This release contains all capacities of CREPE models in the ONNX format.
Overview
There are totally 5 model weights of different capacities: full, large, medium, small and tiny.
- The 'full' and 'tiny' models were converted from the torchcrepe repository.
- The 'large', 'medium' and 'small' models were converted from the original TensorFlow implementation using scripts in this repository.
Usage
- Put these models into the
onnxcrepe/assets/directory. - Edit
modelin the configuration file(s) inonnxcrepe/configs/directory to switch among different model capacities.
Speed and performance
As the 'full' capacity refers to the model in the original paper, smaller models provide a trade-off between the computation time versus the time resolution or slightly lower accuracy. More details of the speed comparison can be found here.
Notes: higher rates of octave errors were observed when predicting with smaller models. Carefully tuning fmin and fmax may help.