ubuntu22.04@laptop OpenCV Get Started: 012_mouse_and_trackbar

ubuntu22.04@laptop OpenCV Get Started: 012_mouse_and_trackbar

  • [1. 源由](#1. 源由)
  • [2. mouse/trackbar应用Demo](#2. mouse/trackbar应用Demo)
    • [2.1 C++应用Demo](#2.1 C++应用Demo)
    • [2.2 Python应用Demo](#2.2 Python应用Demo)
  • [3. 鼠标位置跟踪注释](#3. 鼠标位置跟踪注释)
    • [3.1 注册回调函数](#3.1 注册回调函数)
    • [3.2 回调操作](#3.2 回调操作)
    • [3.3 效果](#3.3 效果)
  • [4. 使用轨迹栏调整图像大小](#4. 使用轨迹栏调整图像大小)
    • [4.1 初始化轨迹栏&注册回调函数](#4.1 初始化轨迹栏&注册回调函数)
    • [4.2 回调操作](#4.2 回调操作)
    • [4.3 效果](#4.3 效果)
  • [4. 总结](#4. 总结)
  • [5. 参考资料](#5. 参考资料)
  • [6. 补充](#6. 补充)

1. 源由

鼠标指针和轨迹条是图形用户界面(GUI)中的关键组件。

如果没有这些关键交互组件,就无法真正考虑与GUI交互。

因此,结合演示代码了解OpenCV中鼠标和轨迹条的内置功能,对于程序交互来说至关重要。

2. mouse/trackbar应用Demo

012_mouse_and_trackbar是OpenCV通过鼠标指针和轨迹条与用户交互的示例。

2.1 C++应用Demo

C++应用Demo工程结构:

复制代码
012_mouse_and_trackbar/CPP$ tree .
.
├── Mouse
│   ├── CMakeLists.txt
│   └── mouse.cpp
└── Trackbar
    ├── CMakeLists.txt
    └── trackbar.cpp

2 directories, 4 files

确认OpenCV安装路径:

复制代码
$ find /home/daniel/ -name "OpenCVConfig.cmake"
/home/daniel/OpenCV/installation/opencv-4.9.0/lib/cmake/opencv4/
/home/daniel/OpenCV/opencv/build/OpenCVConfig.cmake
/home/daniel/OpenCV/opencv/build/unix-install/OpenCVConfig.cmake


$ export OpenCV_DIR=/home/daniel/OpenCV/installation/opencv-4.9.0/lib/cmake/opencv4/

C++应用Demo工程编译执行:

复制代码
$ cd Mouse
$ mkdir build
$ cd build
$ cmake ..
$ cmake --build . --config Release
$ cd ..
$ ./build/mouse

$ cd Trackbar
$ mkdir build
$ cd build
$ cmake ..
$ cmake --build . --config Release
$ cd ..
$ ./build/trackbar

2.2 Python应用Demo

Python应用Demo工程结构:

复制代码
012_mouse_and_trackbar/Python$ tree .
.
├── requirements.txt
├── mouse.py
└── trackbar.py

0 directories, 3 files

Python应用Demo工程执行:

复制代码
$ workoncv-4.9.0
$ python mouse.py
$ python trackbar.py

3. 鼠标位置跟踪注释

3.1 注册回调函数

OpenCV提供了鼠标事件检测功能,用于检测各种鼠标操作。

代码上采用注册回调函数方式实现:

C++:

复制代码
// highgui function called when mouse events occur
setMouseCallback("Window", drawRectangle);

Python:

复制代码
# highgui function called when mouse events occur
cv2.setMouseCallback("Window", drawRectangle)

3.2 回调操作

当有鼠标操作时:

  • EVENT_LBUTTONDOWN:记录左上角坐标
  • EVENT_LBUTTONUP:记录右下角坐标,并更新图像

实现对左上角和右下角的框选,矩形框标注选择范围。

C++:

复制代码
// Points to store the center of the circle and a point on the circumference
Point top_left_corner, bottom_right_corner;
// image image
Mat image;

// function which will be called on mouse input
void drawRectangle(int action, int x, int y, int flags, void *userdata)
{
  // Mark the center when left mouse button is pressed
  if( action == EVENT_LBUTTONDOWN )
  {
    top_left_corner = Point(x,y);
  }
  // When left mouse button is released
  else if( action == EVENT_LBUTTONUP)
  {
    bottom_right_corner = Point(x,y);
    // Draw rectangle
    rectangle(image, top_left_corner, bottom_right_corner, Scalar(0,255,0), 2, 8 );
    // Display image
    imshow("Window", image);
  }
  
}

Python:

复制代码
# Lists to store the points
top_left_corner=[]
bottom_right_corner=[]

# Define drawRectangle function
def drawRectangle(action, x, y, flags, *userdata):
  # Referencing global variables 
  global top_left_corner, bottom_right_corner
  # Action to be taken when left mouse button is pressed
  if action == cv2.EVENT_LBUTTONDOWN:
    top_left_corner = [(x,y)]
    # Action to be taken when left mouse button is released
  elif action == cv2.EVENT_LBUTTONUP:
    bottom_right_corner = [(x,y)]    
    # Draw the rectangle
    cv2.rectangle(image, top_left_corner[0], bottom_right_corner[0], (0,255,0),2, 8)
    cv2.imshow("Window",image)

