Merge pull request kohya-ss#300 from bmaltais/dev

v21.1.3
wkpark · Mar 4, 2023 · d1b8af9 · d1b8af9
2 parents a1551fc + 3f45448
commit d1b8af9
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diff --git a/README-ja.md b/README-ja.md
@@ -38,6 +38,18 @@ PowerShellを使う場合、venvを使えるようにするためには以下の
 - 「Set-ExecutionPolicy Unrestricted」と入力し、Yと答えます。
 - 管理者のPowerShellを閉じます。
 
+## Ubuntu環境でのインストール
+
+```
+git clone https://github.com/kohya-ss/sd-scripts.git
+cd sd-scripts
+bash ubuntu_setup.sh
+```
+
+をコマンドプロンプトで実行し、tkをインストールし、accelerateの質問をWindowsと同じように答えます。
+
+`./gui.sh`でGUIを実行します。
+
 ## Windows環境でのインストール
 
 以下の例ではPyTorchは1.12.1／CUDA 11.6版をインストールします。CUDA 11.3版やPyTorch 1.13を使う場合は適宜書き換えください。

diff --git a/README.md b/README.md
@@ -41,6 +41,19 @@ If you run on Linux and would like to use the GUI, there is now a port of it as
 
 ## Installation
 
+### Ubuntu
+In the terminal, run
+
+```
+git clone https://github.com/bmaltais/kohya_ss.git
+cd kohya_ss
+bash ubuntu_setup.sh
+```
+
+then configure accelerate with the same answers as in the Windows instructions when prompted.
+
+### Windows
+
 Give unrestricted script access to powershell so venv can work:
 
 - Run PowerShell as an administrator
@@ -163,6 +176,9 @@ This will store your a backup file with your current locally installed pip packa
 
 ## Change History
 
+* 2023/03/04 (v21.1.3):
+    - Fix progress bar being displayed when not required.
+    - Add support for linux, thank you @devNegative-asm
 * 2023/03/03 (v21.1.2):
     - Fix issue https://github.com/bmaltais/kohya_ss/issues/277
     - Fix issue https://github.com/bmaltais/kohya_ss/issues/278 introduce by LoCon project switching to pip module. Make sure to run upgrade.ps1 to install the latest pip requirements for LoCon support.

diff --git a/dreambooth_gui.py b/dreambooth_gui.py
@@ -25,7 +25,7 @@
     gradio_config,
     gradio_source_model,
     set_legacy_8bitadam,
-    my_data,
+    update_my_data,
 )
 from library.tensorboard_gui import (
     gradio_tensorboard,
@@ -214,7 +214,7 @@ def open_configuration(
             my_data = json.load(f)
             print('Loading config...')
             # Update values to fix deprecated use_8bit_adam checkbox and set appropriate optimizer if it is set to True
-            my_data = my_data(my_data)
+            my_data = update_my_data(my_data)
     else:
         file_path = original_file_path  # In case a file_path was provided and the user decide to cancel the open action
         my_data = {}
@@ -456,7 +456,7 @@ def train_model(
 
     print(run_cmd)
     # Run the command
-    subprocess.run(run_cmd)
+    os.system(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}')
@@ -500,7 +500,9 @@ def dreambooth_tab(
                 '📂', elem_id='open_folder_small'
             )
             train_data_dir_input_folder.click(
-                get_folder_path, outputs=train_data_dir
+                get_folder_path,
+                outputs=train_data_dir,
+                show_progress=False,
             )
             reg_data_dir = gr.Textbox(
                 label='Regularisation folder',
@@ -510,7 +512,9 @@ def dreambooth_tab(
                 '📂', elem_id='open_folder_small'
             )
             reg_data_dir_input_folder.click(
-                get_folder_path, outputs=reg_data_dir
+                get_folder_path,
+                outputs=reg_data_dir,
+                show_progress=False,
             )
         with gr.Row():
             output_dir = gr.Textbox(
@@ -529,7 +533,9 @@ def dreambooth_tab(
                 '📂', elem_id='open_folder_small'
             )
             logging_dir_input_folder.click(
-                get_folder_path, outputs=logging_dir
+                get_folder_path,
+                outputs=logging_dir,
+                show_progress=False,
             )
         with gr.Row():
             output_name = gr.Textbox(
@@ -610,7 +616,11 @@ def dreambooth_tab(
                     placeholder='(Optiona) path to checkpoint of vae to replace for training',
                 )
                 vae_button = gr.Button('📂', elem_id='open_folder_small')
-                vae_button.click(get_any_file_path, outputs=vae)
+                vae_button.click(
+                    get_any_file_path,
+                    outputs=vae,
+                    show_progress=False,
+                )
             (
                 use_8bit_adam,
                 xformers,
@@ -664,10 +674,12 @@ def dreambooth_tab(
     button_start_tensorboard.click(
         start_tensorboard,
         inputs=logging_dir,
+        show_progress=False,
     )
 
