使用 this python recipe ,我在我的 Tk 窗口上创建了一个类似笔记本的小部件。一切正常,直到我尝试将图像添加到每个选项卡中。当我将图像添加到选项卡时,我最初设置的文本不再显示。我想知道我是否可以让文本(在本例中是“tab one”)显示在图像的正下方。以下是我当前的代码:
from Tkinter import *
class Notebook(Frame):
def __init__(self, parent, activerelief = SOLID, inactiverelief = SOLID, xpad = 4, ypad = 4, activefg = 'black',activebg='green',inactivebg='grey',bd=1,inactivefg = 'black', **kw):
self.activefg = activefg
self.activebg=activebg
self.bd=bd
self.inactivebg=inactivebg
self.inactivefg = inactivefg
self.deletedTabs = []
self.xpad = xpad
self.ypad = ypad
self.activerelief = activerelief
self.inactiverelief = inactiverelief
self.kwargs = kw
self.tabVars = {}
self.tabs = 0
self.noteBookFrame = Frame(parent)
self.BFrame = Frame(self.noteBookFrame)
self.noteBook = Frame(self.noteBookFrame, relief = RAISED, bd = 1, **kw)
self.noteBook.grid_propagate(0)
Frame.__init__(self)
self.noteBookFrame.grid()
self.BFrame.grid(row =0, sticky = W)
self.noteBook.grid(row = 1, column = 0, columnspan = 27)
def add_tab(self, width = 1, **kw):
temp = self.tabs
self.tabVars[self.tabs] = [Label(self.BFrame, relief = RIDGE, **kw)]
self.tabVars[self.tabs][0].bind("<Button-1>", lambda Event:self.change_tab(temp))
self.tabVars[self.tabs][0].pack(side = LEFT, ipady = self.ypad, ipadx = self.xpad)
self.tabVars[self.tabs].append(Frame(self.noteBook, **self.kwargs))
self.tabVars[self.tabs][1].grid(row = 0, column = 0)
self.change_tab(0)
self.tabs += 1
return self.tabVars[temp][1]
def change_tab(self, IDNum):
for i in (a for a in range(0, len(self.tabVars.keys()))):
if not i in self.deletedTabs:
if i <> IDNum:
self.tabVars[i][1].grid_remove()
self.tabVars[i][0]['relief'] = self.inactiverelief
self.tabVars[i][0]['fg'] = self.inactivefg
self.tabVars[i][0]['bg'] = self.inactivebg
self.tabVars[i][0]['bd'] = self.bd
else:
self.tabVars[i][1].grid()
self.tabVars[IDNum][0]['relief'] = self.activerelief
self.tabVars[i][0]['fg'] = self.activefg
self.tabVars[i][0]['bg'] = self.activebg
self.tabVars[i][0]['bd'] = self.bd
root=Tk()
scheduledimage=PhotoImage(data="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")
note=Notebook(root, width= 400, height =400, activefg = 'red', inactivefg = 'blue')
note.grid()
tab1 = note.add_tab(text = "Tab One",image=scheduledimage)
tab2 = note.add_tab(text = "Tab Two")
tab3 = note.add_tab(text = "Tab Three")
root.mainloop()
最佳答案
标签引用:compound
Controls how to combine text and image in the label. By default, if an image or bitmap is given, it is drawn instead of the text. If this option is set to CENTER, the text is drawn on top of the image. If this option is set to one of BOTTOM, LEFT, RIGHT, or TOP, the image is drawn besides the text (use BOTTOM to draw the image under the text, etc.). Default is NONE.
tab1 = note.add_tab(text = "Tab One",image=scheduledimage, compound=TOP)
ttk.Notebook示例:
from Tkinter import *
from ttk import *
root = Tk()
scheduledimage=PhotoImage(...)
