Merge pull request #309 from bmaltais/dev

Change how subprocess is run

dreambooth_gui.py

@@ -455,8 +455,12 @@ def train_model(
     )
 
     print(run_cmd)
+    
     # Run the command
-    os.system(run_cmd)
+    if os.name == 'posix':
+        os.system(run_cmd)
+    else:
+        subprocess.run(run_cmd)
 
     # check if output_dir/last is a folder... therefore it is a diffuser model
     last_dir = pathlib.Path(f'{output_dir}/{output_name}')

finetune_gui.py

@@ -310,7 +310,10 @@ def train_model(
         print(run_cmd)
 
         # Run the command
-        os.system(run_cmd)
+        if os.name == 'posix':
+            os.system(run_cmd)
+        else:
+            subprocess.run(run_cmd)
 
     # create images buckets
     if generate_image_buckets:
@@ -332,7 +335,10 @@ def train_model(
         print(run_cmd)
 
         # Run the command
-        os.system(run_cmd)
+        if os.name == 'posix':
+            os.system(run_cmd)
+        else:
+            subprocess.run(run_cmd)
 
     image_num = len(
         [
@@ -441,8 +447,12 @@ def train_model(
     )
 
     print(run_cmd)
+    
     # Run the command
-    os.system(run_cmd)
+    if os.name == 'posix':
+        os.system(run_cmd)
+    else:
+        subprocess.run(run_cmd)
 
     # check if output_dir/last is a folder... therefore it is a diffuser model
     last_dir = pathlib.Path(f'{output_dir}/{output_name}')

library/basic_caption_gui.py

@@ -39,7 +39,10 @@ def caption_images(
         print(run_cmd)
 
         # Run the command
-        os.system(run_cmd)
+        if os.name == 'posix':
+            os.system(run_cmd)
+        else:
+            subprocess.run(run_cmd)
 
     if overwrite_input:
         if not prefix == '' or not postfix == '':

library/blip_caption_gui.py

@@ -50,7 +50,10 @@ def caption_images(
     print(run_cmd)
 
     # Run the command
-    os.system(run_cmd)
+    if os.name == 'posix':
+        os.system(run_cmd)
+    else:
+        subprocess.run(run_cmd)
 
     # Add prefix and postfix
     add_pre_postfix(

library/convert_model_gui.py

@@ -88,7 +88,10 @@ def convert_model(
     print(run_cmd)
 
     # Run the command
-    os.system(run_cmd)
+    if os.name == 'posix':
+        os.system(run_cmd)
+    else:
+        subprocess.run(run_cmd)
 
     if (
         not target_model_type == 'diffuser'

library/extract_lora_gui.py

@@ -55,7 +55,10 @@ def extract_lora(
     print(run_cmd)
 
     # Run the command
-    os.system(run_cmd)
+    if os.name == 'posix':
+        os.system(run_cmd)
+    else:
+        subprocess.run(run_cmd)
 
 
 ###

library/merge_lora_gui.py

@@ -54,7 +54,10 @@ def merge_lora(
     print(run_cmd)
 
     # Run the command
-    os.system(run_cmd)
+    if os.name == 'posix':
+        os.system(run_cmd)
+    else:
+        subprocess.run(run_cmd)
 
 
 ###

library/resize_lora_gui.py

@@ -41,7 +41,10 @@ def resize_lora(
     print(run_cmd)
 
     # Run the command
-    os.system(run_cmd)
+    if os.name == 'posix':
+        os.system(run_cmd)
+    else:
+        subprocess.run(run_cmd)
 
 
 ###

library/wd14_caption_gui.py

@@ -31,7 +31,10 @@ def caption_images(train_data_dir, caption_extension, batch_size, thresh):
     print(run_cmd)
 
     # Run the command
-    os.system(run_cmd)
+    if os.name == 'posix':
+        os.system(run_cmd)
+    else:
+        subprocess.run(run_cmd)
 
     print('...captioning done')
 

lora_gui.py

@@ -545,8 +545,12 @@ def train_model(
     )
 
     print(run_cmd)
+    
     # Run the command
-    os.system(run_cmd)
+    if os.name == 'posix':
+        os.system(run_cmd)
+    else:
+        subprocess.run(run_cmd)
 
     # check if output_dir/last is a folder... therefore it is a diffuser model
     last_dir = pathlib.Path(f'{output_dir}/{output_name}')

textual_inversion_gui.py

@@ -497,8 +497,12 @@ def train_model(
         run_cmd += f' --use_style_template'
 
     print(run_cmd)
+    
     # Run the command
-    os.system(run_cmd)
+    if os.name == 'posix':
+        os.system(run_cmd)
+    else:
+        subprocess.run(run_cmd)
 
     # check if output_dir/last is a folder... therefore it is a diffuser model
     last_dir = pathlib.Path(f'{output_dir}/{output_name}')