How to use the gdal.GCPsToGeoTransform function in GDAL

#~ pf('')
            ld('self.src_path',self.src_path, self.src)

        # check for source raster type
        src_ds = gdal.Open(self.src_path, GA_ReadOnly)
        self.src_ds = src_ds
        self.description = self.src_ds.GetMetadataItem('DESCRIPTION')

        # source is successfully opened, then create destination dir
        os.makedirs(self.dest)

        src_geotr = src_ds.GetGeoTransform()
        src_proj = txt2proj4(src_ds.GetProjection())
        gcps = src_ds.GetGCPs()
        if gcps:
            ld('src GCPsToGeoTransform', gdal.GCPsToGeoTransform(gcps))

        if not src_proj and gcps :
            src_proj = txt2proj4(src_ds.GetGCPProjection())

        override_srs = self.options.srs
        if override_srs is not None:
            src_proj = txt2proj4(override_srs)

        ld('src_proj', src_proj, 'src geotr', src_geotr)
        assert src_proj, 'The source does not have a spatial reference system assigned'

        src_bands = src_ds.RasterCount
        band1 = src_ds.GetRasterBand(1)
        if src_bands == 1 and band1.GetColorInterpretation() == GCI_PaletteIndex : # source is a paletted raster
            transparency = None
            if self.base_resampling == 'NearestNeighbour' and self.resampling == Image.NEAREST :

def gdal_get_transform(src_image):
    geo_trans = src_image.GetGeoTransform()
    if geo_trans == (0.0, 1.0, 0.0, 0.0, 0.0, 1.0):
        geo_trans = gdal.GCPsToGeoTransform(src_image.GetGCPs())

    return geo_trans

def gdal_get_transform(src_image):
    geo_trans = src_image.GetGeoTransform()
    if geo_trans == (0.0, 1.0, 0.0, 0.0, 0.0, 1.0):
        geo_trans = gdal.GCPsToGeoTransform(src_image.GetGCPs())

    return geo_trans

continue

            output_dataset = output_driver.Create(
                '', clip_shp_1, clip_shp_0,
                src_image.RasterCount, raster_band.DataType)

            # Copy All metadata data from src to dst
            domains = src_image.GetMetadataDomainList()
            for tag in domains:
                md = src_image.GetMetadata(tag)
                if md:
                    output_dataset.SetMetadata(md, tag)

            # Rewrite the rpc_md that we modified above.
            output_dataset.SetMetadata(rpc_md, 'RPC')
            output_dataset.SetGeoTransform(gdal.GCPsToGeoTransform(corner_gcps))
            output_dataset.SetProjection(gdal_get_projection(src_image))

            # End logging, print blank line for clarity
            print('')
            bands = src_image.RasterCount
            if bands > 1:
                for i in range(bands):
                    outBand = output_dataset.GetRasterBand(i + 1)
                    outBand.SetNoDataValue(nodata_values[i])
                    outBand.WriteArray(clip[i])
            else:
                outBand = output_dataset.GetRasterBand(1)
                outBand.SetNoDataValue(nodata_values[0])
                outBand.WriteArray(clip)

            if dst_img_file:

#~ pf('')
            ld('self.src_path',self.src_path, self.src)

        # check for source raster type
        src_ds = gdal.Open(self.src_path, GA_ReadOnly)
        self.src_ds = src_ds
        self.description = self.src_ds.GetMetadataItem('DESCRIPTION')

        # source is successfully opened, then create destination dir
        os.makedirs(self.dest)

        src_geotr = src_ds.GetGeoTransform()
        src_proj = txt2proj4(src_ds.GetProjection())
        gcps = src_ds.GetGCPs()
        if gcps:
            ld('src GCPsToGeoTransform', gdal.GCPsToGeoTransform(gcps))

        if not src_proj and gcps :
            src_proj = txt2proj4(src_ds.GetGCPProjection())

        override_srs = self.options.srs
        if override_srs is not None:
            src_proj = txt2proj4(override_srs)

        ld('src_proj', src_proj, 'src geotr', src_geotr)
        assert src_proj, 'The source does not have a spatial reference system assigned'

        src_bands = src_ds.RasterCount
        band1 = src_ds.GetRasterBand(1)
        if src_bands == 1 and band1.GetColorInterpretation() == GCI_PaletteIndex : # source is a paletted raster
            transparency = None
            if self.base_resampling == 'NearestNeighbour' and self.resampling == Image.NEAREST :

continue

            output_dataset = output_driver.Create(
                '', clip_shp_1, clip_shp_0,
                src_image.RasterCount, raster_band.DataType)

            # Copy All metadata data from src to dst
            domains = src_image.GetMetadataDomainList()
            for tag in domains:
                md = src_image.GetMetadata(tag)
                if md:
                    output_dataset.SetMetadata(md, tag)

            # Rewrite the rpc_md that we modified above.
            output_dataset.SetMetadata(rpc_md, 'RPC')
            output_dataset.SetGeoTransform(gdal.GCPsToGeoTransform(corner_gcps))
            output_dataset.SetProjection(gdal_get_projection(src_image))

            # End logging, print blank line for clarity
            print('')
            bands = src_image.RasterCount
            if bands > 1:
                for i in range(bands):
                    outBand = output_dataset.GetRasterBand(i + 1)
                    outBand.SetNoDataValue(nodata_values[i])
                    outBand.WriteArray(clip[i])
            else:
                outBand = output_dataset.GetRasterBand(1)
                outBand.SetNoDataValue(nodata_values[0])
                outBand.WriteArray(clip)

            if dst_img_file:

if args.render_cls:
            eType = gdal.GDT_Byte
        else:
            eType = gdal.GDT_Float32
        dsm = dtmDriver.Create(
            args.output_dsm, xsize=dtm.RasterXSize,
            ysize=dtm.RasterYSize, bands=1, eType=eType,
            options=options)
        if (projection):
            # georeference through affine geotransform
            dsm.SetProjection(projection)
            dsm.SetGeoTransform(transform)
        else:
            # georeference through GCPs
            dsm.SetGCPs(gcps, gcpProjection)
            gdal.GCPsToGeoTransform(gcps, transform)
        corners = [[0, 0], [0, dtm.RasterYSize],
                   [dtm.RasterXSize, dtm.RasterYSize], [dtm.RasterXSize, 0]]
        geoCorners = numpy.zeros((4, 2))
        for i, corner in enumerate(corners):
            geoCorners[i] = [
                transform[0] + corner[0] * transform[1] +
                corner[1] * transform[2],
                transform[3] + corner[0] * transform[4] +
                corner[1] * transform[5]]
        dtmBounds[0] = numpy.min(geoCorners[:, 0])
        dtmBounds[1] = numpy.max(geoCorners[:, 0])
        dtmBounds[2] = numpy.min(geoCorners[:, 1])
        dtmBounds[3] = numpy.max(geoCorners[:, 1])

        if args.render_cls:
            # label for no building