Question

我正在尝试编写自己的裁剪功能，因此我可以从较大的图像中选择一个区域，然后对其执行一些其他操作。我使用matplotlib导入和显示图像：self.img=plt.imread("someimage.png")

如果我留在画布区域，这可以正常工作：

 def __onclick__(self, event):

    self.point=[]
    if event.xdata is not None:
        xholder=event.xdata
    else:
        xholder = 0
    if event.ydata is not None:
        yholder = event.ydata
    else:
        yholder = 0 
    self.point.append([int(xholder),int(yholder)])
def __onrelease__(self,event):
    if event.xdata is not None:
        xholder=event.xdata
    else:
        xholder = self.img.shape[0]
    if event.ydata is not None:
        yholder = event.ydata
    else:
        yholder = self.img.shape[1]
    self.point.append([int(xholder),int(yholder)])
    self.plotcanvas.axes.imshow(self.img[self.point[0][1]:self.point[1][1],self.point[0][0]:self.point[1][0]])
    self.plotcanvas.draw()

然而，当我走出画布边界event.xdata和event.ydata时，返回（无，无）。一旦鼠标单击在画布区域中注册，是否仍然只将鼠标移动限制在画布区域？

使用允许导入.png文件然后裁剪的代码进行编辑

import sys
from PyQt4 import QtGui, QtCore
from matplotlib import pyplot as plt
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
from matplotlib.backends.backend_qt4agg import NavigationToolbar2QTAgg as NavigationToolbar
import numpy as np


class Example(QtGui.QMainWindow):

    def __init__(self):
        super(Example, self).__init__()
        self.initUI()

    def initUI(self):           
        self.statusBar()
        self.form_widget=FormWidget(self)
        self.setCentralWidget(self.form_widget)
        openFile = QtGui.QAction('Open', self)
        openFile.setShortcut('Ctrl+O')
        openFile.setStatusTip('Open new File')
        openFile.triggered.connect(self.showDialog)
        toolbar = self.addToolBar('Exit')
        toolbar.addAction(openFile)
        self.show()

    def showDialog(self):

        fname = QtGui.QFileDialog.getOpenFileName(self, 'Open file', 
                '/home')

        self.form_widget.redraw(fname)

class FormWidget(QtGui.QWidget):
    def __init__(self,parent):        
        super(FormWidget,self).__init__() 
        self.layout=QtGui.QVBoxLayout(self)
        self.mpcanvas=MyMplCanvas(self)
        self.plotcanvas=MyMplCanvas(self)
        self.layout.addWidget(self.plotcanvas)
        self.layout.addWidget(self.mpcanvas)
        self.setLayout(self.layout)
        self.cidpresscsv=self.mpcanvas.fig.canvas.mpl_connect('button_press_event', self.__onclick__)
        self.cidreleasecsv=self.mpcanvas.fig.canvas.mpl_connect('button_release_event', self.__onrelease__)
    def redraw(self,fname):
        self.mpcanvas.axes=self.mpcanvas.fig.add_subplot(111)
        self.img=plt.imread(fname)
        self.mpcanvas.axes.imshow(self.img)
        self.mpcanvas.draw()
    def __onclick__(self, event):
        self.point=[]
        if event.xdata is not None:
            xholder=event.xdata
        else:
            xholder = 0
        if event.ydata is not None:
            yholder = event.ydata
        else:
            yholder = 0
        self.point.append([int(xholder),int(yholder)])
    def __onrelease__(self,event):
        if event.xdata is not None:
            xholder=event.xdata
        else:
            xholder = self.img.shape[0]
        if event.ydata is not None:
            yholder = event.ydata
        else:
            yholder = self.img.shape[1]
        self.point.append([int(xholder),int(yholder)])
        self.plotcanvas.axes.imshow(self.img[self.point[0][1]:self.point[1][1],self.point[0][0]:self.point[1][0]])
        self.plotcanvas.draw()




class MyMplCanvas(FigureCanvas):
    def __init__(self, parent=None, width=5, height=4, dpi=100):
        self.fig = plt.figure(figsize=(width, height), dpi=dpi)
        self.axes = self.fig.add_subplot(111)
        self.fig.tight_layout()
        self.axes.hold(False)
        self.compute_initial_figure()
        FigureCanvas.__init__(self, self.fig)
        self.setParent(parent)
        FigureCanvas.setSizePolicy(self,
                                   QtGui.QSizePolicy.Expanding,
                                   QtGui.QSizePolicy.Expanding)
        FigureCanvas.updateGeometry(self)

    def compute_initial_figure(self):
        pass



def main():

    app = QtGui.QApplication(sys.argv)
    ex = Example()
    sys.exit(app.exec_())


if __name__ == '__main__':
    main()

这是在删除所有不必要的东西之后出现的，并且仍然创建一个功能程序，允许您导入.png文件，然后将其中的区域整理出来。我确信Ed Smith提出的Rectangle选择器可能会起作用，但是我无法使示例代码工作，并且对于存储值的位置以及eclick和erelease在其他事件处理程序的上下文中的工作方式感到困惑。我担心我不太熟悉matplotlib和python。

Answer 1

框选择器matplotlib widget可能是最简单的方法。您可以将代码与您拥有的图像一起使用：

<?
ignore_user_abort();
ob_start();

// do stuff, generate output

// get size of the content
$length = ob_get_length();

// tell client to close the connection after $length bytes received
header('Connection: close');
header("Content-Length: $length");

// flush all output
ob_end_flush();
flush();

// close session if you have one ...
// continue your processing tasks ...
?>

虽然鼠标不限于此框，但from matplotlib.widgets import RectangleSelector from pylab import * def onselect(eclick, erelease): 'eclick and erelease are matplotlib events at press and release' print ' startposition : (%f, %f)' % (eclick.xdata, eclick.ydata) print ' endposition : (%f, %f)' % (erelease.xdata, erelease.ydata) print ' used button : ', eclick.button def toggle_selector(event): print ' Key pressed.' if event.key in ['Q', 'q'] and toggle_selector.RS.active: print ' RectangleSelector deactivated.' toggle_selector.RS.set_active(False) if event.key in ['A', 'a'] and not toggle_selector.RS.active: print ' RectangleSelector activated.' toggle_selector.RS.set_active(True) fig = figure ax = subplot(111) A = np.random.random((30,30)) ax.imshow(A) toggle_selector.RS = RectangleSelector(ax, onselect, drawtype='box') connect('key_press_event', toggle_selector) show()和minspanx为minspany时的默认行为是将返回的坐标限制在框中。我不认为你可以很容易地将鼠标移动限制在画布上。

在matplotlib图中限制鼠标到画布区域

1 个答案: