Update app.py

app.py

@@ -2,16 +2,11 @@ import gradio as gr
 from diffusers import StableDiffusionImg2ImgPipeline
 import torch
 from PIL import Image
-import base64
-import io
-
-MODEL_ID = "runwayml/stable-diffusion-v1-5"
 
 pipe = StableDiffusionImg2ImgPipeline.from_pretrained(
-    MODEL_ID,
+    "hf-internal-testing/tiny-stable-diffusion-pipe",
     torch_dtype=torch.float32
 )
-pipe.enable_attention_slicing()
 
 def generate(image, prompt):
     if image is None:
@@ -19,8 +14,8 @@ def generate(image, prompt):
 
     img = image.convert("RGB").resize((512, 512))
 
-    full_prompt = f"interior design, {prompt}, photorealistic, high quality, 8k, professional photography"
-    negative_prompt = "ugly, blurry, bad quality, distorted, deformed, low resolution"
+    full_prompt = f"interior design, {prompt}, photorealistic, high quality"
+    negative_prompt = "ugly, blurry, bad quality, distorted"
 
     result = pipe(
         prompt=full_prompt,
@@ -28,7 +23,7 @@ def generate(image, prompt):
         image=img,
         strength=0.75,
         guidance_scale=7.5,
-        num_inference_steps=25,
+        num_inference_steps=8,
     ).images[0]
 
     return result
@@ -37,11 +32,10 @@ demo = gr.Interface(
     fn=generate,
     inputs=[
         gr.Image(type="pil", label="Leeg interieur render"),
-        gr.Textbox(label="Stijl omschrijving", placeholder="bijv: Scandinavisch minimalistisch, warme tinten, houten vloer")
+        gr.Textbox(label="Stijl omschrijving")
     ],
     outputs=gr.Image(type="pil", label="Resultaat"),
-    title="Interior AI",
-    description="Upload een leeg render en beschrijf de gewenste stijl."
+    title="Interior AI"
 )
 
 if __name__ == "__main__":