Python如何获取鼠标坐标 python获取光标位置

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落花流水人家 2023-10-15 17:26:27

文章标签 Python如何获取鼠标坐标 pycharm python opencv 快捷键 文章分类 Python 后端开发

一、pycharm

1.1 鼠标悬停在函数名上大概1-2秒钟或Ctrl+Q

Python如何获取鼠标坐标 python获取光标位置_Python如何获取鼠标坐标

或者如果您不想等待，直接光标放在函数名上后，按Ctr+Q快捷键，也可以迅速显示这个注释窗口。

1.2 鼠标光标落在函数/方法的括号内时使用快捷键Ctrl+P定位当前光标输入的参数

Python如何获取鼠标坐标 python获取光标位置_python_02

1.3 鼠标光标悬停在函数的名字或参数上，按住Ctrl键+鼠标左键单击。

Python如何获取鼠标坐标 python获取光标位置_pycharm_03

Python如何获取鼠标坐标 python获取光标位置_快捷键_04

其实这种方法就是从源头上查看某内置函数、某模块对应的代码。

如何知道这个代码文件所在路径呢？请用【__file__】魔法命令（详见Python __file__属性：查看模块的源文件路径）。

以 string 模块为例：

import string
print(string.__file__)  # 输出D:\python3.6\lib\string.py

但请注意，并不是所有模块都提供 __file__ 属性，因为并不是所有模块的实现都采用python语言，有些模块采用的是其它编程语言（如 C 语言）。

1.4 打印help函数的返回结果。

下面以OpenCV-python的findContours函数为例。

print(help(cv2.findContours))

#输出结果如下
Help on built-in function findContours:
findContours(...)
    findContours(image, mode, method[, contours[, hierarchy[, offset]]]) -> contours, hierarchy
    .   @brief Finds contours in a binary image.
    .   
    .   The function retrieves contours from the binary image using the algorithm @cite Suzuki85 . The contours
    .   are a useful tool for shape analysis and object detection and recognition. See squares.cpp in the
    .   OpenCV sample directory.
    .   @note Since opencv 3.2 source image is not modified by this function.
    .   
    .   @param image Source, an 8-bit single-channel image. Non-zero pixels are treated as 1's. Zero
    .   pixels remain 0's, so the image is treated as binary . You can use #compare, #inRange, #threshold ,
    .   #adaptiveThreshold, #Canny, and others to create a binary image out of a grayscale or color one.
    .   If mode equals to #RETR_CCOMP or #RETR_FLOODFILL, the input can also be a 32-bit integer image of labels (CV_32SC1).
    .   @param contours Detected contours. Each contour is stored as a vector of points (e.g.
    .   std::vector<std::vector<cv::Point> >).
    .   @param hierarchy Optional output vector (e.g. std::vector<cv::Vec4i>), containing information about the image topology. It has
    .   as many elements as the number of contours. For each i-th contour contours[i], the elements
    .   hierarchy[i][0] , hierarchy[i][1] , hierarchy[i][2] , and hierarchy[i][3] are set to 0-based indices
    .   in contours of the next and previous contours at the same hierarchical level, the first child
    .   contour and the parent contour, respectively. If for the contour i there are no next, previous,
    .   parent, or nested contours, the corresponding elements of hierarchy[i] will be negative.
    .   @note In Python, hierarchy is nested inside a top level array. Use hierarchy[0][i] to access hierarchical elements of i-th contour.
    .   @param mode Contour retrieval mode, see #RetrievalModes
    .   @param method Contour approximation method, see #ContourApproximationModes
    .   @param offset Optional offset by which every contour point is shifted. This is useful if the
    .   contours are extracted from the image ROI and then they should be analyzed in the whole image
    .   context.
None

1.5 利用doc函数实现注释调用。

print(cv2.findContours.__doc__)

#下面是输出；和上面的用help函数来调用注释的结果一样
findContours(image, mode, method[, contours[, hierarchy[, offset]]]) -> contours, hierarchy
.   @brief Finds contours in a binary image.
.   
.   The function retrieves contours from the binary image using the algorithm @cite Suzuki85 . The contours
.   are a useful tool for shape analysis and object detection and recognition. See squares.cpp in the
.   OpenCV sample directory.
.   @note Since opencv 3.2 source image is not modified by this function.
.   
.   @param image Source, an 8-bit single-channel image. Non-zero pixels are treated as 1's. Zero
.   pixels remain 0's, so the image is treated as binary . You can use #compare, #inRange, #threshold ,
.   #adaptiveThreshold, #Canny, and others to create a binary image out of a grayscale or color one.
.   If mode equals to #RETR_CCOMP or #RETR_FLOODFILL, the input can also be a 32-bit integer image of labels (CV_32SC1).
.   @param contours Detected contours. Each contour is stored as a vector of points (e.g.
.   std::vector<std::vector<cv::Point> >).
.   @param hierarchy Optional output vector (e.g. std::vector<cv::Vec4i>), containing information about the image topology. It has
.   as many elements as the number of contours. For each i-th contour contours[i], the elements
.   hierarchy[i][0] , hierarchy[i][1] , hierarchy[i][2] , and hierarchy[i][3] are set to 0-based indices
.   in contours of the next and previous contours at the same hierarchical level, the first child
.   contour and the parent contour, respectively. If for the contour i there are no next, previous,
.   parent, or nested contours, the corresponding elements of hierarchy[i] will be negative.
.   @note In Python, hierarchy is nested inside a top level array. Use hierarchy[0][i] to access hierarchical elements of i-th contour.
.   @param mode Contour retrieval mode, see #RetrievalModes
.   @param method Contour approximation method, see #ContourApproximationModes
.   @param offset Optional offset by which every contour point is shifted. This is useful if the
.   contours are extracted from the image ROI and then they should be analyzed in the whole image
.   context.