gradio_app

_viz/viz_template.html

@@ -755,9 +755,9 @@
             pointSize: 0.03,
             pointOpacity: 1.0,
             showTrajectory: true,
-            trajectoryLineWidth: 1.5,
-            trajectoryBallSize: 0.005,
-            trajectoryHistory: 30,
+            trajectoryLineWidth: 2.5,
+            trajectoryBallSize: 0.015,
+            trajectoryHistory: 0,
             showCameraFrustum: true,
             frustumSize: 0.2
           };
@@ -805,9 +805,9 @@
             pointSize: 0.03,
             pointOpacity: 1.0,
             showTrajectory: true,
-            trajectoryLineWidth: 1.5,
-            trajectoryBallSize: 0.02,
-            trajectoryHistory: 30,
+            trajectoryLineWidth: 2.5,
+            trajectoryBallSize: 0.015,
+            trajectoryHistory: 0,
             showCameraFrustum: true,
             frustumSize: 0.2
           };

app.py

@@ -164,6 +164,7 @@ def gpu_run_tracker(tracker_model_arg, tracker_viser_arg, temp_dir, video_name,
         mask = mask.sum(axis=-1)>0
     else:
         mask = np.ones_like(video_tensor[0,0].cpu().numpy())>0
+        grid_size = 10
     
     # Get frame dimensions and create grid points
     frame_H, frame_W = video_tensor.shape[2:]
@@ -177,7 +178,6 @@ def gpu_run_tracker(tracker_model_arg, tracker_viser_arg, temp_dir, video_name,
     
     query_xyt = torch.cat([torch.zeros_like(grid_pts[:, :, :1]), grid_pts], dim=2)[0].cpu().numpy()
     print(f"Query points shape: {query_xyt.shape}")
-
     # Run model inference
     with torch.amp.autocast(device_type="cuda", dtype=torch.bfloat16):
         (
@@ -571,7 +571,7 @@ def launch_viz(grid_size, vo_points, fps, original_image_state):
     
     mask_files = glob.glob(os.path.join(temp_dir, "*.png"))
     if not mask_files:
-        return None, None
+        mask_files = [None]
         
     video_files = glob.glob(os.path.join(temp_dir, "*.mp4"))
     if not video_files: