Update app.py

app.py

@@ -1,53 +1,37 @@
-import io
 import gradio as gr
 import spaces
-from fastapi import FastAPI, File, UploadFile
-from fastapi.middleware.cors import CORSMiddleware
-from fastapi.responses import Response
 from transparent_background import Remover
 from PIL import Image
+import numpy as np
 
-# Inisialisasi remover SEKALI saat startup (akan otomatis detect GPU)
+# Inisialisasi model saat startup (akan otomatis pakai GPU di ZeroGPU)
 remover = Remover(mode='base')
 
-@spaces.GPU(duration=30)
-def remove_bg(img: Image.Image) -> Image.Image:
-    """Remove background menggunakan transparent-background (GPU accelerated)"""
-    return remover.process(img, type='rgba')
-
-# ---------- 1) UI GRADIO ----------
+@spaces.GPU(duration=60)  # Alokasi GPU selama 60 detik per request
+def remove_bg(img):
+    if img is None:
+        return None
+    
+    # transparent-background butuh format RGB
+    if isinstance(img, np.ndarray):
+        img = Image.fromarray(img)
+    
+    img_rgb = img.convert("RGB")
+    
+    # Proses hapus background (kembalikan PNG transparan)
+    output = remover.process(img_rgb, type='rgba')
+    return output
+
+# Buat Interface Gradio Murni
 demo = gr.Interface(
     fn=remove_bg,
     inputs=gr.Image(type="pil", label="Upload Gambar"),
     outputs=gr.Image(type="pil", label="Hasil (PNG Transparan)"),
     title="Remove Background API",
-    description="Backend remove background dengan GPU acceleration. REST API: POST /remove-bg",
-    examples=[],
-    cache_examples=False,
-)
-
-# ---------- 2) REST API FASTAPI (untuk frontend Vercel) ----------
-app = FastAPI()
-
-app.add_middleware(
-    CORSMiddleware,
-    allow_origins=["*"],
-    allow_methods=["*"],
-    allow_headers=["*"],
+    description="Backend untuk Vercel. Endpoint API: /api/remove_bg",
+    api_name="remove_bg"  # PENTING: Ini membuat endpoint API otomatis
 )
 
-@app.get("/health")
-def health():
-    return {"status": "online", "gpu_available": True}
-
-@app.post("/remove-bg")
-async def api_remove_bg(file: UploadFile = File(...)):
-    data = await file.read()
-    input_img = Image.open(io.BytesIO(data)).convert("RGB")
-    output_img = remove_bg(input_img)
-    buf = io.BytesIO()
-    output_img.save(buf, format="PNG")
-    return Response(content=buf.getvalue(), media_type="image/png")
-
-# Gabungkan Gradio UI + FastAPI
-app = gr.mount_gradio_app(app, demo, path="/")
+if __name__ == "__main__":
+    # Jangan pakai FastAPI, biarkan Gradio berjalan native
+    demo.launch()