2

我正在尝试显示从二进制文件中读取的图像数据（我编写了用于从文件中检索此数据并将其存储为图像以供 QImage() 使用的代码）。我想做的是将滑块连接到图形视图小部件，这样当您移动滑块时，它会在帧中移动并显示该帧中的图像（这些是长度范围为 1-500 帧的回声图）。我对 PyQt 很陌生，很好奇一个人是如何开始这样做的？ 

from PyQt4.QtCore import *
from PyQt4.QtGui import *
import numpy as np



class FileHeader(object):

    fileheader_fields=      ("filetype","fileversion","numframes","framerate","resolution","numbeams","samplerate","samplesperchannel","receivergain","windowstart","winlengthsindex","reverse","serialnumber","date","idstring","ID1","ID2","ID3","ID4","framestart","frameend","timelapse","recordInterval","radioseconds","frameinterval","userassigned")
   fileheader_formats=('S3','B','i4','i4','i4','i4','f','i4','i4','i4','i4','i4','i4','S32','S256','i4','i4','i4','i4','i4','i4','i4','i4','i4','i4','S136')

    def __init__(self,filename,parent=None):
        a=QApplication([])
        filename=str(QFileDialog.getOpenFileName(None,"open file","C:/vprice/DIDSON/DIDSON Data","*.ddf"))
        self.infile=open(filename, 'rb')
        dtype=dict(names=self.fileheader_fields, formats=self.fileheader_formats)
        self.fileheader=np.fromfile(self.infile, dtype=dtype, count=1)
        self.fileheader_length=self.infile.tell()


    for field in self.fileheader_fields:
        setattr(self,field,self.fileheader[field])



    def get_frame_first(self):
        frame=Frame(self.infile)
        print self.fileheader
        self.infile.seek(self.fileheader_length)
        print frame.frameheader
        print frame.data



    def __iter__(self):
        self.infile.seek(self.fileheader_length)

    for _ in range(self.numframes):
        yield Frame(self.infile)

    #def close(self):
        #self.infile.close()
    def display(self):
        print self.fileheader


class Frame(object):
    frameheader_fields=("framenumber","frametime","version","status","year","month","day","hour","minute","second","hsecond","transmit","windowstart","index","threshold","intensity","receivergain","degc1","degc2","humidity","focus","battery","status1","status2","velocity","depth","altitude","pitch","pitchrate","roll","rollrate","heading","headingrate","sonarpan","sonartilt","sonarroll","latitude","longitude","sonarposition","configflags","userassigned")
    frameheader_formats=("i4","2i4","S4","i4","i4","i4","i4","i4","i4","i4","i4","i4","i4","i4","i4","i4","i4","i4","i4","i4","i4","i4","S16","S16","f","f","f","f","f","f","f","f","f","f","f","f","f8","f8","f","i4","S60")
    data_format="uint8"

    def __init__(self,infile):

        dtype=dict(names=self.frameheader_fields,formats=self.frameheader_formats)
        self.frameheader=np.fromfile(infile,dtype=dtype,count=1)


        for field in self.frameheader_fields:
            setattr(self,field,self.frameheader[field])

        ncols,nrows=96,512


        self.data=np.fromfile(infile,self.data_format,count=ncols*nrows)

        self.data=self.data.reshape((nrows,ncols))

class QEchogram():
    def __init__(self):
        self.__colorTable=[]
        self.colorTable=None
        self.threshold=[50,255]
        self.painter=None
        self.image=None

    def echogram(self):
        fileheader=FileHeader(self)
        frame=Frame(fileheader.infile)
        echoData=frame.data

        #fileName = fileName

        self.size=[echoData.shape[0],echoData.shape[1]]

        #  define the size of the data (and resulting image)
        #size = [96, 512]

        #  create a color table for our image
        #  first define the colors as RGB triplets
        colorTable =  [(255,255,255),
                       (159,159,159),
                       (95,95,95),
                       (0,0,255),
                       (0,0,127),
                       (0,191,0),
                       (0,127,0),
                       (255,255,0),
                       (255,127,0),
                       (255,0,191),
                       (255,0,0),
                       (166,83,60),
                       (120,60,40),
                       (200,200,200)]

