How to use the deeplabcut.refine_training_dataset.refinement.MainFrame function in deeplabcut

def prevImage(self, event):
        """
        Checks the previous Image and enables user to move the annotations.
        """

        MainFrame.saveEachImage(self)

        # Checks if zoom/pan button is ON
        MainFrame.updateZoomPan(self)

        self.statusbar.SetStatusText('Working on folder: {}'.format(os.path.split(str(self.dir))[-1]))
        self.next.Enable(True)
        self.iter = self.iter - 1

        # Checks for the first image and disables the Previous button
        if self.iter == 0:
            self.prev.Enable(False)

        if self.iter >= 0:
            self.updatedCoords = []
            # Reading Image
            self.img = os.path.join(self.project_path,self.index[self.iter])

def nextImage(self, event):
        """
        Reads the next image and enables the user to move the annotations
        """
        #  Checks for the last image and disables the Next button
        if len(self.index) - self.iter == 1:
            self.next.Enable(False)
            return
        self.prev.Enable(True)

        # Checks if zoom/pan button is ON
        MainFrame.updateZoomPan(self)

        MainFrame.saveEachImage(self)
        self.statusbar.SetStatusText('Working on folder: {}'.format(os.path.split(str(self.dir))[-1]))

        self.iter = self.iter + 1

        if len(self.index) > self.iter:
            self.updatedCoords = []
            self.img = os.path.join(self.project_path,self.index[self.iter])
            img_name = Path(self.img).name

            # Plotting
            self.figure.delaxes(self.figure.axes[1]) # Removes the axes corresponding to the colorbar
            self.figure,self.axes,self.canvas,self.toolbar = self.image_panel.drawplot(self.img,img_name,self.iter,self.index,self.threshold,self.bodyparts,self.colormap,self.preview,keep_view=self.view_locked)
            im = io.imread(self.img)
            self.axes.callbacks.connect('xlim_changed', self.onZoom)

def nextImage(self, event):
        """
        Reads the next image and enables the user to move the annotations
        """
        #  Checks for the last image and disables the Next button
        if len(self.index) - self.iter == 1:
            self.next.Enable(False)
            return
        self.prev.Enable(True)

        # Checks if zoom/pan button is ON
        MainFrame.updateZoomPan(self)

        MainFrame.saveEachImage(self)
        self.statusbar.SetStatusText('Working on folder: {}'.format(os.path.split(str(self.dir))[-1]))

        self.iter = self.iter + 1

        if len(self.index) > self.iter:
            self.updatedCoords = []
            self.img = os.path.join(self.project_path,self.index[self.iter])
            img_name = Path(self.img).name

            # Plotting
            self.figure.delaxes(self.figure.axes[1]) # Removes the axes corresponding to the colorbar
            self.figure,self.axes,self.canvas,self.toolbar = self.image_panel.drawplot(self.img,img_name,self.iter,self.index,self.threshold,self.bodyparts,self.colormap,self.preview,keep_view=self.view_locked)
            im = io.imread(self.img)
            self.axes.callbacks.connect('xlim_changed', self.onZoom)
            self.axes.callbacks.connect('ylim_changed', self.onZoom)
            if np.max(im) == 0:

if self.move2corner==True:
                ny,nx=np.shape(im)[0],np.shape(im)[1]
                if self.points[0]>nx or self.points[0]<0:
                    self.points[0]=self.center[0]
                if self.points[1]>ny or self.points[1]<0:
                    self.points[1]= self.center[1]

            if not ('CollectedData_' in self.fileName) and self.likelihood < self.threshold:
                circle = [patches.Circle((self.points[0], self.points[1]), radius=self.markerSize, facecolor = 'None', edgecolor = color)]
            else:
                circle = [patches.Circle((self.points[0], self.points[1]), radius=self.markerSize, fc = color, alpha=self.alpha)]

            self.axes.add_patch(circle[0])
            self.dr = auxfun_drag.DraggablePoint(circle[0],bp,self.likelihood)
            self.dr.connect()
            self.dr.coords = MainFrame.getLabels(self,self.iter)[bpindex]
            self.drs.append(self.dr)
            self.updatedCoords.append(self.dr.coords)
        self.figure.canvas.draw()

# Checks for the first image and disables the Previous button
        if self.iter == 0:
            self.prev.Enable(False)

        if self.iter >= 0:
            self.updatedCoords = []
            # Reading Image
            self.img = os.path.join(self.project_path,self.index[self.iter])
            img_name = Path(self.img).name

            # Plotting
            self.figure.delaxes(self.figure.axes[1]) # Removes the axes corresponding to the colorbar
            self.figure,self.axes,self.canvas,self.toolbar = self.image_panel.drawplot(self.img,img_name,self.iter,self.index,self.threshold,self.bodyparts,self.colormap,self.preview,keep_view=self.view_locked)
            self.axes.callbacks.connect('xlim_changed', self.onZoom)
            self.axes.callbacks.connect('ylim_changed', self.onZoom)
            MainFrame.plot(self,self.img)
        else:
            self.prev.Enable(False)
        MainFrame.saveEachImage(self)

def saveDataSet(self, event):

