Skip to content

Latest commit

 

History

History
76 lines (57 loc) · 2.54 KB

README.md

File metadata and controls

76 lines (57 loc) · 2.54 KB
Raw

Fourier Decomposition Web Application

This project is a web application built with FastAPI that allows users to upload audio files (WAV format) and decompose them into their Fourier components. The application performs a Fast Fourier Transform (FFT) on the audio signal and identifies the dominant frequencies.

Features

  • File Upload: Allows users to upload WAV files for processing.
  • Fourier Analysis: Computes the Fourier Transform of the audio signal and returns the dominant frequencies.
  • Visualization: (Optional) Could be extended for plotting or visualizing the frequency spectrum.

Technologies

  • FastAPI: For creating the web application.
  • librosa: For loading and reading audio files.
  • NumPy: For performing the FFT and manipulating the signal.
  • Jinja2: For rendering HTML templates.

Installation

Prerequisites

  • Python 3.7+
  • A virtual environment (optional but recommended)

Steps to Set Up

  1. Clone the repository:

    git clone https://github.com/susmita2022khatun/Fourier_decomposition.git
cd Fourier_decomposition

  2. Create and activate a virtual environment (optional):

    python -m venv venv
# On Windows
venv\Scripts�ctivate
# On Mac/Linux
source venv/bin/activate

  3. Install the required dependencies:

    pip install -r requirements.txt

  4. Ensure the uploads and static directories exist:

    • uploads/ will store the uploaded audio files.
    • static/ will contain static files (CSS, JS, etc.).

  5. Run the application:

    python main.py

    The application will start the server at http://127.0.0.1:8000/.

Usage

  1. Visit the application in a browser at http://127.0.0.1:8000/.
  2. Upload a WAV file using the file input on the webpage.
  3. The server will process the audio and return a JSON response containing the dominant frequencies in the audio signal.

Example Response:

{
  "filename": "example.wav",
  "dominant_frequencies": [440.0, 880.0, 1320.0]
}

Code Overview

  • main.py: Contains the FastAPI application logic, including routes for uploading files and processing them using the FFT.
  • process.py: Contains helper functions for performing Fourier decomposition, including discrete_fourier, fft, and fftfreq.
  • static/: Directory for static files like CSS or JavaScript (optional, could be used for front-end enhancements).
  • templates/: Contains HTML templates (like index.html) rendered by FastAPI using Jinja2.