Root endpoint / returning API info

app.py

@@ -110,7 +110,7 @@ def _process_saree_core(base_image: Image.Image, pattern_image: Image.Image):
     pattern_folded = np.clip(pattern_folded, 0, 1)
 
     # ==========================================================
-    # NEW: Background removal using bgrem (instead of GrabCut)
+    # Background removal with post-processing (no duplicate blur)
     # ==========================================================
     buf = BytesIO()
     base_image.save(buf, format="PNG")
@@ -119,26 +119,19 @@ def _process_saree_core(base_image: Image.Image, pattern_image: Image.Image):
     # Get RGBA from bgrem
     result_no_bg = bgrem_remove(base_bytes)
     mask_img = Image.open(BytesIO(result_no_bg)).convert("RGBA")
-    
+
     # Extract alpha and clean edges
     mask_alpha = np.array(mask_img)[:, :, 3].astype(np.float32) / 255.0
-    
-    # --- NEW FIXES ---
-    # 1. Slightly shrink the mask to remove halos
+
+    # 1. Slightly shrink mask (erode)
     kernel = np.ones((3, 3), np.uint8)
     mask_binary = (mask_alpha > 0.05).astype(np.uint8) * 255
     mask_eroded = cv2.erode(mask_binary, kernel, iterations=1)
-    
-    # 2. Feather edges to smooth transition
-    mask_blurred = cv2.GaussianBlur(mask_eroded, (15, 15), sigmaX=3, sigmaY=3)
-    
-    # 3. Re-normalize
-    mask_blurred = mask_blurred.astype(np.float32) / 255.0
 
+    # 2. Feather edges (blur)
+    mask_blurred = cv2.GaussianBlur(mask_eroded, (15, 15), sigmaX=3, sigmaY=3)
 
-    # Feather edges for smoother blending
-    mask_blurred = cv2.GaussianBlur((mask_alpha * 255).astype(np.uint8), (15, 15), sigmaX=5, sigmaY=5)
-    mask_blurred[mask_blurred < 25] = 0
+    # 3. Normalize
     mask_blurred = mask_blurred.astype(np.float32) / 255.0
 
     # Final RGBA
@@ -189,6 +182,16 @@ gradio_iface = gr.Interface(
 
 app = FastAPI()
 
+# Root endpoint
+@app.get("/")
+async def root():
+    return JSONResponse(
+        content={
+            "message": "Saree Depth + Pattern Draping API",
+            "endpoints": ["/predict-saree", "/api/predict/", "/gradio"]
+        }
+    )
+
 # Mount Gradio at /gradio
 app = gr.mount_gradio_app(app, gradio_iface, path="/gradio")