

settings = \
    {
        'augment':[],
        'modelname':basename(__file__).split('.')[0],
        'backend': 'tensorflow',
        'batchsize':256,
        'channels':1,
        'colormode':'RGB',
        'crop': 0,
        'crop_test': 6,
        'decay':1e-6,
        'decimation': 'bicubic',
        'espatience' : 20,
        'epoch':100,
        'inputsize':16,
        'interp_compare': '',
        'interp_up': 'bicubic',
        'lrpatience': 10,
        'lrfactor' : 0.5,
        'metrics': 'ALL',
        'minimumlrate' : 1e-7,
        'noise':'',
        'normalization':['divide', 255.0],
        'normalizeback': False,
        'normalizeground':False,'lrate':0.001,
        'outputdir':'',
        'saveimages': False,
        'scale':2,
        'seed': 19,
        'shuffle' : True,
        'stride':5,
        'target_channels': 1,
        'target_cmode' : 'RGB',
        'traindir': r'',
        'testpath' : [r''],
        'upscaleimage': False,
        'valdir': r'D:\calismalarim\datasets\US\UltrasoundCases\USCases Database\val',
        'weightpath':'',
        'workingdir': abspath(dirname(__file__))
    }