        MainFrame.saveEachImage(self)

        # Checks if zoom/pan button is ON
        MainFrame.updateZoomPan(self)
        self.statusbar.SetStatusText("File saved")

        self.Dataframe = MainFrame.check_labels(self)
        # Overwrite machine label file
        self.Dataframe.to_hdf(self.dataname, key='df_with_missing', mode='w')
        
        self.Dataframe.columns.set_levels([self.scorer.replace(self.scorer,self.humanscorer)],level=0,inplace=True)
        self.Dataframe = self.Dataframe.drop('likelihood',axis=1,level=2)

        if Path(self.dir,'CollectedData_'+self.humanscorer+'.h5').is_file():
            print("A training dataset file is already found for this video. The refined machine labels are merged to this data!")
            DataU1 = pd.read_hdf(os.path.join(self.dir,'CollectedData_'+self.humanscorer+'.h5'), 'df_with_missing')
            # combine datasets Original Col. + corrected machinefiles:
            DataCombined = pd.concat([self.Dataframe,DataU1])
            # Now drop redundant ones keeping the first one [this will make sure that the refined machine file gets preference]
            DataCombined = DataCombined[~DataCombined.index.duplicated(keep='first')]
            '''
            if len(self.droppedframes)>0: #i.e. frames were dropped/corrupt. also remove them from original file (if they exist!)
                for fn in self.droppedframes:

"""
                If ok is selected then the image is updated with the thresholded value of the likelihood
                """
                textBox = wx.TextEntryDialog(self, "Select the likelihood threshold",caption = "Enter the threshold",value="0.1")
                textBox.ShowModal()
                self.threshold = float(textBox.GetValue())
                textBox.Destroy()
                self.img = os.path.join(self.project_path,self.index[self.iter])
                img_name = Path(self.img).name
                self.axes.clear()
                self.preview = False
                self.figure.delaxes(self.figure.axes[1]) # Removes the axes corresponding to the colorbar
                self.figure,self.axes,self.canvas,self.toolbar = self.image_panel.drawplot(self.img,img_name,self.iter,self.index,self.threshold,self.bodyparts,self.colormap,self.preview)
                self.axes.callbacks.connect('xlim_changed', self.onZoom)
                self.axes.callbacks.connect('ylim_changed', self.onZoom)
                MainFrame.plot(self,self.img)
                MainFrame.saveEachImage(self)
            else:
                self.figure.delaxes(self.figure.axes[1]) # Removes the axes corresponding to the colorbar
                self.figure,self.axes,self.canvas,self.toolbar = self.image_panel.drawplot(self.img,img_name,self.iter,self.index,self.threshold,self.bodyparts,self.colormap,self.preview)
                self.axes.callbacks.connect('xlim_changed', self.onZoom)
                self.axes.callbacks.connect('ylim_changed', self.onZoom)
                MainFrame.plot(self,self.img)
                MainFrame.saveEachImage(self)

        else:
            msg = wx.MessageBox('No Machinelabels file found! Want to retry?', 'Error!', wx.YES_NO | wx.ICON_WARNING)
            if msg == 2:
                self.load.Enable(True)
                self.next.Enable(False)
                self.save.Enable(False)

self.next.Enable(False)
            self.prev.Enable(False)
            self.slider.Enable(False)
            self.checkBox.Enable(False)

        nextFilemsg = wx.MessageBox('File saved. Do you want to refine another file?', 'Repeat?', wx.YES_NO | wx.ICON_INFORMATION)
        if nextFilemsg == 2:
            self.file = 1
            self.axes.clear()
            self.figure.delaxes(self.figure.axes[1])
            self.choiceBox.Clear(True)
            MainFrame.updateZoomPan(self)
            self.load.Enable(True)
            # self.slider.Enable(False)
            # self.checkBox.Enable(False)
            MainFrame.browseDir(self, event)

else:
            self.Dataframe.sort_index(inplace=True)
            self.Dataframe.to_hdf(os.path.join(self.dir,'CollectedData_'+ self.humanscorer+'.h5'), key='df_with_missing', mode='w')
            self.Dataframe.to_csv(os.path.join(self.dir,'CollectedData_'+ self.humanscorer +'.csv'))
            self.next.Enable(False)
            self.prev.Enable(False)
            self.slider.Enable(False)
            self.checkBox.Enable(False)

        nextFilemsg = wx.MessageBox('File saved. Do you want to refine another file?', 'Repeat?', wx.YES_NO | wx.ICON_INFORMATION)
        if nextFilemsg == 2:
            self.file = 1
            self.axes.clear()
            self.figure.delaxes(self.figure.axes[1])
            self.choiceBox.Clear(True)
            MainFrame.updateZoomPan(self)
            self.load.Enable(True)
            # self.slider.Enable(False)
            # self.checkBox.Enable(False)
            MainFrame.browseDir(self, event)