(8):
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group_name = f"LOD{i}_GROUP"
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if not cmds.objExists(group_name):
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cmds.group(empty=True, name=group_name)
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# 将模型移动到对应组
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all_models = cmds.ls("LOD*_*", type="transform")
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for model in all_models:
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if cmds.attributeQuery("LOD_INDEX", node=model, exists=True):
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lod_index = cmds.getAttr(f"{model}.LOD_INDEX")
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group_name = f"LOD{lod_index}_GROUP"
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cmds.parent(model, group_name)
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print("自动分组完成")
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except Exception as e:
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cmds.warning(f"自动分组失败: {str(e)}")
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# MetaHuman模型特定功能
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def validate_metahuman_topology():
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"""验证模型是否符合MetaHuman拓扑要求"""
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try:
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selection = cmds.ls(sl=True, type="transform")
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if not selection:
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raise ValueError("请先选择要验证的模型")
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results = []
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for obj in selection:
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mesh = cmds.listRelatives(obj, shapes=True, type="mesh")
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if not mesh:
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continue
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# 获取模型信息
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vertex_count = cmds.polyEvaluate(obj, vertex=True)
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face_count = cmds.polyEvaluate(obj, face=True)
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# 检查是否符合MetaHuman标准
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is_valid = True
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messages = []
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# 获取LOD级别
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lod_index = -1
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if cmds.attributeQuery("LOD_INDEX", node=obj, exists=True):
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lod_index = cmds.getAttr(f"{obj}.LOD_INDEX")
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# 根据LOD级别验证顶点数和面数
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if lod_index == 0:
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if vertex_count != 7127:
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messages.append(f"顶点数不符合LOD0标准(当前:{vertex_count}, 应为:7127)")
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is_valid = False
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elif lod_index == 1:
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if vertex_count != 5127:
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messages.append(f"顶点数不符合LOD1标准(当前:{vertex_count}, 应为:5127)")
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is_valid = False
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# ... 其他LOD级别的验证
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results.append({
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"object": obj,
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"is_valid": is_valid,
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"messages": messages
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})
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# 显示验证结果
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for result in results:
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status = "✓" if result["is_valid"] else "✗"
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print(f"{status} {result['object']}:")
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if not result["is_valid"]:
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for msg in result["messages"]:
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print(f" - {msg}")
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return results
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except Exception as e:
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cmds.warning(f"拓扑验证失败: {str(e)}")
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return None
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def transfer_uvs():
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"""传递UV到其他LOD级别"""
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try:
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# 获取源模型和目标模型
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selection = cmds.ls(sl=True, type="transform")
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if len(selection) != 2:
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raise ValueError("请选择一个源模型和一个目标模型")
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source = selection[0]
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target = selection[1]
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# 执行UV传递
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cmds.transferAttributes(
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source,
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target,
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transferUVs=2,
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transferColors=0,
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sampleSpace=4 # World space
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)
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# 删除构建历史
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cmds.delete(target, ch=True)
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print(f"UV传递完成: {source} -> {target}")
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except Exception as e:
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cmds.warning(f"UV传递失败: {str(e)}")
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def generate_lod_chain():
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"""生成完整的LOD链"""
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try:
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# 获取选中的LOD0模型
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selection = cmds.ls(sl=True, type="transform")
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if not selection:
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raise ValueError("请先选择LOD0模型")
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source = selection[0]
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if not cmds.attributeQuery("LOD_INDEX", node=source, exists=True):
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raise ValueError("请选择带有LOD属性的模型")
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lod_index = cmds.getAttr(f"{source}.LOD_INDEX")
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if lod_index != 0:
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raise ValueError("请选择LOD0模型")
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# 为每个LOD级别生成简化模型
