Append video name to output path when video_index is specified

When running inference with video_index parameter to predict on a specific
video from a multi-video .slp file, the output path now includes the video
name to prevent overwrites. This allows users to run predictions on multiple
videos from the same .slp file without manually specifying output paths.

Changes:
- Modified run_inference() to append video filename stem to output path
  when video_index is provided and output_path is None
- Format: <labels_file>.<video_name>.predictions.slp
- Falls back to video_{index} if filename is not a simple string
- Added test_video_index_output_path() to verify behavior

Example:
- Before: labels.slp + video_index=0 → labels.predictions.slp
- After:  labels.slp + video_index=0 (video1.mp4) → labels.video1.predictions.slp

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <[email protected]>

Author: gitttt-1234

sleap_nn/predict.py

@@ -504,9 +504,17 @@ def run_inference(
 
     if make_labels:
         if output_path is None:
-            output_path = Path(
-                data_path if data_path is not None else "results"
-            ).with_suffix(".predictions.slp")
+            base_path = Path(data_path if data_path is not None else "results")
+
+            # If video_index is specified, append video name to output path
+            if video_index is not None and len(output.videos) > video_index:
+                video = output.videos[video_index]
+                # Get video filename and sanitize it for use in path
+                video_name = Path(video.filename).stem if isinstance(video.filename, str) else f"video_{video_index}"
+                # Insert video name before .predictions.slp extension
+                output_path = base_path.parent / f"{base_path.stem}.{video_name}.predictions.slp"
+            else:
+                output_path = base_path.with_suffix(".predictions.slp")
         output.save(Path(output_path).as_posix(), restore_original_videos=False)
     finish_timestamp = str(datetime.now())
     logger.info(f"Predictions output path: {output_path}")

tests/test_predict.py

@@ -1423,3 +1423,39 @@ def test_topdown_predictor_with_tracking_cleaning(
         device="cpu" if torch.backends.mps.is_available() else "auto",
     )
     assert len(labels) < 10
+
+
+def test_video_index_output_path(
+    minimal_instance,
+    minimal_instance_centered_instance_ckpt,
+    minimal_instance_centroid_ckpt,
+    tmp_path,
+):
+    """Test that video_index appends video name to output path."""
+    # Run inference with video_index and no explicit output_path
+    labels = run_inference(
+        model_paths=[
+            minimal_instance_centroid_ckpt,
+            minimal_instance_centered_instance_ckpt,
+        ],
+        data_path=minimal_instance.as_posix(),
+        video_index=0,
+        make_labels=True,
+        device="cpu",
+        peak_threshold=0.0,
+        integral_refinement=None,
+    )
+
+    # Check that output file was created with video name in path
+    expected_pattern = f"*minimal_instance*.predictions.slp"
+    output_files = list(Path(minimal_instance).parent.glob(expected_pattern))
+    assert len(output_files) > 0, "No output file found with video name in path"
+
+    # The output file should contain the video name
+    output_file = output_files[0]
+    video_name = Path(labels.videos[0].filename).stem
+    assert video_name in output_file.stem, f"Video name '{video_name}' not found in output path '{output_file}'"
+
+    # Clean up
+    for f in output_files:
+        f.unlink()