Add lazy piano transcription and optional leased server worker

scripts/piano/Dockerfile

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+FROM python:3.10-slim
+ENV PYTHONUNBUFFERED=1 PIP_NO_CACHE_DIR=1 OMP_NUM_THREADS=2
+RUN apt-get update && apt-get install -y --no-install-recommends ffmpeg libsndfile1 wget && rm -rf /var/lib/apt/lists/*
+WORKDIR /app
+COPY requirements.txt .
+RUN pip install -r requirements.txt
+COPY worker.py .
+VOLUME ["/models"]
+CMD ["python", "worker.py"]

scripts/piano/requirements.txt

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+--extra-index-url https://download.pytorch.org/whl/cpu
+torch==2.5.1+cpu
+piano-transcription-inference==0.0.6
+numpy==1.23.5
+librosa==0.9.2
+numba==0.57.1
+scipy==1.10.1
+soundfile==0.12.1
+mido==1.3.3

scripts/piano/test_worker.py

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+import unittest
+from worker import compact
+
+
+class CompactNotesTest(unittest.TestCase):
+    def test_hand_split_and_velocity(self):
+        notes = compact([{'midi_note': 48, 'onset_time': 1.23456, 'offset_time': 1.78, 'velocity': 85}, {'midi_note': 60, 'onset_time': 2, 'offset_time': 3, 'velocity': 200}])
+        self.assertEqual(notes[0], {'pitch': 48, 'start': 1.235, 'end': 1.78, 'velocity': 85, 'hand': 'left'})
+        self.assertEqual(notes[1]['hand'], 'right')
+        self.assertEqual(notes[1]['velocity'], 127)
+
+    def test_empty_or_zero_duration(self):
+        self.assertEqual(compact([]), [])
+        self.assertEqual(compact([{'midi_note': 60, 'onset_time': 2, 'offset_time': 2, 'velocity': 85}]), [])
+
+
+if __name__ == '__main__':
+    unittest.main()

scripts/piano/worker.py

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+"""Optional CPU piano worker. Polls authenticated jobs; loads model on first job."""
+import json
+import os
+import re
+import tempfile
+import threading
+import time
+import urllib.request
+import urllib.error
+from pathlib import Path
+
+BASE = os.environ.get('YTP_BASE', 'http://ytplayer:3000').rstrip('/')
+TOKEN = os.environ.get('YTP_TOKEN', '')
+CHECKPOINT = Path(os.environ.get('PIANO_CHECKPOINT', '/models/piano.pth'))
+MODEL_URL = 'https://zenodo.org/record/4034264/files/CRNN_note_F1%3D0.9677_pedal_F1%3D0.9186.pth?download=1'
+ID = re.compile(r'^(?:[\w-]{11}|upl_[a-f0-9]{12})$')
+
+
+def api(path, body):
+    request = urllib.request.Request(BASE + path, data=json.dumps(body).encode(), headers={'Authorization': 'Bearer ' + TOKEN, 'Content-Type': 'application/json'})
+    with urllib.request.urlopen(request, timeout=45) as response:
+        return json.load(response)
+
+
+def compact(events):
+    return [{'pitch': int(event['midi_note']), 'start': round(float(event['onset_time']), 3),
+             'end': round(float(event['offset_time']), 3), 'velocity': max(1, min(127, int(event['velocity']))),
+             'hand': 'left' if int(event['midi_note']) < 60 else 'right'}
+            for event in events if event['offset_time'] > event['onset_time']]
+
+
+def download(url, destination, limit):
+    with urllib.request.urlopen(url, timeout=60) as response, open(destination, 'wb') as target:
+        size = 0
+        while True:
+            chunk = response.read(1024 * 1024)
+            if not chunk:
+                break
+            size += len(chunk)
+            if size > limit:
+                raise ValueError('Download exceeds worker limit')
+            target.write(chunk)
+
+
+def work(job, model):
+    video = job['videoId']
+    if not ID.fullmatch(video):
+        raise ValueError('Invalid job id')
+    path = '/api/uploads/' + video if video.startswith('upl_') else '/api/media/' + video + '?a=1'
+    if job['audioPath'] != path:
+        raise ValueError('Invalid audio path')
+    endpoint = '/api/piano-worker/' + video
+    stop = threading.Event()
+
+    def heartbeat():
+        while not stop.wait(30):
+            try:
+                api(endpoint, {'action': 'heartbeat', 'lease': job['lease']})
+            except Exception:
+                # Completion still checks the lease; an expired worker cannot publish.
+                pass
+
+    thread = threading.Thread(target=heartbeat, daemon=True)
+    thread.start()
+    try:
+        if model is None:
+            if not CHECKPOINT.exists() or CHECKPOINT.stat().st_size < 160000000:
+                CHECKPOINT.parent.mkdir(parents=True, exist_ok=True)
+                temporary = CHECKPOINT.with_suffix('.part')
+                download(MODEL_URL, temporary, 250000000)
+                if temporary.stat().st_size < 160000000:
+                    raise ValueError('Incomplete model checkpoint')
+                temporary.replace(CHECKPOINT)
+            import torch
+            from piano_transcription_inference import PianoTranscription
+            torch.set_num_threads(int(os.environ.get('PIANO_THREADS', '2')))
+            model = PianoTranscription(device='cpu', checkpoint_path=str(CHECKPOINT))
+        from piano_transcription_inference import load_audio, sample_rate
+        with tempfile.TemporaryDirectory() as folder:
+            media = Path(folder) / 'audio.bin'
+            try:
+                download(BASE + path, media, 100 * 1048576)
+            except urllib.error.HTTPError as error:
+                if error.code != 404 or video.startswith('upl_'):
+                    raise
+                download(BASE + path.split('?')[0], media, 100 * 1048576)
+            audio, _ = load_audio(str(media), sr=sample_rate, mono=True)
+            if len(audio) / sample_rate > 900:
+                raise ValueError('Worker audio is limited to 15 minutes')
+            result = model.transcribe(audio, None)
+            notes = compact(result['est_note_events'])
+            if len(notes) > 30000:
+                raise ValueError('Too many notes')
+            api(endpoint, {'action': 'complete', 'lease': job['lease'], 'notes': notes})
+        return model
+    except Exception as error:
+        api(endpoint, {'action': 'fail', 'lease': job['lease'], 'error': str(error)[:500]})
+        return model
+    finally:
+        stop.set()
+        thread.join(timeout=1)
+
+
+def main():
+    if len(TOKEN) < 24:
+        print('Piano worker disabled: configure a dedicated worker token.', flush=True)
+        while True:
+            time.sleep(300)
+    model = None
+    while True:
+        try:
+            job = api('/api/piano-worker/claim', {}).get('job')
+            if job:
+                model = work(job, model)
+            else:
+                time.sleep(10)
+        except Exception as error:
+            print('Piano worker: ' + str(error), flush=True)
+            time.sleep(15)
+
+
+if __name__ == '__main__':
+    main()