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for i in range(1, 8):
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target_name = source.replace("LOD0", f"LOD{i}")
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# 复制模型
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duplicate = cmds.duplicate(source, name=target_name)[0]
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# 设置LOD属性
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cmds.setAttr(f"{duplicate}.LOD_INDEX", i)
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# 简化模型
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reduction_ratio = 1.0 - (i * 0.1) # 每级减少10%
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cmds.polyReduce(
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duplicate,
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percentage=reduction_ratio * 100,
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triangulate=False,
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preserveTopology=True,
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keepQuadsWeight=1.0,
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keepBorder=True
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)
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print(f"生成LOD{i}完成: {target_name}")
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print("LOD链生成完成")
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except Exception as e:
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cmds.warning(f"LOD链生成失败: {str(e)}")
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def check_model_symmetry():
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"""检查模型对称性"""
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try:
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selection = cmds.ls(sl=True, type="transform")
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if not selection:
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raise ValueError("请先选择要检查的模型")
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for obj in selection:
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# 获取顶点位置
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vertices = cmds.ls(f"{obj}.vtx[*]", flatten=True)
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vertex_positions = {}
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for vtx in vertices:
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pos = cmds.pointPosition(vtx, world=True)
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# 使用x坐标的绝对值作为键，保存顶点信息
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x_abs = abs(pos[0])
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if x_abs not in vertex_positions:
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vertex_positions[x_abs] = []
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vertex_positions[x_abs].append((vtx, pos))
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# 检查对称性
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asymmetric_vertices = []
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for x_abs, points in vertex_positions.items():
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if len(points) == 2:
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vtx1, pos1 = points[0]
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vtx2, pos2 = points[1]
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# 检查y和z坐标是否对称
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if abs(pos1[1] - pos2[1]) > 0.001 or abs(pos1[2] - pos2[2]) > 0.001:
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asymmetric_vertices.extend([vtx1, vtx2])
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elif len(points) == 1 and x_abs > 0.001: # 忽略中心线上的点
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asymmetric_vertices.append(points[0][0])
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# 显示结果
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if asymmetric_vertices:
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cmds.select(asymmetric_vertices)
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print(f"发现{len(asymmetric_vertices)}个不对称顶点")
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else:
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print(f"{obj}模型对称性检查通过")
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except Exception as e:
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cmds.warning(f"对称性检查失败: {str(e)}")
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def mirror_geometry():
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"""镜像几何体"""
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try:
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selection = cmds.ls(sl=True, type="transform")
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if not selection:
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raise ValueError("请先选择要镜像的模型")
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for obj in selection:
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# 创建镜像几何体
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mirrored = cmds.duplicate(obj, name=f"{obj}_mirrored")[0]
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# 执行镜像
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cmds.scale(-1, 1, 1, mirrored)
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# 反转法线
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cmds.polyNormal(mirrored, normalMode=0)
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print(f"模型镜像完成: {mirrored}")
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except Exception as e:
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cmds.warning(f"模型镜像失败: {str(e)}")
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# 骨骼权重相关功能
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def transfer_skin_weights():
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"""传递蒙皮权重"""
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try:
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selection = cmds.ls(sl=True, type="transform")
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if len(selection) < 2:
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raise ValueError("请选择源模型和目标模型")
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source = selection[0]
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targets = selection[1:]
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# 获取源模型的蒙皮变形器
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skin_cluster = mel.eval(f'findRelatedSkinCluster("{source}")')
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if not skin_cluster:
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raise ValueError(f"源模型{source}没有蒙皮变形器")
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# 获取骨骼列表
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joints = cmds.skinCluster(skin_cluster, q=True, inf=True)
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# 为每个目标模型创建蒙皮并传递权重
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for target in targets:
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# 创建新的蒙皮变形器
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new_skin = cmds.skinCluster(
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joints,
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target,
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toSelectedBones=True,
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bindMethod=0,
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skinMethod=0,
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normalizeWeights=1
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)[0]
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# 复制权重
