chore: import upstream snapshot with attribution

2026-07-13 13:25:10 +08:00
commit c397331b1e
3684 changed files with 990993 additions and 0 deletions
@@ -0,0 +1,89 @@
+#!/usr/bin/env python3
+"""Batch ASR example for FunASR (improved)
+
+Features added:
+- argparse for command-line configuration
+- optional recursive folder scan
+- progress reporting with simple counts
+- safer model loading and per-file error handling
+- configurable output file and supported extensions
+- creates output folder if missing
+- configurable VAD model
+"""
+
+import argparse
+import sys
+from pathlib import Path
+from typing import List
+
+try:
+    from funasr import AutoModel
+    from funasr.utils.postprocess_utils import rich_transcription_postprocess
+except Exception as e:
+    print("Error importing funasr. Make sure FunASR is installed (pip install -U funasr) or you're running from the repo root.", file=sys.stderr)
+    raise
+
+def find_audio_files(folder: Path, exts: List[str], recursive: bool) -> List[Path]:
+    if recursive:
+        return [p for p in folder.rglob("*") if p.is_file() and p.suffix.lower() in exts]
+    else:
+        return [p for p in folder.iterdir() if p.is_file() and p.suffix.lower() in exts]
+
+def main():
+    parser = argparse.ArgumentParser(description="Batch ASR using FunASR AutoModel")
+    parser.add_argument("--input-folder", "-i", type=Path, default=Path("examples/audio_samples"),
+                        help="Folder with audio files (default: examples/audio_samples)")
+    parser.add_argument("--output-file", "-o", type=Path, default=Path("examples/batch_transcriptions.txt"),
+                        help="Output text file (default: examples/batch_transcriptions.txt)")
+    parser.add_argument("--model", "-m", default="paraformer-zh",
+                        help="Model name (default: paraformer-zh). Examples: paraformer-zh, paraformer-en, SenseVoiceSmall")
+    parser.add_argument("--device", "-d", default="cpu", help="Device for inference (default: cpu)")
+    parser.add_argument("--recursive", "-r", action="store_true", help="Recursively search input folder for audio files")
+    parser.add_argument("--extensions", "-e", nargs="+", default=[".wav", ".mp3"], help="Accepted audio extensions (default: .wav .mp3)")
+    parser.add_argument("--vad-model", default="fsmn-vad", help="VAD model to use. Set to 'none' to disable. (default: fsmn-vad)")
+    args = parser.parse_args()
+
+    if not args.input_folder.exists():
+        print(f"Input folder does not exist: {args.input_folder}", file=sys.stderr)
+        sys.exit(2)
+
+    exts = [ext.lower() if ext.startswith('.') else f'.{ext.lower()}' for ext in args.extensions]
+    files = sorted(find_audio_files(args.input_folder, exts, args.recursive))
+    if len(files) == 0:
+        print(f"No audio files found in {args.input_folder} with extensions {exts}")
+        sys.exit(0)
+
+    vad_arg = args.vad_model if args.vad_model.lower() != 'none' else None
+    print(f"Loading model '{args.model}' on device '{args.device}'... (this may take a while)")
+    try:
+        model = AutoModel(model=args.model, vad_model=vad_arg, device=args.device)
+    except Exception as e:
+        print("Failed to load model:", e, file=sys.stderr)
+        raise
+
+    results = {}
+    total = len(files)
+    for idx, fpath in enumerate(files, start=1):
+        rel_key = str(fpath.relative_to(args.input_folder))
+        try:
+            print(f"[{idx}/{total}] Processing: {fpath}")
+            # `cache` was removed per review because it's not used by generate
+            res = model.generate(input=str(fpath), language="auto")
+            text = rich_transcription_postprocess(res[0]["text"]) if res and isinstance(res, list) and "text" in res[0] else ""
+            results[rel_key] = text
+            print(f"  -> {text}")
+        except Exception as e:
+            print(f"  Error processing {fpath}: {e}", file=sys.stderr)
+            results[rel_key] = f"<ERROR: {e}>"
+
+    # Ensure output directory exists
+    args.output_file.parent.mkdir(parents=True, exist_ok=True)
+    with args.output_file.open("w", encoding="utf-8") as outf:
+        for fname, transcription in results.items():
+            outf.write(f"{fname}: {transcription}\n")
+
+    print(f"\nAll transcriptions saved to {args.output_file}")
+
+
+if __name__ == "__main__":
+    main()