UPDATE

app.py

@@ -3,7 +3,7 @@ from segment_anything import SamAutomaticMaskGenerator, sam_model_registry
 from transformers import AutoImageProcessor, AutoModel
 from huggingface_hub import snapshot_download
 from PIL import Image, ImageDraw
-import torch, numpy as np, cv2, zipfile, io, os
+import torch, numpy as np, cv2, zipfile, io, os, tempfile
 from sklearn.cluster import KMeans
 
 # -----------------------------------------------------
@@ -99,16 +99,17 @@ def segment_saree(image):
         # Transparent layers
         transparent_imgs = [Image.fromarray(make_transparent(l, l.any(axis=2))) for l in layers]
 
-        # ZIP all outputs
-        zip_buffer = io.BytesIO()
-        with zipfile.ZipFile(zip_buffer, "a", zipfile.ZIP_DEFLATED) as zf:
+        # Write ZIP to a temp file (Gradio expects a real path)
+        tmpdir = tempfile.mkdtemp()
+        zip_path = os.path.join(tmpdir, "saree_layers.zip")
+        with zipfile.ZipFile(zip_path, "w", zipfile.ZIP_DEFLATED) as zf:
             for n, t in zip(names, transparent_imgs):
-                bio = io.BytesIO()
-                t.save(bio, format="PNG")
-                zf.writestr(f"{n}.png", bio.getvalue())
-        zip_buffer.seek(0)
+                tmp_img = os.path.join(tmpdir, f"{n}.png")
+                t.save(tmp_img)
+                zf.write(tmp_img, arcname=f"{n}.png")
+
+        return seg_img, transparent_imgs[0], transparent_imgs[1], transparent_imgs[2], zip_path
 
-        return seg_img, transparent_imgs[0], transparent_imgs[1], transparent_imgs[2], zip_buffer
     except Exception as e:
         print("Error:", e)
         blank = Image.new("RGB", (512, 512), color=(30, 30, 30))
@@ -118,7 +119,7 @@ def segment_saree(image):
 # 4️⃣  Gradio UI
 # -----------------------------------------------------
 description = """
-### 🧵 Saree AI — Intelligent Segmentation & Layer Export  
+### 🧶 Saree AI — Intelligent Segmentation & Layer Export  
 Upload a **flat or draped saree image**, and this tool will:
 - ✂️ Remove background  
 - 🧠 Segment into **Body**, **Border**, **Pallu** using SAM + DINOv2  
@@ -138,9 +139,9 @@ demo = gr.Interface(
         gr.Image(type="pil", label="Pallu (Transparent)"),
         gr.File(label="📦 Download All (ZIP)"),
     ],
-    title="🧶 Saree AI — SAM + DINOv2 Smart Segmentation",
+    title="🧵 Saree AI — SAM + DINOv2 Smart Segmentation",
     description=description,
-    allow_flagging="never",
+    flagging_mode="never",
 )
 
 if __name__ == "__main__":