use yield

app.py

@@ -509,8 +509,8 @@ def on_image_click(
 @spaces.GPU()
 def propagate_masks(GLOBAL_STATE: gr.State):
     if GLOBAL_STATE is None or GLOBAL_STATE.inference_session is None:
-        # yield GLOBAL_STATE, "Load a video first.", gr.update()
-        return GLOBAL_STATE, "Load a video first.", gr.update()
+        yield "Load a video first.", gr.update()
+        return
 
     processor = deepcopy(GLOBAL_STATE.processor)
     model = deepcopy(GLOBAL_STATE.model)
@@ -524,7 +524,7 @@ def propagate_masks(GLOBAL_STATE: gr.State):
     processed = 0
 
     # Initial status; no slider change yet
-    # yield GLOBAL_STATE, f"Propagating masks: {processed}/{total}", gr.update()
+    yield f"Propagating masks: {processed}/{total}", gr.update()
 
     last_frame_idx = 0
     with torch.inference_mode():
@@ -547,16 +547,15 @@ def propagate_masks(GLOBAL_STATE: gr.State):
 
             processed += 1
             # Every 15th frame (or last), move slider to current frame to update preview via slider binding
-            # if processed % 15 == 0 or processed == total:
-            #     yield GLOBAL_STATE, f"Propagating masks: {processed}/{total}", gr.update(value=frame_idx)
-            # else:
-            #     yield GLOBAL_STATE, f"Propagating masks: {processed}/{total}", gr.update()
+            if processed % 15 == 0 or processed == total:
+                yield f"Propagating masks: {processed}/{total}", gr.update(value=frame_idx)
+            else:
+                yield f"Propagating masks: {processed}/{total}", gr.update()
 
     text = f"Propagated masks across {processed} frames for {len(inference_session.obj_ids)} objects."
 
     # Final status; ensure slider points to last processed frame
-    # yield GLOBAL_STATE, text, gr.update(value=last_frame_idx)
-    return GLOBAL_STATE, text, gr.update(value=last_frame_idx)
+    yield text, gr.update(value=last_frame_idx)
 
 
 def reset_session(GLOBAL_STATE: gr.State) -> tuple[AppState, Image.Image, int, int, str]:
@@ -812,7 +811,7 @@ with gr.Blocks(title="SAM2 Video (Transformers) - Interactive Segmentation", the
     propagate_btn.click(
         propagate_masks,
         inputs=[GLOBAL_STATE],
-        outputs=[GLOBAL_STATE, propagate_status, frame_slider],
+        outputs=[propagate_status, frame_slider],
     )
 
     reset_btn.click(