How cb-42/annoteator works
AnNOTEators is a drum-audio transcription project: users provide a local recording or YouTube link and receive drum notation, optionally as PDF. The CLI coordinates downloading, drum separation, onset framing, neural drum-hit prediction, and notation generation; the README also documents notebook use and custom model development. The graph includes the documented training-data preparation and augmentation branch. Edges reflect calls visible in excerpts or README workflow statements; unsampled internals are not inferred.
Main entry points: main.py CLI workflow · data_preparation.py Data preparation · prediction.py Drum-hit prediction · input_transform.py Drum separation
Components 16
Transcription workflow
- CLI workflow
main.py - Audio download
inference/input_transform.py - Drum separation
inference/input_transform.py - Onset framing
inference/input_transform.py - Drum-hit prediction
inference/prediction.py - Pretrained networks
inference/pretrained_models - Notation generation
inference/transcriber.py
Model development
- E-GMD dataset
dataset/e-gmd-v1.0.0/e-gmd-v1.0.0 - Data preparation
model_development/data_preparation.py - Audio augmentation
model_development/augment_audio.py
Other components
- Musician
- YouTube source
- Audio file
- Drum sheet music
- Data scientist
- Prepared training data
Connections 19
- Musician → CLI workflow: provides input
README.md - CLI workflow → Audio download: downloads link
main.py - YouTube source → Audio download: supplies audio
README.md - CLI workflow → Audio file: uses local file
main.py - CLI workflow → Drum separation: calls
main.py - Drum separation → Audio file: reads
inference/input_transform.py - CLI workflow → Onset framing: calls
main.py - Onset framing → Drum separation: frames drum track
README.md - CLI workflow → Drum-hit prediction: calls
main.py - Drum-hit prediction → Pretrained networks: loads network
inference/prediction.py - Drum-hit prediction → Onset framing: predicts framed clips
inference/prediction.py - CLI workflow → Notation generation: calls
main.py - Notation generation → Drum sheet music: constructs notation
README.md - CLI workflow → Drum sheet music: exports
main.py - Data scientist → Data preparation: prepares data
README.md - E-GMD dataset → Data preparation: provides paired data
README.md - Data preparation → Audio augmentation: applies augmentations
model_development/data_preparation.py - Data preparation → Prepared training data: creates clips
README.md - Audio augmentation → Prepared training data: augments clips