Create model and log folder when running th dreambooth folder creation utility

README.md

@@ -1,8 +1,8 @@
 # Kohya's dreambooth and finetuning
 
-This repo now combine bot Kohya_ss solution under one roof. I am merging both under a single repo to align with the new official kohya repo where he will maintain his code from now on: https://github.com/kohya-ss/sd-scripts
+This repository now includes the solutions provided by Kohya_ss in a single location. I have combined both solutions under one repository to align with the new official Kohya repository where he will maintain his code from now on: https://github.com/kohya-ss/sd-scripts.
 
-A new note accompaning the release of his new repo can be found here: https://note.com/kohya_ss/n/nba4eceaa4594
+A note accompanying the release of his new repository can be found here: https://note.com/kohya_ss/n/nba4eceaa4594
 
 ## Dreambooth
 

README_dreambooth.md

@@ -139,6 +139,8 @@ Drop by the discord server for support: https://discord.com/channels/10415185624
 
 ## Change history
 
+* 12/19 (v18.5) update:
+    - Create model and log folder when running th dreambooth folder creation utility
 * 12/19 (v18.4) update:
     - Add support for shuffle_caption, save_state, resume, prior_loss_weight under "Advanced Configuration" section
     - Fix issue with open/save config not working properly

library/dreambooth_folder_creation_gui.py

@@ -95,6 +95,15 @@ def dreambooth_folder_preparation(
             util_regularization_images_dir_input, regularization_dir
         )
 
+    # create log and model folder
+    # Check if the log folder exists and create it if it doesn't
+    if not os.path.exists(os.path.join(util_training_dir_output, 'log')):
+        os.makedirs(os.path.join(util_training_dir_output, 'log'))
+
+    # Check if the model folder exists and create it if it doesn't
+    if not os.path.exists(os.path.join(util_training_dir_output, 'model')):
+        os.makedirs(os.path.join(util_training_dir_output, 'model'))
+
     print(
         f'Done creating kohya_ss training folder structure at {util_training_dir_output}...'
     )