C++20 inference for CREPE a monophonic pitch tracker based on a deep convolutional neural network operating directly on the time-domain waveform input.

This uses ONNXRuntime & scripts from ort-builder to:

• Converts an ONNX model to ORT format and serializes it to C++ source code, generate custom slimmed ONNX Runtime static libs.
• Create a flexible but tiny inference engine for a specific model.
• A minimal ORT binary using only the CPU provider

• crepe-model contains the ONNX & ORT model along with the generated h and c file
• scripts contain the ORT model build scripts
• src shared inference
• src_wasm main WASM, for the web app
• src_cli is a very simple cli app that uses miniaudio for audio processing
• src_test a simple test that replicates the orignal repo python test for debugging using miniaudio
• deps project dependencies
• web Javascript/HTML code for the WASM app.

You can use my fork of crepe, this adds ONNX export capability for CREPE models

• export_model_to_onnx() function to core.py that converts Keras models to ONNX
• A script (onnx_export.py) to easily export models with different capacities

Create your venv and get your requirements.

Usage examples:

$ pip install -e .
$ python -m crepe.onnx_export tiny  # Creates model-tiny.onnx
$ python -m crepe.onnx_export full -o custom_name.onnx

Then we will use ort-builder :

$ git submodule update --init

$ python3 -m venv venv
$ source ./venv/bin/activate`

$ pip install -r requirements.txt
$ ./convert-model-to-ort.sh model.onnx

Now we build our customized onnx runtime static libraries

$ ./build-mac.sh

On macOS. Assuming that you have a typical C++ toolchain, CMake and AppleClang/clang etc. You're also going to need to set up the Emscripten SDK for compiling to WebAssembly.

$ git clone --recurse-submodules https://github.com/joeloftusdev/crepe.cpp

cli/test

$ mkdir build
$ cd build

$ cmake -DCMAKE_BUILD_TYPE=Release ..

$ cmake --build .

Example output running the catch2 test:

# Run the test with verbose output:
$ ./src-test/crepe_test -s

PASSED:
  CHECK( analytics.mean_confidence > 0.0f )
with expansion:
  0.84595f > 0.0f
with messages:
  Sample rate: 16000Hz
  Results Summary:
  Processed 270 frames
  Mean confidence: 0.845953
  Sample frequencies (Hz): [187.803 187.803 189.985 192.193 192.193]
  Min frequency: 187.803
  Max frequency: 1766.17
  Correlation between time and frequency: 0.961408
  Should be close to 1.0 for frequency sweep

wasm:

$ source "/path/to/emsdk/emsdk_env.sh"
$ emcmake cmake -S . -B build-wasm-release -DCMAKE_BUILD_TYPE=Release
$ emmake cmake --build build-wasm-release   

Open the index.html with live server or whatever you preference and view the wasm app:

• The orignal CREPE repo
• ort-builder
• basicpitch.cpp was a great reference for the structure of this repo.