Official Open JOSS reviewed version.
- Fix bug of name conflict while loading chord model.
Accumulated release. Various improvements and bug fix. See details below.
- Migrate checkpoints from private Google Drive to Github release. See here
- Replace opencv
- Upgrade Tensorflow version to 2.5.0 for Nvidia 30 series GPU compatibility.
- Upgrade Spleeter version to 2.3.0 for new TF version compatibility.
- Replace Opencv with PIL for drum feature resizing and remove opencv from the dependency.
- Simplify model loading mechanism by unifying the all checkpoint format to use TF format.
- Lazy import extraction functions to boost loading time.
- Change the order of Dockerfile commands for better utilizing cache.
- Add notice about compatibility issue of running on certain CPU architecture.
- Add explaination about enabling auto completion.
- Rephrase sentences in paper according to JOSS review feedback.
- Add explaination about installing development dependencies.
- Use pepy as the alternative source for 'download' state badge.
- Fix bug of unable to find vocal contour checkpoint.
- Fix bug of fail to custom layers of chord module.
- Fix various unit tests bugs.
- Fix minor linter errors.
Hotfix version according to issue #23
- Add a new piano transcription model and set it as the default model while using
music
module.
- Fix bug while parsing weight files in the checkpoint folder.
Various improvements on music module and some critical bug fixes.
- Improve the peak finding and thresholding strategy for more stable and better performance.
- Modify the feeding strategy of feature slices with adjustable overlapping rate while making predictions.
- Apply learning rate scheduler for music module.
- Replace the usage of custom training loop of music module with the built-in TF
.fit()
function.
- Fix a critical bug of inference of music module that would lead to missing onsets.
- Fix generation of pertubation of vocal module while training.
- Merge the demo page into master from
build_doc
branch.
Hotifx version according to issue #19.
- Fix bug of treating numpy array as list while appending elements.
Hotfix version according to issue #19.
- Fix column inconsistency of
aggregate_f0_info
andwrite_agg_f0_results
. - Update version of dependencies according to the security alert.
- Move
load_label
functions of different datasets into dataset structure classes. - Add custom exception on fail downloading GD file due to access limit.
- Add unit tests on parsing label files into shared intermediate format.
- Fix wrong access name of the dict in vocal midi inference function.
- Fix bug of generating beat module training labels.
Hotfix release of spleeter error.
- Call Spleeter in CLI mode instead of using python class.
Release the beat
module for symbolic domain beat transcription.
- Release
beat
module. - Add an example
patch-cnn
module for demonstrating the implementation progress.
- Refactor the flow of chord module for parsing the feature and label files.
- Modularize F0 information aggragation functions to utils.py and io.py.
- Improve verbosity on fail to open hdf files.
- Re-arrange the side bar with an additional group of CLI.
- Add custom CSS style for adjusting the width of audio and video elements.
- Fix Spleeter import errors after upgrading to v2.1.2.
We release the modules for vocal melody transcription after a decent amount of effort. Now you can transcribe your favorite singing voice.
- Release
vocal
andvocal-contour
submodules.
- Improve chord transcription results by filtering out chord predictions with short duration.
- Resolve the path for transcription output in a consistent way.
- Re-organize Quick Start and Tutorial pages to improve accessibility.
- Move the section for development from README.md to CONTRIBUTING.md.
- Fix bugs of passing the wrong parameter to vamp for chroma feature extraction.
- Add more supported datasets for download and process.
- Supports to save checkpoints in .pb format with customized model checkpoint callback.
- Huge refactor of constants.dataset. Improves reusability and add more useful common utilities.
- Modularize common parts of app classes.
- Construct base class of loading dataset samples. Reduce duplicate code and reuse the same functionalities.
- Filter out messy Tensorflow warnings when using CLI.
- Resolved bugs of some function parameters not actually being used inside functions.
- Fix CFP extraction down_fs don't actually work.
- Add command for synthesizing MIDI file.
- Provides colab for quick start now!
- Lazy import application instance for avoiding pulling large amount of dependencies.
- Group sub-commands into different sections when showing help message.
- Better dealing with the input model path.
- Better approach for resolving dataset path when given with "./".
- Add documentation for Conda user for manually install omnizart.
- Fix wrong save path of checkpoints.
- Fix installation script for not upgrading pip after activating virtual environment.
First release of omnizart
CLI tool, as well as a python package.
- Multi-instrument transcription
- Drum transcription
- Chord transcription
- Download datasets
- Extract feature of datasets for each module
- Train models for each module