    #  then create a color table for Qt - this encodes the color table
    #  into a list of 32bit integers (4 bytes) where each byte is the
    #  red, green, blue and alpha 8 bit values. In this case we don't
    #  set alpha so it defaults to 255 (opaque)
        ctLength = len(colorTable)
        self.__ctLength=ctLength
        __colorTable = []
        for c in colorTable:
            __colorTable.append(QColor(c[0],c[1],c[2]).rgb())




        echoData = np.round((echoData - self.threshold[0])*(float(self.__ctLength)/(self.threshold[1]-self.threshold[0])))
        echoData[echoData < 0] = 0
        echoData[echoData > self.__ctLength-1] = self.__ctLength-1
        echoData = echoData.astype(np.uint8)
        self.data=echoData

    #  create an image from our numpy data
        image = QImage(echoData.data, echoData.shape[1], echoData.shape[0], echoData.shape[1],
                   QImage.Format_Indexed8)
        image.setColorTable(__colorTable)

    #  convert to ARGB
        image = image.convertToFormat(QImage.Format_ARGB32)


    #  save the image to file
        image.save(fileName)
        self.image=QImage(self.size[0],self.size[1],QImage.Format_ARGB32)
        self.painter=QPainter(self.image)
        self.painter.drawImage(QRect(0.0,0.0,self.size[0],self.size[1]),image)

    def getImage(self):
        self.painter.end()
        return self.image
    def getPixmap(self):
        self.painter.end()
        return QPixmap.fromImage(self.image)




if __name__=="__main__":

    data=QEchogram()
    fileName="horizontal.png"
    data.echogram()
    dataH=data.data
    print "Horizontal data", dataH
4

2 回答 2

5

如果您展示了到目前为止您正在尝试的内容，我可以给您一个更具体的答案，但现在我只会做出假设并举一个例子。

首先，您要做的是创建一个QSlider。您将 QSlider 最小值/最大值设置为您可用的图像范围。当您滑动它时，sliderMoved信号会触发并告诉您新值是什么。

接下来，您可以提前创建一个包含所有QPixmap图像的列表。如果这些图像很大并且您担心内存，您可能必须使用您已经编码的方法按需创建它们。但是我们假设您现在可以将它们放在一个列表中，以使示例更容易。

然后使用单个QGraphicsPixmapItem创建 QGraphics 设置。该项目可以根据需要替换其像素图。

把它们放在一起，你会得到这样的东西：

from PyQt4 import QtCore, QtGui

class Widget(QtGui.QWidget):

    def __init__(self, parent=None):
        super(Widget, self).__init__(parent)
        self.resize(640,480)
        self.layout = QtGui.QVBoxLayout(self)

        self.scene = QtGui.QGraphicsScene(self)
        self.view = QtGui.QGraphicsView(self.scene)
        self.layout.addWidget(self.view)

        self.image = QtGui.QGraphicsPixmapItem()
        self.scene.addItem(self.image)
        self.view.centerOn(self.image)

        self._images = [
            QtGui.QPixmap('Smiley.png'),
            QtGui.QPixmap('Smiley2.png')
        ]

        self.slider = QtGui.QSlider(self)
        self.slider.setOrientation(QtCore.Qt.Horizontal)
        self.slider.setMinimum(0)
        # max is the last index of the image list
        self.slider.setMaximum(len(self._images)-1)
        self.layout.addWidget(self.slider)

        # set it to the first image, if you want.
        self.sliderMoved(0)

        self.slider.sliderMoved.connect(self.sliderMoved)

    def sliderMoved(self, val):
        print "Slider moved to:", val
        try:
            self.image.setPixmap(self._images[val])
        except IndexError:
            print "Error: No image at index", val

if __name__ == "__main__":
    app = QtGui.QApplication([])
    w = Widget()
    w.show()
    w.raise_()
    app.exec_()

您可以看到我们设置了滑块的范围以匹配您的图像列表。如果图像列表的内容发生变化，您可以随时更改此范围。当sliderMoved触发时，它将使用该值作为图像列表的索引并设置像素图。

我还在我们的 SLOT 中添加了一个检查sliderMoved()，以防您的滑块范围与您的图像列表不同步。如果您滑动到图像列表中不存在的索引，它将优雅地失败并离开现有图像。

于 2012-06-30T05:37:54.967 回答
2

您正在做的很多工作——将图像数据转换为 QImage，使用滑块显示帧——可能会使用为此目的编写的库更好地解决。我可以想到几个库可以与 PyQt 一起使用，并提供您需要的一切：

（免责声明：无耻插件）

如果您可以将所有图像数据收集到一个 3D numpy 数组中，那么在 pyqtgraph 中显示它的代码如下所示：

import pyqtgraph as pg
pg.image(imageData)

这将为您提供带有框架滑块和颜色查找表控件的可缩放图像显示。

于 2012-07-02T20:54:09.930 回答