Update app.py

"디퓨전 모델로 도입"

app.py

@@ -1,24 +1,27 @@
 import streamlit as st
-import requests
+import torch
+from diffusers import StableDiffusionPipeline
 from PIL import Image
 import numpy as np
 import io
+import requests
 
-# Function to apply deepfake-like transformation using an API
+# Function to apply deepfake-like transformation using Stable Diffusion
 def apply_deepfake(image):
     # Convert PIL image to bytes
     image_bytes = io.BytesIO()
     image.save(image_bytes, format='JPEG')
     image_bytes = image_bytes.getvalue()
-
-    # Call the Hugging Face API
-    api_url = "https://api-inference.huggingface.co/models/spaces/dalle-mini/dalle-mini"
-    headers = {"Authorization": "Bearer YOUR_HUGGING_FACE_API_TOKEN"}
-    response = requests.post(api_url, headers=headers, files={"file": image_bytes})
-
-    # Convert response to image
-    response_image = Image.open(io.BytesIO(response.content))
-    return response_image
+    
+    # Initialize the Stable Diffusion pipeline
+    model_id = "CompVis/stable-diffusion-v1-4"
+    pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
+    pipe = pipe.to("cuda")
+
+    prompt = "A person with a different face but same pose and background"
+    
+    result = pipe(prompt, init_image=image, strength=0.75)
+    return result.images[0]
 
 st.title("Image Processing MVP")