fix app

app.py

@@ -368,9 +368,9 @@ def process_single_video(
 
         # Build payload and send to server
         files, sample_data = build_payload([progress_sample])
-        # Add use_frame_steps flag to sample_data
-        sample_data["use_frame_steps"] = use_frame_steps
-        response = post_batch_npy(server_url, files, sample_data, timeout_s=120.0)
+        # Add use_frame_steps flag as extra form data
+        extra_data = {"use_frame_steps": use_frame_steps} if use_frame_steps else None
+        response = post_batch_npy(server_url, files, sample_data, timeout_s=120.0, extra_form_data=extra_data)
 
         # Process response
         outputs_progress = response.get("outputs_progress", {})
@@ -431,7 +431,6 @@ def process_two_videos(
     prediction_type: str = "preference",
     server_url: str = "",
     fps: float = 1.0,
-    use_frame_steps: bool = False,
 ) -> Tuple[Optional[str], Optional[str], Optional[str]]:
     """Process two videos for preference, similarity, or progress prediction using eval server."""
     # Get server URL from state if not provided
@@ -529,8 +528,6 @@ def process_two_videos(
 
             # Build payload and send to server
             files, sample_data = build_payload([progress_sample_a, progress_sample_b])
-            # Add use_frame_steps flag to sample_data
-            sample_data["use_frame_steps"] = use_frame_steps
             response = post_batch_npy(server_url, files, sample_data, timeout_s=120.0)
 
             # Process response
@@ -1048,12 +1045,6 @@ with demo:
                         step=0.1,
                         info="Frames per second to extract from videos (higher = more frames)",
                     )
-                    use_frame_steps_dual = gr.Checkbox(
-                        label="Use Frame Steps",
-                        value=False,
-                        info="Process frames incrementally for progress predictions",
-                        visible=False,  # Only visible for progress mode
-                    )
                     analyze_dual_btn = gr.Button("Compare Videos", variant="primary")
 
                     gr.Markdown("---")
@@ -1121,17 +1112,6 @@ with demo:
             current_dataset_a = gr.State(None)
             current_dataset_b = gr.State(None)
 
-            # Show/hide frame steps checkbox based on prediction type
-            def update_frame_steps_visibility(pred_type):
-                """Show frame steps checkbox only for progress mode."""
-                return gr.update(visible=(pred_type == "progress"))
-
-            prediction_type.change(
-                fn=update_frame_steps_visibility,
-                inputs=[prediction_type],
-                outputs=[use_frame_steps_dual],
-            )
-
             # Helper functions for Video A
             def update_config_choices_a(dataset_name):
                 """Update config choices for Video A when dataset changes."""
@@ -1521,7 +1501,6 @@ with demo:
                     prediction_type,
                     server_url_state,
                     fps_input_dual,
-                    use_frame_steps_dual,
                 ],
                 outputs=[result_text, video_a_display, video_b_display],
                 api_name="process_two_videos",

eval_utils.py

@@ -280,11 +280,28 @@ def post_batch(url: str, payload: dict[str, Any], timeout_s: float = 120.0) -> d
 
 
 def post_batch_npy(
-    url: str, files: dict[str, Any], sample_data: list[dict[str, Any]], timeout_s: float = 120.0
+    url: str,
+    files: dict[str, Any],
+    sample_data: list[dict[str, Any]],
+    timeout_s: float = 120.0,
+    extra_form_data: Optional[dict[str, Any]] = None,
 ) -> dict[str, Any]:
-    """POST batch using .npy format for numpy arrays."""
+    """POST batch using .npy format for numpy arrays.
+    
+    Args:
+        url: Server URL
+        files: Dict of numpy arrays converted to .npy format
+        sample_data: List of sample dictionaries
+        timeout_s: Request timeout in seconds
+        extra_form_data: Optional extra form data to include (e.g., use_frame_steps)
+    """
     # Convert sample_data to form data
     data = {f"sample_{i}": json.dumps(sample) for i, sample in enumerate(sample_data)}
+    
+    # Add extra form data if provided
+    if extra_form_data:
+        for key, value in extra_form_data.items():
+            data[key] = json.dumps(value) if not isinstance(value, str) else value
 
     # Send as multipart form data
     resp = requests.post(url.rstrip("/") + "/evaluate_batch_npy", files=files, data=data, timeout=timeout_s)