Подключение слайдера к графическому представлению в PyQt

Я пытаюсь отобразить данные изображения, считанные из двоичного файла (у меня есть код, написанный для извлечения этих данных из файла и их сохранения в виде изображения для использования с QImage() ). Что я хотел бы сделать, так это подключить ползунок к виджету «Графическое представление», чтобы при перемещении ползунка он перемещался по кадрам и отображал изображение из этого кадра (это эхограммы длиной от 1 до 500 кадров). Я очень новичок в PyQt, и мне было любопытно, как можно вообще начать это делать?

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