SaMuGeD-24-midi-sampling

Our to-do list at this point

- Refine Pattern Recognition Algorithm:

Focus on identifying and clustering repetitive musical phrases. Experiment with MIDI toolkit to get time signatures and divide notes into bars.

- SF Segmenter Enhancements:

Adjust parameters for better segmentation of smaller parts. Develop a user-friendly interface for parameter adjustments.

- Clustering Approach:

Use histograms to analyze note frequencies within bars. Explore clustering algorithms to identify repetitive patterns.

- User Input and Flexibility:

Allow users to experiment with different segment lengths and configurations. Consider user settings for tolerable silence durations in samples.

Roadmap/Plan

Setup

Create and start a virtual environment

Windows

python -m venv .venv
.\.venv\Scripts\activate

Unix (Linux, macOS)

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

Install required packages

For all systems, use the following command to install all required packages:

pip install -r requirements.txt

For Unix-based systems (e.g., Linux, macOS), use the command below to install all necessary dependencies:

pip install -r requirements_unix.txt

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