self.tk.call(_flatten((self._w, cmd)) + self._options(cnf)) _tkinter.TclError: unknown option "-relief"

这个错误提示表明，在调用 `button.config(relief="sunken")` 和 `button.config(relief="raised")` 时发生了错误。可能是因为你的 tkinter 版本不支持这个选项。

你可以尝试将这两行代码改为：

button.config(borderwidth=2)
button.config(relief="groove")

这样应该可以达到相同的效果。如果你想要更改按钮的边框宽度和样式，请调整 `borderwidth` 和 `relief` 的值。

相关问题

Exception in Tkinter callback Traceback (most recent call last): File "C:\Users\DELL\Anaconda3\lib\tkinter\__init__.py", line 1702, in __call__ return self.func(*args) File "<ipython-input-334-75eabe3071f9>", line 43, in run_classifier result_label.config(text="训练集分类器的准确率为：{:.2f}".format(score)) File "C:\Users\DELL\Anaconda3\lib\tkinter\__init__.py", line 1482, in configure return self._configure('configure', cnf, kw) File "C:\Users\DELL\Anaconda3\lib\tkinter\__init__.py", line 1473, in _configure self.tk.call(_flatten((self._w, cmd)) + self._options(cnf)) _tkinter.TclError: invalid command name ".!label4" Exception in Tkinter callback Traceback (most recent call last): File "C:\Users\DELL\Anaconda3\lib\tkinter\__init__.py", line 1702, in __call__ return self.func(*args) File "<ipython-input-334-75eabe3071f9>", line 48, in run2 result_label2.config(text="测试集分类器的准确率为：{:.2f}".format(score2)) File "C:\Users\DELL\Anaconda3\lib\tkinter\__init__.py", line 1482, in configure return self._configure('configure', cnf, kw) File "C:\Users\DELL\Anaconda3\lib\tkinter\__init__.py", line 1473, in _configure self.tk.call(_flatten((self._w, cmd)) + self._options(cnf)) _tkinter.TclError: invalid command name ".!label5"

这个错误是因为程序中某个标签（Label）的名字不正确导致的。具体来说，错误信息中的".!label4"和".!label5"分别对应两个标签的名字。请检查你的程序，看看这两个标签的名字是否正确，并且确保程序中没有重复的标签名字。如果需要，你可以在标签名字后添加一个数字或其他字符来避免重名。另外，也可以尝试重新启动程序来解决这个问题。

current_dir = os.path.dirname(os.path.realpath(__file__)) data_dir = os.path.join(current_dir, 'data') class Model(nn.Module): def __init__(self, template_path): super(Model, self).__init__() # set template mesh self.template_mesh = jr.Mesh.from_obj(template_path, dr_type='n3mr') self.vertices = (self.template_mesh.vertices * 0.5).stop_grad() self.faces = self.template_mesh.faces.stop_grad() self.textures = self.template_mesh.textures.stop_grad() # optimize for displacement map and center self.displace = jt.zeros(self.template_mesh.vertices.shape) self.center = jt.zeros((1, 1, 3)) # define Laplacian and flatten geometry constraints self.laplacian_loss = LaplacianLoss(self.vertices[0], self.faces[0]) self.flatten_loss = FlattenLoss(self.faces[0]) def execute(self, batch_size): base = jt.log(self.vertices.abs() / (1 - self.vertices.abs())) centroid = jt.tanh(self.center) vertices = (base + self.displace).sigmoid() * nn.sign(self.vertices) vertices = nn.relu(vertices) * (1 - centroid) - nn.relu(-vertices) * (centroid + 1) vertices = vertices + centroid # apply Laplacian and flatten geometry constraints laplacian_loss = self.laplacian_loss(vertices).mean() flatten_loss = self.flatten_loss(vertices).mean() return jr.Mesh(vertices.repeat(batch_size, 1, 1), self.faces.repeat(batch_size, 1, 1), dr_type='n3mr'), laplacian_loss, flatten_loss 在每行代码后添加注释

# 导入必要的包
import os
import jittor as jt
from jittor import nn
import jrender as jr

# 定义数据文件夹路径
current_dir = os.path.dirname(os.path.realpath(__file__))
data_dir = os.path.join(current_dir, 'data')

# 定义模型类
class Model(nn.Module):

def __init__(self, template_path):
super(Model, self).__init__()

# 设置模板网格
self.template_mesh = jr.Mesh.from_obj(template_path, dr_type='n3mr')
self.vertices = (self.template_mesh.vertices * 0.5).stop_grad() # 顶点坐标
self.faces = self.template_mesh.faces.stop_grad() # 面
self.textures = self.template_mesh.textures.stop_grad() # 纹理

# 优化位移贴图和中心点
self.displace = jt.zeros(self.template_mesh.vertices.shape) # 位移贴图
self.center = jt.zeros((1, 1, 3)) # 中心点坐标

# 定义拉普拉斯约束和平坦几何约束
self.laplacian_loss = LaplacianLoss(self.vertices[0], self.faces[0])
self.flatten_loss = FlattenLoss(self.faces[0])

def execute(self, batch_size):
base = jt.log(self.vertices.abs() / (1 - self.vertices.abs())) # 基础值
centroid = jt.tanh(self.center) # 中心点
vertices = (base + self.displace).sigmoid() * nn.sign(self.vertices) # 顶点坐标
vertices = nn.relu(vertices) * (1 - centroid) - nn.relu(-vertices) * (centroid + 1) # 顶点坐标变换
vertices = vertices + centroid # 顶点坐标变换

# 应用拉普拉斯约束和平坦几何约束
laplacian_loss = self.laplacian_loss(vertices).mean() # 拉普拉斯约束损失
flatten_loss = self.flatten_loss(vertices).mean() # 平坦几何约束损失

return jr.Mesh(vertices.repeat(batch_size, 1, 1), # 重复顶点坐标
self.faces.repeat(batch_size, 1, 1), # 重复面
dr_type='n3mr'), laplacian_loss, flatten_loss