note = Notebook(root)
tab1 = Frame(note)
tab2 = Frame(note)
tab3 = Frame(note)
Button(tab1, text='Exit', command=root.destroy).pack(padx=100, pady=100)
note.add(tab1, text = "Tab One",image=scheduledimage, compound=TOP)
note.add(tab2, text = "Tab Two")
note.add(tab3, text = "Tab Three")
note.pack()
root.mainloop()
exit()
关于Python Tkinter 笔记本小部件,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/16514617/
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TCP是面向连接的协议,连接的建立和释放是每一次面向连接的通信中必不可少的过程。TCP连接的管理就是使连接的建立和释放都能正常地进行。三次握手TCP连接的建立—三次握手建立TCP连接①若主机A中运行了一个客户进程,当它需要主机B的服务时,就发起TCP连接请求,并在所发送的分段中用SYN=1表示连接请求,并产生一个随机发送序号x,如果连接成功,A将以x作为其发送序号的初始值:seq=x。主机B收到A的连接请求报文,就完成了第一次握手。客户端发送SYN=1表示连接请求客户端发送一个随机发送序号x,如果连接成功,A将以x作为其发送序号的初始值:seq=x②主机B如果同意建立连接,则向主机A发送确认报
VXLAN简介定义RFC定义了VLAN扩展方案VXLAN(VirtualeXtensibleLocalAreaNetwork,虚拟扩展局域网)。VXLAN采用MACinUDP(UserDatagramProtocol)封装方式,是NVO3(NetworkVirtualizationoverLayer3)中的一种网络虚拟化技术。目的随着网络技术的发展,云计算凭借其在系统利用率高、人力/管理成本低、灵活性/可扩展性强等方面表现出的优势,已经成为目前企业IT建设的新趋势。而服务器虚拟化作为云计算的核心技术之一,得到了越来越多的应用。服务器虚拟化技术的广泛部署,极大地增加了数据中心的计算密度;同时,为
目录一、原理部分1、什么是串行通信(1)并行通信与串行通信(2)串行通信的制式(3)串行通信的主要方式 2、配置串口(1)SCON和PCON:串行口1的控制寄存器(2)SBUF:串行口数据缓冲寄存器 (3)AUXR:辅助寄存器编辑(4)ES、PS:与串行口1中断相关的寄存器(5)波特率设置 3、串口框架编写二、程序案例一、原理部分1、什么是串行通信(1)并行通信与串行通信微控制器与外部设备的数据通信,根据连线结构和传送方式的不同,可以分为两种:并行通信和串行通信。并行通信:数据的各位同时发送与接收,每个数据位使用一条导线,这种方式传输快,但是需要多条导线进行信号传输。串行通信:数据一位一
这篇文章,主要介绍如何使用SpringCloud微服务组件从0到1搭建一个微服务工程。目录一、从0到1搭建微服务工程1.1、基础环境说明(1)使用组件(2)微服务依赖1.2、搭建注册中心(1)引入依赖(2)配置文件(3)启动类1.3、搭建配置中心(1)引入依赖(2)配置文件(3)启动类1.4、搭建API网关(1)引入依赖(2)配置文件(3)启动类1.5、搭建服务提供者(1)引入依赖(2)配置文件(3)启动类1.6、搭建服务消费者(1)引入依赖(2)配置文件(3)启动类1.7、运行测试一、从0到1搭建微服务工程1.1、基础环境说明(1)使用组件这里主要是使用的SpringCloudNetflix
目录文章信息写在前面Background&MotivationMethodDCNV2DCNV3模型架构Experiment分类检测文章信息Title:InternImage:ExploringLarge-ScaleVisionFoundationModelswithDeformableConvolutionsPaperLink:https://arxiv.org/abs/2211.05778CodeLink:https://github.com/OpenGVLab/InternImage写在前面拿到文章之后先看了一眼在ImageNet1k上的结果,确实很高,超越了同等大小下的VAN、RepLK
文章目录前言一、注册小程序二、项目创建三、运行项目四、其他配置最后前言此次项目开发使用uniapp和uview进行开发,需要用到的开发工具为HBuilderX和微信开发者工具,具体的安装方式见官网,小程序注册见微信公众平台。一、注册小程序注册在微信公众平台注册小程序,按照提示注册完后会发配一个appid和密钥,需要复制保存好。完善信息设置=>基本设置,填写小程序基本信息,包括名称、头像、介绍及服务范围等。第三方设置根据开发需求添加插件授权。成员管理管理=>成员管理,点击编辑或下拉选择添加成员,输入微信号添加新的项目成员,只有成员可以进行真机测试。体验成员可以使用发布的体验版。开发设置开发=>开
ESP32学习笔记(七)复位和时钟目录:ESP32学习笔记(一)芯片型号介绍ESP32学习笔记(二)开发环境搭建VSCode+platformioESP32学习笔记(三)硬件资源介绍ESP32学习笔记(四)串口通信ESP32学习笔记(五)外部中断ESP32学习笔记(六)定时器ESP32学习笔记(七)复位和时钟1.复位2.系统时钟2.1时钟树2.2时钟源从时钟树可以看出时钟源共七种ESP32的时钟源分别来自外部晶振、内部PLL或振荡电路具体地说,这些时钟源为:2.2.1快速时钟PLL_CLK320MHz或480MHz内部PLL时钟XTL_CLK2~40MHz外部晶振时钟,模组板载的是40MHz晶