Update app.py

app.py

@@ -76,7 +76,7 @@ def embed(pil_img):
     processed_inputs = proc(images=clean_image, return_tensors="pt")
     with torch.no_grad():
         feats = model.get_image_features(**processed_inputs)
-    user_vector = feats.squeeze().cpu().numpy()
+    user_vector = feats.pooler_output.squeeze().cpu().numpy()
     return normalize(user_vector.reshape(1, -1))[0]
 
 def recommend(query_image):
@@ -115,10 +115,9 @@ def recommend(query_image):
         emj      = ACTION_EMOJI.get(label, "")
         real_idx = DS_INDICES[int(idx)]
         try:
-           img = ds[int(real_idx)]["image"].convert("RGB")
-        except Exception as e:
-           print(f"Warning: could not load image at index {real_idx}: {e}")
-           img = Image.new("RGB", (120,120), (60,60,60))
+            img = ds[int(real_idx)]["image"].convert("RGB")
+        except:
+            img = Image.new("RGB", (120,120), (60,60,60))
         gallery.append((img, f"#{rank} {emj} {label.replace('_',' ')} · {score:.4f}"))
         pct = min(int(score * 100), 100)
         bars += f"""
@@ -221,6 +220,4 @@ with gr.Blocks(title="Human Action Recommender") as demo:
     </div>""")
 
 if __name__ == "__main__":
-    demo.launch(server_name="0.0.0.0", server_port=7860)
-
-    
+    demo.launch()