formatting

1 files changed, 11 insertions, 11 deletions

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 485ef46c..b072d745 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -7,14 +7,14 @@ import tqdm
 import html

 import datetime

 

-from PIL import Image,PngImagePlugin

+from PIL import Image, PngImagePlugin

 

 from modules import shared, devices, sd_hijack, processing, sd_models

 import modules.textual_inversion.dataset

 

-from modules.textual_inversion.image_embedding import (embedding_to_b64,embedding_from_b64,

-                                                       insert_image_data_embed,extract_image_data_embed,

-                                                       caption_image_overlay )

+from modules.textual_inversion.image_embedding import (embedding_to_b64, embedding_from_b64,

+                                                       insert_image_data_embed, extract_image_data_embed,

+                                                       caption_image_overlay)

 

 class Embedding:

     def __init__(self, vec, name, step=None):

@@ -90,10 +90,10 @@ class EmbeddingDatabase:
                 embed_image = Image.open(path)

                 if 'sd-ti-embedding' in embed_image.text:

                     data = embedding_from_b64(embed_image.text['sd-ti-embedding'])

-                    name = data.get('name',name)

+                    name = data.get('name', name)

                 else:

                     data = extract_image_data_embed(embed_image)

-                    name = data.get('name',name)

+                    name = data.get('name', name)

             else:

                 data = torch.load(path, map_location="cpu")

 

@@ -278,24 +278,24 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
             shared.state.current_image = image

 

             if save_image_with_stored_embedding and os.path.exists(last_saved_file):

-                

+

                 last_saved_image_chunks = os.path.join(images_embeds_dir, f'{embedding_name}-{embedding.step}.png')

 

                 info = PngImagePlugin.PngInfo()

                 data = torch.load(last_saved_file)

                 info.add_text("sd-ti-embedding", embedding_to_b64(data))

 

-                title = "<{}>".format(data.get('name','???'))

+                title = "<{}>".format(data.get('name', '???'))

                 checkpoint = sd_models.select_checkpoint()

                 footer_left = checkpoint.model_name

                 footer_mid = '[{}]'.format(checkpoint.hash)

                 footer_right = '{}'.format(embedding.step)

 

-                captioned_image = caption_image_overlay(image,title,footer_left,footer_mid,footer_right)

-                captioned_image = insert_image_data_embed(captioned_image,data)

+                captioned_image = caption_image_overlay(image, title, footer_left, footer_mid, footer_right)

+                captioned_image = insert_image_data_embed(captioned_image, data)

 

                 captioned_image.save(last_saved_image_chunks, "PNG", pnginfo=info)

-            

+

             image.save(last_saved_image)

 

             last_saved_image += f", prompt: {preview_text}"