Ivory vs Omnizart

Ivory uses AI to transcribe piano audio into editable sheet music and MIDI. Its model is trained specifically for polyphonic piano solos. The web app accepts MP3, WAV, MP4, and standard MIDI files up to 15MB, as well as YouTube links. Users can edit notes by moving, resizing, or deleting them and apply smart quantization; synchronized score and piano-roll views, chord detection, hand separation, tempo control, and looping support review. Exports are available as PDF, MusicXML, and MIDI, and notation files can be imported into Sibelius, Finale, and MuseScore. Ivory lists workflows for Logic Pro, Ableton Live, FL Studio, Cubase, and Reaper, while its audio-to-MIDI DAW plugin integration is coming soon. The free plan costs nothing and includes unlimited transcriptions, but Performance MIDI previews are limited to 30 seconds. The yearly plan costs €59 a year and adds full-length Performance MIDI, advanced editing, and the premium AI model. The iOS app requires iOS 16 or later; videos exported without a subscription have an Ivory watermark.

Omnizart is a free Python library for transcribing polyphonic music into pitched instruments, vocal melody, chords, drum events, and beats. Pre-trained checkpoints allow transcription without first training a model. The project also documents dataset downloads, feature preprocessing, model training, transcription, and sonification, with MIDI, CSV, and text output formats. It lists separate applications for music, drums, vocals, vocal contours, chords, and beats, along with chord detection, MIDI export, and stem separation. Installation options include pip, Docker, and Conda, and a command-line interface is provided. Documentation links to a Colab notebook and a Replicate web demo. Omnizart supports Linux, Windows, macOS, and self-hosted setups, but is incompatible with ARM-based macOS because of underlying dependencies. The package requires Python 3.8 or later and below 3.15. Drum checkpoints can be used for transcription, though the drum model has an unresolved issue that prevents loss convergence when training from scratch. It is MIT-licensed and offers GitHub Issues for installation, compatibility, and usage problems.