| |
| """Egystormy Tools — portable local MuScriptor transcription pack. |
| |
| Usage: |
| runtime/python transcribe.py <input_audio> <output.mid> |
| |
| Fully offline and self-contained: the interpreter is ./runtime, all |
| third-party libraries live in ./libs, and the model weights in ./weights. |
| No Python installation, no setup, no network, no account. |
| |
| Design note — no beat detection, on purpose: this entry point uses |
| ``TranscriptionModel.transcribe`` + ``events_to_midi_bytes`` directly and |
| never calls the beat-grid path (``transcribe_and_postprocess`` / |
| ``detect_tempo``). MuScriptor's beat detection hard-imports |
| beat_this -> torchaudio at call time, and a mismatched torchaudio build |
| kills the whole transcription. Skipping it costs nothing that matters |
| here: note timings stay true (seconds-accurate); the MIDI simply carries |
| no tempo map. (In this pack torch is 2.15.0+cpu while the newest |
| torchaudio on the CPU index is 2.11.1+cpu — no matched 2.15 pair exists, |
| which is exactly the hazard avoided.) |
| """ |
|
|
| import os |
| import sys |
| import time |
| from pathlib import Path |
|
|
| PACK = Path(__file__).resolve().parent |
| sys.path.insert(0, str(PACK / "libs")) |
| |
| os.environ.setdefault("HF_HUB_OFFLINE", "1") |
| os.environ.setdefault("TRANSFORMERS_OFFLINE", "1") |
|
|
| T0 = time.perf_counter() |
|
|
|
|
| def stamp(label: str) -> None: |
| print(f"[pack] {label}: {time.perf_counter() - T0:.2f}s elapsed", flush=True) |
|
|
|
|
| def main() -> int: |
| if len(sys.argv) != 3: |
| print("usage: runtime/python transcribe.py <input_audio> <output.mid>", |
| file=sys.stderr) |
| return 2 |
| src = Path(sys.argv[1]) |
| dst = Path(sys.argv[2]) |
| weights = PACK / "weights" / "model.safetensors" |
| if not src.exists(): |
| print(f"input audio not found: {src}", file=sys.stderr) |
| return 2 |
| if not weights.exists(): |
| print(f"weights not found: {weights}", file=sys.stderr) |
| return 2 |
|
|
| from muscriptor import TranscriptionModel |
| from muscriptor.events import NoteStartEvent, ProgressEvent |
|
|
| stamp("imports done") |
|
|
| |
| |
| |
| audio_arg = src |
| tmp_wav = None |
| if src.suffix.lower() in {".m4a", ".aac", ".opus", ".wma"}: |
| import shutil |
| import subprocess |
| import tempfile |
|
|
| ffmpeg = shutil.which("ffmpeg") |
| if ffmpeg: |
| fd, tmp_wav = tempfile.mkstemp(suffix=".wav") |
| os.close(fd) |
| subprocess.run( |
| [ffmpeg, "-y", "-v", "error", "-i", str(src), tmp_wav], |
| check=True, |
| ) |
| audio_arg = Path(tmp_wav) |
|
|
| model = TranscriptionModel.load_model(weights_path=weights, device="cpu") |
| stamp("model loaded (cold start)") |
|
|
| t_transcribe = time.perf_counter() |
| events = [] |
| notes = 0 |
| for ev in model.transcribe(str(audio_arg)): |
| if isinstance(ev, ProgressEvent): |
| print(f"[pack] progress: chunk {ev.completed}/{ev.total}", flush=True) |
| else: |
| events.append(ev) |
| if isinstance(ev, NoteStartEvent): |
| notes += 1 |
|
|
| midi_bytes = model.events_to_midi_bytes(iter(events), beat_grid=None) |
| dst.parent.mkdir(parents=True, exist_ok=True) |
| dst.write_bytes(midi_bytes) |
| if tmp_wav: |
| os.unlink(tmp_wav) |
|
|
| print(f"[pack] transcribe wall time: {time.perf_counter() - t_transcribe:.2f}s", |
| flush=True) |
| print(f"DONE notes={notes} output={dst} bytes={len(midi_bytes)}", flush=True) |
| return 0 |
|
|
|
|
| if __name__ == "__main__": |
| raise SystemExit(main()) |
|
|
