Color-Based Object Detection & Dodge Game Project

Overview

A university project consisting of two parts: the first part focuses on implementing various image processing filters and color-based object detection algorithms using Python and OpenCV. The second part involves the development of a dodge game - Chicken Escape 🐔🦊, enhanced with real-time object detection for player control.

Part 1: Filters and Object Detection 📸

Filters Implemented

• Binarization and Thresholding
• Smoothing Filters: Mean, Median, Gaussian
• Edge Detection Filters: Laplacian, Gradient
• Morphological Filters: Erosion, Dilation, Closing, Opening
• Custom Filters: Prewitt, Sobel

Object Detection

• Developed the "Object_Color_Detection" function for detecting objects based on color.
• Proposed improvements for the object detection function using the Kalman Filter for predicting the position of objects in real-time.
• Implemented two functionalities using object color detection: "Invisibility Cloak" and "Green Screen".
• Developed a graphical user interface (GUI) for applying filters and object detection.

Part 2: Dodge Game - Chicken Escape 🐔🦊

The Dodge Game is an implementation of computer vision principles in the gaming domain. It offers an immersive gaming experience where players control a chicken 🐔 to navigate through obstacles 🌳 and avoid fox enemies 🦊 using real-time object detection techniques.

Features

• Object Detection Control: Players can control the movement of the character using real-world objects, specifically by manipulating a colored object detected through the camera. The default color is green.
• Dynamic Obstacle Avoidance: The game environment presents dynamic obstacles that the player must navigate through by moving the character horizontally.
• Scoring System: Players accumulate points based on their performance, with increasing difficulty levels as the game progresses.
• Enhancements: Two additional enhancements, such as score tracking or speed variations, contribute to the gameplay experience.

Gameplay

• Objective: Navigate the chicken character through obstacles (foxes and trees) by manipulating a colored object detected through the camera.
• Controls:
  • Keyboard Controls:
    • "SPACE" bar: Start or restart the game.
    • "Q": Move the character left.
    • "D": Move the character right.
    • "E": Quit the game.
    • "2": Horizontal movement.
    • "3": Horizontal and vertical movement (Kalman Filter).
  • Object Detection: Control the character's movement by shifting the position of a colored object detected through the camera.

Installation

To run the project, follow these steps:

1. Ensure Python is installed on your system.
2. Install the necessary libraries: pip install -r requirements.txt.
3. Run the project: python IHM.py.
4. Interface Buttons:
   • Object Detection: Start detecting and tracking the object using your webcam. (default color is green)
   • Invisibility: Activate the invisibility mode to make the object disappear against a background.
   • Fond Vert: Apply the green screen effect to replace the background with a custom image.
   • Stop: Stop the object detection or background effect.
   • Clean: Clear the canvas.
   • Game: Run the dodge game window.
   • Moyen: Apply the mean filter to the displayed image.
   • Median: Apply the median filter to the displayed image.
   • Gradient: Apply the gradient filter to the displayed image.
   • Gaussien: Apply the Gaussian filter to the displayed image.
   • Laplacien: Apply the Laplacian filter to the displayed image.
   • Erode/Dilate: Apply morphological operations (erosion and dilation) to the displayed image.
   • Closing/Opening: Apply morphological operations (closing and opening) to the displayed image.
   • Prewitt(H/V): Apply the Prewitt filter (horizontal or vertical) to the displayed image.
   • Sobel: Apply the Sobel filter to the displayed image.
   • Threshold and Type Adjustments: Adjust the threshold and type for thresholding using the scales provided.