mask file generation

#!/usr/bin/env python3

import multiresolutionimageinterface as mir
import matplotlib.pyplot as plt
reader = mir.MultiResolutionImageReader()
mr_image = reader.open('/home/wli/Downloads/tumor_009.tif')
# dims=mr_image.getLevelDimensions(6)
# tile = mr_image.getUCharPatch(0, 0, dims[0], dims[1], 6)
# plt.imshow(tile)
# plt.show()
annotation_list=mir.AnnotationList()
xml_repository = mir.XmlRepository(annotation_list)
xml_repository.setSource('/home/wli/Downloads/tumor_009.xml')
xml_repository.load()
#annotation=annotation_list.getAnnotation(0)
#print(annotation.getArea())
#print(annotation.getNumberOfPoints())
#print(annotation.getCoordinate(0).getX())
annotation_mask=mir.AnnotationToMask()
camelyon17_type_mask = False
label_map = {'metastases': 1, 'normal': 2} if camelyon17_type_mask else {'_0': 1, '_1': 1, '_2': 0}
conversion_order = ['metastases', 'normal'] if camelyon17_type_mask else  ['_0', '_1', '_2']
output_path='/home/wli/Downloads/tumor_009_labels.tif'
annotation_mask.convert(annotation_list, output_path, mr_image.getDimensions(), mr_image.getSpacing(), label_map, conversion_order)