How to use SMOTENC inside the Pipeline?

Question

I would greatly appreciate if you could let me know how to use SMOTENC. I wrote:

num_indices1 = list(X.iloc[:,np.r_[0:94,95,97,100:123]].columns.values)
cat_indices1 = list(X.iloc[:,np.r_[94,96,98,99,123:160]].columns.values)
print(len(num_indices1))
print(len(cat_indices1))

pipeline=Pipeline(steps= [
    # Categorical features
    ('feature_processing', FeatureUnion(transformer_list = [
            ('categorical', MultiColumn(cat_indices1)),

            #numeric
            ('numeric', Pipeline(steps = [
                ('select', MultiColumn(num_indices1)),
                ('scale', StandardScaler())
                        ]))
        ])),
    ('clf', rg)
    ]
)

Therefore, as it is indicated I have 5 categorical features. Really, indices 123 to 160 are related to one categorical feature with 37 possible values which is converted into 37 columns using get_dummies.

I think SMOTENC should be inserted before the classifier ('clf', reg) but I don't know how to define "categorical_features" in SMOTENC. Besides, could you please let me know where to use imblearn.pipeline?

Thanks in advance.