generate_nonlinear_ldd.py 文件源码

def generate_ldd_model_csv(input_csv,model=None,mask=None,work_prefix=None,options={}):
    internal_sample=[]

    with open(input_csv, 'r') as csvfile:
        reader = csv.reader(csvfile, delimiter=',', quoting=csv.QUOTE_NONE)
        for row in reader:
            internal_sample.append(MriDataset(scan=row[0],mask=row[1]))

    internal_model=None
    if model is not None:
        internal_model=MriDataset(scan=model,mask=mask)

    if work_prefix is not None and not os.path.exists(work_prefix):
        os.makedirs(work_prefix)

    return generate_ldd_average(internal_sample,internal_model,
                                prefix=work_prefix,options=options)