Merge branch 'master' into test_resolve_conflicts

1 files changed, 13 insertions, 4 deletions

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index f59b47a9..d2a389c9 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -88,9 +88,9 @@ class EmbeddingDatabase:
 

             data = []

 

-            if filename.upper().endswith('.PNG'):

+            if os.path.splitext(filename.upper())[-1] in ['.PNG', '.WEBP', '.JXL', '.AVIF']:

                 embed_image = Image.open(path)

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

+                if hasattr(embed_image, 'text') and 'sd-ti-embedding' in embed_image.text:

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

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

                 else:

@@ -242,6 +242,7 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc
 

     last_saved_file = "<none>"

     last_saved_image = "<none>"

+    embedding_yet_to_be_embedded = False

 

     ititial_step = embedding.step or 0

     if ititial_step > steps:

@@ -283,6 +284,7 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc
         if embedding.step > 0 and embedding_dir is not None and embedding.step % save_embedding_every == 0:

             last_saved_file = os.path.join(embedding_dir, f'{embedding_name}-{embedding.step}.pt')

             embedding.save(last_saved_file)

+            embedding_yet_to_be_embedded = True

 

         write_loss(log_directory, "textual_inversion_loss.csv", embedding.step, len(ds), {

             "loss": f"{losses.mean():.7f}",

@@ -320,7 +322,7 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc
 

             shared.state.current_image = image

 

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

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

 

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

 

@@ -329,15 +331,22 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc
                 info.add_text("sd-ti-embedding", embedding_to_b64(data))

 

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

+

+                try:

+                    vectorSize = list(data['string_to_param'].values())[0].shape[0]

+                except Exception as e:

+                    vectorSize = '?'

+

                 checkpoint = sd_models.select_checkpoint()

                 footer_left = checkpoint.model_name

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

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

+                footer_right = '{}v {}s'.format(vectorSize, 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.save(last_saved_image_chunks, "PNG", pnginfo=info)

+                embedding_yet_to_be_embedded = False

 

             image.save(last_saved_image)