     button_stop_tensorboard.click(
         stop_tensorboard,
+        show_progress=False,
     )
 
     settings_list = [
@@ -730,23 +742,27 @@ def dreambooth_tab(
         open_configuration,
         inputs=[config_file_name] + settings_list,
         outputs=[config_file_name] + settings_list,
+        show_progress=False,
     )
 
     button_save_config.click(
         save_configuration,
         inputs=[dummy_db_false, config_file_name] + settings_list,
         outputs=[config_file_name],
+        show_progress=False,
     )
 
     button_save_as_config.click(
         save_configuration,
         inputs=[dummy_db_true, config_file_name] + settings_list,
         outputs=[config_file_name],
+        show_progress=False,
     )
 
     button_run.click(
         train_model,
         inputs=settings_list,
+        show_progress=False,
     )
 
     return (

diff --git a/finetune_gui.py b/finetune_gui.py
@@ -19,7 +19,7 @@
     color_aug_changed,
     run_cmd_training,
     set_legacy_8bitadam,
-    my_data,
+    update_my_data,
 )
 from library.tensorboard_gui import (
     gradio_tensorboard,
@@ -33,6 +33,8 @@
 save_style_symbol = '\U0001f4be'  # 💾
 document_symbol = '\U0001F4C4'   # 📄
 
+PYTHON = 'python3' if os.name == 'posix' else './venv/Scripts/python.exe'
+
 
 def save_configuration(
     save_as,
@@ -216,7 +218,7 @@ def open_config_file(
             my_data_db = json.load(f)
             print('Loading config...')
             # Update values to fix deprecated use_8bit_adam checkbox and set appropriate optimizer if it is set to True
-            my_data = my_data(my_data)
+            my_data = update_my_data(my_data)
     else:
         file_path = original_file_path  # In case a file_path was provided and the user decide to cancel the open action
         my_data_db = {}
@@ -295,9 +297,7 @@ def train_model(
         if not os.path.exists(train_dir):
             os.mkdir(train_dir)
 
-        run_cmd = (
-            f'./venv/Scripts/python.exe finetune/merge_captions_to_metadata.py'
-        )
+        run_cmd = f'{PYTHON} finetune/merge_captions_to_metadata.py'
         if caption_extension == '':
             run_cmd += f' --caption_extension=".caption"'
         else:
@@ -310,13 +310,11 @@ def train_model(
         print(run_cmd)
 
         # Run the command
-        subprocess.run(run_cmd)
+        os.system(run_cmd)
 
     # create images buckets
     if generate_image_buckets:
-        run_cmd = (
-            f'./venv/Scripts/python.exe finetune/prepare_buckets_latents.py'
-        )
+        run_cmd = f'{PYTHON} finetune/prepare_buckets_latents.py'
         run_cmd += f' "{image_folder}"'
         run_cmd += f' "{train_dir}/{caption_metadata_filename}"'
         run_cmd += f' "{train_dir}/{latent_metadata_filename}"'
@@ -334,7 +332,7 @@ def train_model(
         print(run_cmd)
 
         # Run the command
-        subprocess.run(run_cmd)
+        os.system(run_cmd)
 
     image_num = len(
         [
@@ -444,7 +442,7 @@ def train_model(
 
     print(run_cmd)
     # Run the command
-    subprocess.run(run_cmd)
+    os.system(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}')
@@ -490,7 +488,11 @@ def finetune_tab():
             train_dir_folder = gr.Button(
                 folder_symbol, elem_id='open_folder_small'
             )
-            train_dir_folder.click(get_folder_path, outputs=train_dir)
+            train_dir_folder.click(
+                get_folder_path,
+                outputs=train_dir,
+                show_progress=False,
+            )
 
