Append video name to output path when video_index is specified (#378)

## Summary
Fixes an issue where running inference with `video_index` on multiple
videos from the same .slp file would overwrite the output file. The
output path now includes the video name to create unique filenames for
each video.

## Problem
When running predictions on a multi-video .slp file using the
`video_index` parameter:
- All predictions would save to the same output path (e.g.,
`labels.predictions.slp`)
- Running inference on different videos would overwrite previous results
- Users had to manually specify unique `output_path` for each video

## Solution
When `video_index` is provided and `output_path` is None:
- Extract the video filename from `output.videos[video_index]`
- Append the video name (stem) to the output path
- Format: `<labels_file>.<video_name>.predictions.slp`
- Falls back to `video_{index}` if filename is not a simple string

## Example
**Before:**
```python
run_inference(data_path="labels.slp", video_index=0)  # → labels.predictions.slp
run_inference(data_path="labels.slp", video_index=1)  # → labels.predictions.slp (overwrites!)
```

**After:**
```python
run_inference(data_path="labels.slp", video_index=0)  # video1.mp4 → labels.video1.predictions.slp
run_inference(data_path="labels.slp", video_index=1)  # video2.mp4 → labels.video2.predictions.slp
```

## Changes
- Modified `run_inference()` in `sleap_nn/predict.py` to append video
name when `video_index` is specified
- Added `test_video_index_output_path()` test to verify the behavior

## Testing
- New test verifies video name is included in output path when using
video_index
- Existing tests continue to pass (no breaking changes)
- Behavior unchanged when video_index is None or output_path is
explicitly provided

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

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

---------

Co-authored-by: Claude <[email protected]>

Author: gitttt-1234

sleap_nn/predict.py

@@ -504,9 +504,23 @@ 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 +1423,41 @@ 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()