Update app.py

app.py

@@ -1,10 +1,22 @@
 from flask import Flask, render_template, request
-from transformers import Text2ImagePipeline
+
+
+import torch
+from diffusers import DiffusionPipeline
+
+pipe = DiffusionPipeline.from_pretrained(
+    "cagliostrolab/animagine-xl-3.1", 
+    torch_dtype=torch.float16, 
+    use_safetensors=True, 
+)
+pipe.to('cpu')
+
+
+
 
 app = Flask(__name__)
 
-# Load the Hugging Face model for text-to-image generation
-text_to_image = Text2ImagePipeline(model="text2img")
+
 
 @app.route('/')
 def home():
@@ -17,11 +29,24 @@ def generate():
         text = request.form['text']
 
         # Generate image from text
-        image = text_to_image(text)
+        #image = text_to_image(text)
+        prompt = text
+        negative_prompt = "nsfw, lowres, (bad), text, error, fewer, extra, missing, worst quality, jpeg artifacts, low quality, watermark, unfinished, displeasing, oldest, early, chromatic aberration, signature, extra digits, artistic error, username, scan, [abstract]"
+
+        image = pipe(
+            prompt, 
+            negative_prompt=negative_prompt,
+            width=832,
+            height=1216, 
+            guidance_scale=7,
+            num_inference_steps=28
+        ).images[0]
+
+        image.save("./output/asuka_test.png")
 
         # Save the generated image (for simplicity, you can send it directly to the user)
         # You can save it to a temporary file or memory depending on your needs
-        image.save("static/generated_image.png")
+        #image.save("static/generated_image.png")
 
         return render_template('index.html', generated=True)