             image_folder = gr.Textbox(
                 label='Training Image folder',
@@ -500,7 +502,9 @@ def finetune_tab():
                 folder_symbol, elem_id='open_folder_small'
             )
             image_folder_input_folder.click(
-                get_folder_path, outputs=image_folder
+                get_folder_path,
+                outputs=image_folder,
+                show_progress=False,
             )
         with gr.Row():
             output_dir = gr.Textbox(
@@ -510,7 +514,11 @@ def finetune_tab():
             output_dir_input_folder = gr.Button(
                 folder_symbol, elem_id='open_folder_small'
             )
-            output_dir_input_folder.click(get_folder_path, outputs=output_dir)
+            output_dir_input_folder.click(
+                get_folder_path,
+                outputs=output_dir,
+                show_progress=False,
+            )
 
             logging_dir = gr.Textbox(
                 label='Logging folder',
@@ -520,7 +528,9 @@ def finetune_tab():
                 folder_symbol, elem_id='open_folder_small'
             )
             logging_dir_input_folder.click(
-                get_folder_path, outputs=logging_dir
+                get_folder_path,
+                outputs=logging_dir,
+                show_progress=False,
             )
         with gr.Row():
             output_name = gr.Textbox(
@@ -654,6 +664,7 @@ def finetune_tab():
 
     button_stop_tensorboard.click(
         stop_tensorboard,
+        show_progress=False,
     )
 
     settings_list = [
@@ -724,18 +735,21 @@ def finetune_tab():
         open_config_file,
         inputs=[config_file_name] + settings_list,
         outputs=[config_file_name] + settings_list,
+        show_progress=False,
     )
 
     button_save_config.click(
         save_configuration,
         inputs=[dummy_ft_false, config_file_name] + settings_list,
         outputs=[config_file_name],
+        show_progress=False,
     )
 
     button_save_as_config.click(
         save_configuration,
         inputs=[dummy_ft_true, config_file_name] + settings_list,
         outputs=[config_file_name],
+        show_progress=False,
     )
 
 

diff --git a/gui.sh b/gui.sh
@@ -0,0 +1,3 @@
+#!/bin/bash
+source venv/bin/activate
+python kohya_gui.py 
diff --git a/library/basic_caption_gui.py b/library/basic_caption_gui.py
@@ -2,6 +2,7 @@
 from easygui import msgbox
 import subprocess
 from .common_gui import get_folder_path, add_pre_postfix, find_replace
+import os
 
 
 def caption_images(
@@ -38,7 +39,7 @@ def caption_images(
         print(run_cmd)
 
         # Run the command
-        subprocess.run(run_cmd)
+        os.system(run_cmd)
 
     if overwrite_input:
         if not prefix == '' or not postfix == '':
@@ -85,7 +86,9 @@ def gradio_basic_caption_gui_tab():
                 '📂', elem_id='open_folder_small'
             )
             button_images_dir_input.click(
-                get_folder_path, outputs=images_dir_input
+                get_folder_path,
+                outputs=images_dir_input,
+                show_progress=False,
             )
             caption_file_ext = gr.Textbox(
                 label='Caption file extension',
@@ -139,4 +142,5 @@ def gradio_basic_caption_gui_tab():
                 find,
                 replace,
             ],
+            show_progress=False,
         )
diff --git a/library/blip_caption_gui.py b/library/blip_caption_gui.py
@@ -4,6 +4,8 @@
 import os
 from .common_gui import get_folder_path, add_pre_postfix
 
+PYTHON = 'python3' if os.name == 'posix' else './venv/Scripts/python.exe'
+
 
 def caption_images(
     train_data_dir,
@@ -32,7 +34,7 @@ def caption_images(
         return
 
     print(f'Captioning files in {train_data_dir}...')
-    run_cmd = f'.\\venv\\Scripts\\python.exe "finetune/make_captions.py"'
+    run_cmd = f'{PYTHON} "finetune/make_captions.py"'
     run_cmd += f' --batch_size="{int(batch_size)}"'
     run_cmd += f' --num_beams="{int(num_beams)}"'
     run_cmd += f' --top_p="{top_p}"'
@@ -48,7 +50,7 @@ def caption_images(
     print(run_cmd)
 
     # Run the command
-    subprocess.run(run_cmd)
+    os.system(run_cmd)
 
     # Add prefix and postfix
     add_pre_postfix(
@@ -81,7 +83,9 @@ def gradio_blip_caption_gui_tab():
                 '📂', elem_id='open_folder_small'
             )
             button_train_data_dir_input.click(
-                get_folder_path, outputs=train_data_dir
+                get_folder_path,
+                outputs=train_data_dir,
+                show_progress=False,
             )
         with gr.Row():
             caption_file_ext = gr.Textbox(
@@ -138,4 +142,5 @@ def gradio_blip_caption_gui_tab():
                 prefix,
                 postfix,
             ],
+            show_progress=False,
         )