how to convert boolean column to 0 and 1 by using pd.get_dummies

I want to convert all boolean columns in my pandas dataframe into 0 and 1 by using pd.get_dummies. However, the boolean values stay the same after the get_dummies function.

For example:

tmp = pd.DataFrame([  
        ['green' , True],   
        ['red'   , False],   
        ['blue'  , True]]) 
tmp.columns = ['color',  'class'] 
pd.get_dummies(tmp)  
# I have also tried pd.get_dummies(tmp, dtype=int), but got the same output

I got:

   class  color_blue  color_green  color_red
0   True           0            1          0
1  False           0            0          1
2   True           1            0          0

but I need:

   color_blue  color_green  color_red  class_True  class_False
0           0            1          0        1        0
1           0            0          1        0        1
2           1            0          0        1        0

update:
My dataframe includes numeric data so convert all columns in the dataframe into string may not be the best soluion.

>Solution :

For processing boolean columns convert them to strings (here are converted all columns):

print (pd.get_dummies(tmp.astype(str)))
   color_blue  color_green  color_red  class_False  class_True
0           0            1          0            0           1
1           0            0          1            1           0
2           1            0          0            0           1

Of convert only boolean:

print (pd.get_dummies(tmp.astype({'class':'str'})))
   color_blue  color_green  color_red  class_False  class_True
0           0            1          0            0           1
1           0            0          1            1           0
2           1            0          0            0           1

You can create dictionary only for boolean columns:

d = dict.fromkeys(tmp.select_dtypes('bool').columns, 'str')
print (pd.get_dummies(tmp.astype(d)))