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WaveAnalysis Program

WaveAnalysis is a program designed to calculate the angles of waves using Cartesian coordinates. It involves analyzing two images to determine the wave's break angle.

Table of Contents

Prerequisites

Before running the program, ensure you have the following installed on your local machine:

  • Python 3.7+
  • pip (Python package installer)

Installation

  1. Clone the Repository:

    git clone https://github.com/nicholas-tayag/waveAnalysis.git
cd waveAnalysis

  2. Set Up Virtual Environment (optional but recommended):

    python -m venv venv
source venv/bin/activate   # On Windows use `venv\Scripts\activate`

  3. Install Required Packages:

    pip install -r requirements.txt

    If requirements.txt does not exist, manually install the necessary packages, such as:

    • opencv-python
    • numpy

Running the Program

  1. Prepare Your Images: Place your images in the imgs directory within the waveAnalysis folder. For this example, the program assumes two images, pic1.png and pic2.png.

  2. Run the Script: Execute the script to analyze the images and calculate the wave angles:

    python waveAngle.py

Usage

Manual Point Selection

  1. Load the Images: Upon running the script, the images (pic1.png and pic2.png) will be loaded and displayed one at a time. The images should be placed in the imgs directory within the waveAnalysis folder.

  2. Select Points: For each image, the user will be prompted to manually click on three points along the wave crest. These points are essential for calculating the wave's angle.

  3. Determine Wave Angle: After selecting the points, the program calculates the wave angle using the Cartesian coordinates of the selected points. The calculated angle is then displayed in the console output.

Example Workflow

First Image (pic1.png):

  1. The image is displayed on the screen.
  2. The user clicks on three points along the wave crest.
  3. The program calculates and prints the wave angle in the console.

Second Image (pic2.png):

  1. The image is displayed on the screen.
  2. The user clicks on three points along the wave crest.
  3. The program calculates and prints the wave angle in the console.

This manual point selection process allows for precise input, ensuring an accurate calculation of wave angles based on the user's observations.

Notes

  • Accuracy: The accuracy of the calculated angles depends on the precision of the points selected by the user.
  • Console Output: The calculated angles are displayed in the console after points are selected for each image.

Future Implementations

In future versions, we aim to automate the wave angle calculation process using machine learning. These enhancements include:

  • Integration of YOLO: Utilize YOLO for automatic detection of wave crests and features in images.
  • Machine Learning Models: Develop and train machine learning models to predict and analyze wave angles from video footage or images automatically, minimizing the need for manual point selection.
  • Automated Workflow: Implement a fully automated workflow that ingests video or image data, processes it using machine learning models, and outputs calculated wave angles and other relevant metrics.

These improvements will enhance the accuracy and efficiency of the wave analysis process, enabling more comprehensive data analysis and potentially real-time processing.