diff --git a/image_processing/build_dataset.py b/image_processing/build_dataset.py
index 3cb21651966a3b3d65f1937077c0a74d18971ea2..4c7456910c6a0253a6fbf6154dadd46e378d0e80 100644
--- a/image_processing/build_dataset.py
+++ b/image_processing/build_dataset.py
@@ -101,14 +101,13 @@ antibiotic_enterrobacter_breakpoints = {
 }
 
 
-def create_antibio_dataset(path='/data/label_raw/230804_strain_peptides_antibiogram_Enterobacterales.xlsx',suffix='-d200',base_path=None):
+def create_antibio_dataset(path='data/label_raw/230804_strain_peptides_antibiogram_Enterobacterales.xlsx',suffix='-d200',base_path=None):
     """
     Extract and build file name corresponding to each sample and transform antioresistance measurements to labels
     :param suffix: file suffix
     :param path: excel path
     :return: dataframe
     """
-    print('base path ', base_path, 'path : ',os.path.join(base_path,path))
     df = pd.read_excel(os.path.join(base_path,path), header=1)
     df = df[['sample_name','species','AMC (disk)','AMK (disk)','AMK (mic)','AMK (vitek)','AMP (vitek)','AMX (disk)',
     'AMX (vitek)','ATM (disk)','ATM (vitek)','CAZ (disk)','CAZ (mic)','CAZ (vitek)','CHL (vitek)','CIP (disk)',
@@ -180,8 +179,8 @@ def create_dataset(bin_mz=1,tolerance=0.005,noise=1000,apex='apex',suffix='-d200
             name = label[label['path_aer'] == path.split("/")[-1]]['sample_name'].values[0]
             analyse = 'AER'
         if species is not None: #save image in species specific dir
-            directory_path_png = os.path.join(base_path,'/data/processed_data_wiff_clean_{}_{}_{}_{}/png_image/{}'.format(tolerance_str,noise,apex,bin_mz,species))
-            directory_path_npy =  os.path.join(base_path,'/data/processed_data_wiff_clean_{}_{}_{}_{}/npy_image/{}'.format(tolerance_str,noise,apex,bin_mz,species))
+            directory_path_png = os.path.join(base_path,'data/processed_data_wiff_clean_{}_{}_{}_{}/png_image/{}'.format(tolerance_str,noise,apex,bin_mz,species))
+            directory_path_npy =  os.path.join(base_path,'data/processed_data_wiff_clean_{}_{}_{}_{}/npy_image/{}'.format(tolerance_str,noise,apex,bin_mz,species))
             if not os.path.isdir(directory_path_png):
                 os.makedirs(directory_path_png)
             if not os.path.isdir(directory_path_npy):