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cmds.copySkinWeights(
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ss=skin_cluster,
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ds=new_skin,
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noMirror=True,
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surfaceAssociation="closestPoint",
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influenceAssociation="oneToOne"
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)
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print(f"权重传递完成: {source} -> {target}")
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except Exception as e:
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cmds.warning(f"权重传递失败: {str(e)}")
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def mirror_skin_weights():
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"""镜像蒙皮权重"""
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try:
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selection = cmds.ls(sl=True, type="transform")
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if not selection:
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raise ValueError("请选择要镜像权重的模型")
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for obj in selection:
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# 获取蒙皮变形器
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skin_cluster = mel.eval(f'findRelatedSkinCluster("{obj}")')
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if not skin_cluster:
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continue
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# 执行镜像
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cmds.copySkinWeights(
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ss=skin_cluster,
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ds=skin_cluster,
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mirrorMode="YZ",
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surfaceAssociation="closestPoint",
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influenceAssociation="closestJoint"
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)
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print(f"权重镜像完成: {obj}")
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except Exception as e:
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cmds.warning(f"权重镜像失败: {str(e)}")
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def clean_skin_weights():
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"""清理蒙皮权重"""
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try:
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selection = cmds.ls(sl=True, type="transform")
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if not selection:
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raise ValueError("请选择要清理权重的模型")
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for obj in selection:
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# 获取蒙皮变形器
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skin_cluster = mel.eval(f'findRelatedSkinCluster("{obj}")')
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if not skin_cluster:
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continue
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# 移除小权重
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cmds.skinPercent(
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skin_cluster,
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obj,
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pruneWeights=0.01 # 移除小于1%的权重
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)
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# 规范化权重
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cmds.skinPercent(
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skin_cluster,
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obj,
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normalize=True
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)
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print(f"权重清理完成: {obj}")
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except Exception as e:
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cmds.warning(f"权重清理失败: {str(e)}")
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# 变形器处理功能
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def transfer_blendshapes():
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"""传递变形器"""
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try:
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selection = cmds.ls(sl=True, type="transform")
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if len(selection) < 2:
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raise ValueError("请选择源模型和目标模型")
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source = selection[0]
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targets = selection[1:]
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# 获取源模型的变形器
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blendshapes = cmds.listConnections(source, type="blendShape")
|
||
if not blendshapes:
|
||
raise ValueError(f"源模型{source}没有变形器")
|
||
|
||
for bs in blendshapes:
|
||
# 获取所有目标形状
|
||
targets_count = cmds.blendShape(bs, q=True, target=True)
|
||
target_weights = []
|
||
target_names = []
|
||
|
||
# 保存当前权重
|
||
for i in range(targets_count):
|
||
weight = cmds.getAttr(f"{bs}.weight[{i}]")
|
||
name = cmds.aliasAttr(f"{bs}.weight[{i}]", q=True)
|
||
target_weights.append(weight)
|
||
target_names.append(name)
|
||
|
||
# 为每个目标模型创建变形器
|
||
for target in targets:
|
||
new_bs = cmds.blendShape(
|
||
target,
|
||
frontOfChain=True,
|
||
name=f"{target}_blendShape"
|
||
)[0]
|
||
|
||
# 设置权重
|
||
for i, (weight, name) in enumerate(zip(target_weights, target_names)):
|
||
cmds.setAttr(f"{new_bs}.{name}", weight)
|
||
|
||
print(f"变形器传递完成: {source} -> {targets}")
|
||
|
||
except Exception as e:
|
||
cmds.warning(f"变形器传递失败: {str(e)}")
|
||
|
||
def optimize_blendshapes():
|
||
"""优化变形器"""
|
||
try:
|
||
selection = cmds.ls(sl=True, type="transform")
|
||
if not selection:
|
||
raise ValueError("请选择要优化变形器的模型")
|
||
|
||
for obj in selection:
|
||
# 获取变形器
|
||
blendshapes = cmds.listConnections(obj, type="blendShape")
|
||
if not blendshapes:
|
||
continue
|
||
|
||
for bs in blendshapes:
|
||
# 获取所有目标形状
|
||
target_count = cmds.blendShape(bs, q=True, target=True)
|
||
|
||
# 删除未使用的目标形状
|
||
for i in range(target_count):
|
||
weight = cmds.getAttr(f"{bs}.weight[{i}]")
|
||
if abs(weight) < 0.001: # 权重接近0的目标形状
|
||
cmds.removeMultiInstance(f"{bs}.weight[{i}]", b=True)
|
||
|
||
# 重新排序索引
|
||
cmds.blendShape(bs, edit=True, resetTargetDelta=True)
|
||
|
||
print(f"变形器优化完成: {obj}")
|
||
|
||
except Exception as e:
|
||
cmds.warning(f"变形器优化失败: {str(e)}")
|
||
|
||
def create_corrective_blendshape():
|
||
"""创建修正变形器"""
|
||
try:
|
||
selection = cmds.ls(sl=True, type="transform")
|
||
if len(selection) != 2:
|
||
raise ValueError("请选择基础模型和目标形状")
|
||
|
||
base = selection[0]
|
||
target = selection[1]
|
||
|
||
# 创建修正变形器
|
||
corrective_bs = cmds.blendShape(
|
||
target,
|
||
base,
|
||
frontOfChain=True,
|
||
name=f"{base}_corrective"
|
||
)[0]
|
||
|
||
# 设置权重驱动
|
||
cmds.setDrivenKeyframe(
|
||
f"{corrective_bs}.{target}",
|
||
currentDriver="time",
|
||
driverValue=0,
|
||
value=0
|
||
)
|
||
cmds.setDrivenKeyframe(
|
||
f"{corrective_bs}.{target}",
|
||
currentDriver="time",
|
||
driverValue=1,
|
||
value=1
|
||
)
|
||
|
||
print(f"修正变形器创建完成: {corrective_bs}")
|
||
|
||
except Exception as e:
|
||
cmds.warning(f"创建修正变形器失败: {str(e)}") |