From 5841990b0df04906da7321beef6f7f7902b7d57b Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Sun, 9 Oct 2022 05:38:38 +0100
Subject: Update textual_inversion.py

---
 modules/textual_inversion/textual_inversion.py | 25 ++++++++++++++++++++++---
 1 file changed, 22 insertions(+), 3 deletions(-)

(limited to 'modules/textual_inversion/textual_inversion.py')

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index cd9f3498..f6316020 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -7,6 +7,9 @@ import tqdm
 import html
 import datetime
 
+from PIL import Image, PngImagePlugin
+import base64
+from io import BytesIO
 
 from modules import shared, devices, sd_hijack, processing, sd_models
 import modules.textual_inversion.dataset
@@ -80,7 +83,15 @@ class EmbeddingDatabase:
         def process_file(path, filename):
             name = os.path.splitext(filename)[0]
 
-            data = torch.load(path, map_location="cpu")
+            data = []
+
+            if filename.upper().endswith('.PNG'):
+                embed_image = Image.open(path)
+                if 'sd-embedding' in embed_image.text:
+                    embeddingData = base64.b64decode(embed_image.text['sd-embedding'])
+                    data = torch.load(BytesIO(embeddingData), map_location="cpu")
+            else:
+                data = torch.load(path, map_location="cpu")
 
             # textual inversion embeddings
             if 'string_to_param' in data:
@@ -156,7 +167,7 @@ def create_embedding(name, num_vectors_per_token, init_text='*'):
     return fn
 
 
-def train_embedding(embedding_name, learn_rate, data_root, log_directory, steps, create_image_every, save_embedding_every, template_file):
+def train_embedding(embedding_name, learn_rate, data_root, log_directory, steps, create_image_every, save_embedding_every, template_file, save_image_with_stored_embedding):
     assert embedding_name, 'embedding not selected'
 
     shared.state.textinfo = "Initializing textual inversion training..."
@@ -244,7 +255,15 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, steps,
             image = processed.images[0]
 
             shared.state.current_image = image
-            image.save(last_saved_image)
+
+            if save_image_with_stored_embedding:
+                info = PngImagePlugin.PngInfo()
+                info.add_text("sd-embedding", base64.b64encode(open(last_saved_file,'rb').read()))
+                image.save(last_saved_image, "PNG", pnginfo=info)
+            else:
+                image.save(last_saved_image)
+
+
 
             last_saved_image += f", prompt: {text}"
 
-- 
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