Merge pull request #2491 from bmaltais/dev

v24.1.4

.release

@@ -1 +1 @@
-v24.1.3
+v24.1.4

kohya_gui/common_gui.py

@@ -1424,12 +1424,11 @@ def validate_model_path(pretrained_model_name_or_path: str) -> bool:
         log.info(f"{msg} SUCCESS")
     else:
         # If not one of the default models, check if it's a valid local path
-        if not validate_file_path(pretrained_model_name_or_path):
+        if not validate_file_path(pretrained_model_name_or_path) and not validate_folder_path(pretrained_model_name_or_path):
+            log.info(f"{msg} FAILURE: not a valid file or folder")
             return False
-
     return True
 
-
 def is_file_writable(file_path: str) -> bool:
     """
     Checks if a file is writable.

kohya_gui/dreambooth_gui.py

@@ -536,7 +536,7 @@ def train_model(
     if not validate_folder_path(reg_data_dir):
         return TRAIN_BUTTON_VISIBLE
 
-    if not validate_file_path(resume):
+    if not validate_folder_path(resume):
         return TRAIN_BUTTON_VISIBLE
 
     if not validate_folder_path(train_data_dir):

kohya_gui/finetune_gui.py

@@ -578,7 +578,7 @@ def train_model(
     if not validate_model_path(pretrained_model_name_or_path):
         return TRAIN_BUTTON_VISIBLE
 
-    if not validate_file_path(resume):
+    if not validate_folder_path(resume):
         return TRAIN_BUTTON_VISIBLE
 
     #
@@ -628,8 +628,8 @@ def train_model(
                 run_cmd.append(caption_extension)
 
             # Add paths for the image folder and the caption metadata file
-            run_cmd.append(image_folder)
-            run_cmd.append(os.path.join(train_dir, caption_metadata_filename))
+            run_cmd.append(rf"{image_folder}")
+            run_cmd.append(rf"{os.path.join(train_dir, caption_metadata_filename)}")
 
             # Include the full path flag if specified
             if full_path:
@@ -641,16 +641,20 @@ def train_model(
             # Prepare environment variables
             env = setup_environment()
 
+            # Execute the command if not just for printing
+            if not print_only:
+                subprocess.run(run_cmd, env=env)
+
         # create images buckets
         if generate_image_buckets:
             # Build the command to run the preparation script
             run_cmd = [
                 PYTHON,
                 rf"{scriptdir}/sd-scripts/finetune/prepare_buckets_latents.py",
-                image_folder,
-                os.path.join(train_dir, caption_metadata_filename),
-                os.path.join(train_dir, latent_metadata_filename),
-                pretrained_model_name_or_path,
+                rf"{image_folder}",
+                rf"{os.path.join(train_dir, caption_metadata_filename)}",
+                rf"{os.path.join(train_dir, latent_metadata_filename)}",
+                rf"{pretrained_model_name_or_path}",
                 "--batch_size",
                 str(batch_size),
                 "--max_resolution",

kohya_gui/lora_gui.py

@@ -726,7 +726,7 @@ def train_model(
     if not validate_folder_path(reg_data_dir):
         return TRAIN_BUTTON_VISIBLE
 
-    if not validate_file_path(resume):
+    if not validate_folder_path(resume):
         return TRAIN_BUTTON_VISIBLE
 
     if not validate_folder_path(train_data_dir):

kohya_gui/textual_inversion_gui.py

@@ -536,7 +536,7 @@ def train_model(
     if not validate_folder_path(reg_data_dir):
         return TRAIN_BUTTON_VISIBLE
 
-    if not validate_file_path(resume):
+    if not validate_folder_path(resume):
         return TRAIN_BUTTON_VISIBLE
 
     if not validate_folder_path(train_data_dir):