Added enhancement_VAE/enhance_audio_48k.py

enhancement_VAE/enhance_audio_48k.py

@@ -0,0 +1,58 @@
+#!/usr/bin/env python3
+# coding=utf-8
+# Copyright (c) 2026, NVIDIA CORPORATION.  All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""CLI launcher for Audex Enhancement VAE"""
+
+from __future__ import annotations
+
+import argparse
+from pathlib import Path
+
+import torch
+
+from enhancement_vae import DEFAULT_CHECKPOINT, DEFAULT_CONFIG, enhance_file, iter_input_files, load_model
+
+
+def parse_args() -> argparse.Namespace:
+    script_dir = Path(__file__).resolve().parent
+    parser = argparse.ArgumentParser(description="Enhance XCodec1-decoded 16 kHz WAVs to 48 kHz.")
+    parser.add_argument("--input", type=Path, required=True, help="Input audio file or directory.")
+    parser.add_argument("--output-dir", type=Path, required=True, help="Directory for enhanced 48 kHz WAVs.")
+    parser.add_argument("--device", type=str, default="cuda" if torch.cuda.is_available() else "cpu")
+    parser.add_argument("--seed", type=int, default=0, help="Torch seed for stochastic VAE sampling.")
+    parser.add_argument("--deterministic", action="store_true", help="Use posterior mean instead of VAE sampling.")
+    parser.set_defaults(
+        checkpoint=script_dir / DEFAULT_CHECKPOINT,
+        config=script_dir / DEFAULT_CONFIG,
+    )
+    return parser.parse_args()
+
+
+def main() -> None:
+    args = parse_args()
+    torch.manual_seed(args.seed)
+    device = torch.device(args.device)
+    model = load_model(checkpoint_path=args.checkpoint, config_path=args.config, device=device)
+    input_files = iter_input_files(args.input)
+    if not input_files:
+        raise ValueError(f"No audio files found in {args.input}")
+    for input_path in input_files:
+        output_path = args.output_dir / f"{input_path.stem}_enhanced_48k.wav"
+        enhance_file(model, input_path, output_path, deterministic=args.deterministic)
+        print(f"{input_path} -> {output_path}")
+
+
+if __name__ == "__main__":
+    main()