Update app.py

app.py

@@ -1,32 +1,18 @@
-import streamlit as st
+import gradio as gr
+from transformers import pipeline
 from PIL import Image
-import requests
-from io import BytesIO
-import os
 
-# 환경 변수에서 API 토큰 불러오기
-api_token = os.getenv("HUGGINGFACE_API_TOKEN")
-if not api_token:
-    st.error("API token not found. Please set the HUGGINGFACE_API_TOKEN environment variable.")
+# AnimeGANv2 모델 로드
+model = pipeline("image-to-image", model="akhaliq/AnimeGANv2")
 
 def transform_image(image):
-    api_url = "https://api-inference.huggingface.co/models/akhaliq/AnimeGANv2"
-    headers = {"Authorization": f"Bearer {api_token}"}
+    result = model(image)
+    return result
 
-    buffered = BytesIO()
-    image.save(buffered, format="JPEG")
-    buffered.seek(0)
-    response = requests.post(api_url, headers=headers, files={"file": buffered})
+iface = gr.Interface(
+    fn=transform_image,
+    inputs=gr.inputs.Image(type="pil"),
+    outputs=gr.outputs.Image(type="pil")
+)
 
-    return Image.open(BytesIO(response.content))
-
-st.title("AnimeGANv2 Image Transformer")
-uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
-
-if uploaded_file is not None:
-    image = Image.open(uploaded_file)
-    st.image(image, caption='Uploaded Image.', use_column_width=True)
-    
-    if st.button("Transform"):
-        transformed_image = transform_image(image)
-        st.image(transformed_image, caption='Transformed Image.', use_column_width=True)
+iface.launch()