Capuchinbird Call Classification & Event Detection

Overview

This repository contains a Jupyter Notebook implementing a mini-project in Machine Learning, inspired by the HP Z Challenge. The goal of this project is to train a model that recognizes Capuchinbird calls and applies it to long forest recordings to detect occurrences of the bird.

🚧 Status: Work in Progress 🚧

• The project is still under development, with ongoing model optimization.
• The final CSV output generation is yet to be implemented.
• However, intermediate results can already be explored in the notebook.

Requirements

• Python 3.12.3 (Ensure you use this version for compatibility)
• Dependencies listed in requirements.txt

Setup Instructions

1️⃣ Create a Virtual Environment

python -m venv .venv
source .venv/bin/activate  # For Mac/Linux
.venv\Scripts\activate     # For Windows

2️⃣ Install Dependencies

pip install -r requirements.txt

3️⃣ Download the Kaggle Dataset

Before running the notebook, download the dataset from Kaggle using the following command:

kaggle datasets download -d kenjee/z-by-hp-unlocked-challenge-3-signal-processing -p data/ --unzip

Make sure the dataset is placed in the appropriate directory for the notebook to access.

4️⃣ Start Jupyter Notebook

jupyter notebook

Then open and run Capuchinbird_Classifier.ipynb.

Contributions

This is a personal project, but feel free to open issues or make suggestions!