🖼️ CPP Image Processing

This repository contains the implementation of Exercise 4 from the course 67315 - Programming Workshop in C & C++ at The Hebrew University Of Jerusalem (HUJI).
The project focuses on building a simple image classification system using a Multi-Layer Perceptron (MLP) neural network implemented in C++.
The project received a final grade of 105 (out of 105).

📦 Project Structure

CPP-Image-Processing/
├── Activation.cpp        # Implementation of activation functions
├── Activation.h          # Declarations for activation functions
├── Dense.cpp             # Implementation of Dense layer
├── Dense.h               # Declarations for Dense layer
├── MlpNetwork.cpp        # Implementation of the MLP network
├── MlpNetwork.h          # Declarations for the MLP network
├── Matrix.cpp            # Implementation of the Matrix class
├── Matrix.h              # Declarations for the Matrix class
├── main.cpp              # Entry point of the application
├── Makefile              # Build configuration
├── plot_img.py           # Python script for visualizing images
├── images/               # Directory containing input images
├── parameters/           # Directory containing model parameters
├── LICENSE               # MIT License
└── README.md             # Project documentation

🚀 Getting Started

Prerequisites

• C++ compiler supporting C++11 or later (e.g., g++)
• Python 3.x (for running plot_img.py)​
• Python packages: matplotlib, numpy

Building the Project

1. Clone the repository:

   git clone https://github.com/OrF8/CPP-Image-Processing.git
   cd CPP-Image-Processing
   

2. Compile the project:

   make
   

   This will generate an executable named mlp_classifier.

Running the Application

./mlp_classifier

The application will process the images located in the images/ directory using the MLP network with parameters from the parameters/ directory.

Visualizing Images

To visualize an image using the provided Python script:​

python3 plot_img.py path_to_image

Replace path_to_image with the path to the image you wish to visualize.

📄 License

This project is licensed under the MIT License – see the LICENSE file for details.