3.3 效果

4. 使用轨迹栏调整图像大小

4.1 初始化轨迹栏&注册回调函数

创建轨迹栏对象时,代码上采用注册回调函数方式实现:

C++:

复制代码
int maxScaleUp = 100;
int scaleFactor = 1;

string windowName = "Resize Image";
string trackbarValue = "Scale";

// Create Trackbars and associate a callback function
createTrackbar(trackbarValue, windowName, &scaleFactor, maxScaleUp, scaleImage);

Python:

复制代码
maxScaleUp = 100
scaleFactor = 1
windowName = "Resize Image"
trackbarValue = "Scale"

# Create trackbar
cv2.createTrackbar(trackbarValue, windowName, scaleFactor, maxScaleUp, scaleImage)

4.2 回调操作

当有拖动轨迹栏滑块时,调用回调函数。根据滑块位置,对图像进行比例缩放。

C++:

复制代码
// Callback functions
void scaleImage(int, void*)
{
	// Read the image
	Mat image = imread("../../Input/sample.jpg");

    // Get the Scale factor from the trackbar
    double scaleFactorDouble = 1 + scaleFactor/100.0;
    
	// Set the factor to 1 if becomes 0
    if (scaleFactorDouble == 0)
	{
        scaleFactorDouble = 1;
    }
    
    Mat scaledImage;
    // Resize the image
    resize(image, scaledImage, Size(), scaleFactorDouble, scaleFactorDouble, INTER_LINEAR);
    // Display the image
    imshow(windowName, scaledImage);
}

Python:

复制代码
# Callback functions
def scaleImage(*args):
    # Get the scale factor from the trackbar 
    scaleFactor = 1+ args[0]/100.0
    # Resize the image
    scaledImage = cv2.resize(image, None, fx=scaleFactor, fy = scaleFactor, interpolation = cv2.INTER_LINEAR)
    cv2.imshow(windowName, scaledImage)

4.3 效果

通过轨迹栏的拖动,实现图像的放大缩小。

4. 总结

本文通过设置setMouseCallbackcreateTrackbar注册鼠标操作回调函数和轨迹栏空间回调函数,实现对应的OpenCV图像操作。

  • winname Name of the window.
  • onMouse Callback function for mouse events. See OpenCV samples on how to specify and use the callback.
  • userdata The optional parameter passed to the callback.
  • trackbarname Name of the created trackbar.
  • winname Name of the window that will be used as a parent of the created trackbar.
  • value Optional pointer to an integer variable whose value reflects the position of the slider. Upon creation, the slider position is defined by this variable.
  • count Maximal position of the slider. The minimal position is always 0.
  • onChange Pointer to the function to be called every time the slider changes position. This function should be prototyped as void Foo(int,void*); , where the first parameter is the trackbar position and the second parameter is the user data (see the next parameter). If the callback is the NULL pointer, no callbacks are called, but only value is updated.
  • userdata User data that is passed as is to the callback. It can be used to handle trackbar events without using global variables.

5. 参考资料

【1】ubuntu22.04@laptop OpenCV Get Started

【2】ubuntu22.04@laptop OpenCV安装

【3】ubuntu22.04@laptop OpenCV定制化安装

6. 补充

学习是一种过程,对于前面章节学习讨论过的,就不在文中重复了。

有兴趣了解更多的朋友,请从《ubuntu22.04@laptop OpenCV Get Started》开始,一个章节一个章节的了解,循序渐进。

相关推荐
Slow菜鸟34 分钟前
AI学习篇(三) | AI效率工具指南(2026年)
人工智能·学习
北京软秦科技有限公司1 小时前
AI审核如何助力合规取证?IACheck打造环境检测报告电子存证与法律风险防控新路径
大数据·人工智能
qq_359716231 小时前
openpi使用过程中相关问题
人工智能·深度学习·机器学习
minhuan2 小时前
医疗AI智能体:从数据到关怀人文设计:告别冰冷精准,构建有温度的诊疗交互.131
人工智能·ai智能体·智能体的人文设计·医疗ai人文设计·构建医疗ai智能体
Promise微笑2 小时前
驾驭AI引用:Geo优化中的内容评分机制与实战策略深度解析
人工智能
ai生成式引擎优化技术3 小时前
全球唯一四元结构底层架构问世:TSPR-WEB-LLM-HIC v2.0 终结大模型投毒与幻觉的终极技术范式
人工智能
听你说323 小时前
伊萨推出 ROBBI 360 协作机器人焊接工作站 简化自动化焊接部署流程
人工智能·机器人·自动化
weixin_408099673 小时前
【实战对比】在线 OCR 识别 vs OCR API 接口:从个人工具到系统集成该怎么选?
图像处理·人工智能·后端·ocr·api·图片文字识别·文字识别ocr
罗西的思考3 小时前
【OpenClaw】通过Nanobot源码学习架构---(2)外层控制逻辑
人工智能·机器学习