Image Classification Project

Welcome to the Image Classification repository! This project focuses on image recognition using both C++ and Python. The C++ code serves as the main engine, while Python handles the preprocessing tasks.

Table of Contents

1. Introduction
2. Technologies Used
3. Features
4. Installation
5. Usage
6. Contributing
7. License
8. Contact
9. Releases

Introduction

Hi there! I'm Dhruv, the creator of this project. The goal of this repository is to provide a robust solution for image classification tasks. By leveraging the strengths of both C++ and Python, we can create an efficient system that processes images and recognizes patterns effectively.

Technologies Used

• C++: The core engine of the project, responsible for heavy computations and performance optimization.
• Python: Used primarily for preprocessing images before they are fed into the C++ engine.
• Libraries:
  • OpenCV: For image processing tasks.
  • NumPy: For numerical operations in Python.
  • TensorFlow or PyTorch: Depending on the model used for machine learning.

Features

• Image Recognition: Classifies images into various categories.
• Preprocessing: Cleans and prepares images for analysis.
• Backpropagation: Implements backpropagation for training neural networks.
• Convolutional Layers: Uses convolutional layers for feature extraction.
• Max Pooling: Reduces dimensionality while preserving important features.
• Fully Convolutional Networks: Enables pixel-wise classification for images.
• Custom Filters: Apply various filters for image enhancement.
• Bias Adjustment: Adjusts bias in the model to improve accuracy.

Installation

To set up the project, follow these steps:

1. Clone the repository:

   git clone https://github.com/codewithmalcom/Image_Classification.git
   cd Image_Classification

2. Install required libraries: For Python, you can install the necessary libraries using pip:

   pip install -r requirements.txt

3. Compile C++ code: Navigate to the C++ directory and compile the code:

   cd cpp
   g++ -o image_classifier main.cpp

4. Run the project: After compiling, you can run the C++ engine with the command:

   ./image_classifier

Usage

Once you have installed the project, you can start using it for image classification. Here’s a basic example of how to classify an image:

1. Prepare your images: Place your images in the images folder.
2. Run the preprocessing script:

   python preprocess.py

3. Execute the classification:

   ./image_classifier

The output will show the predicted classes for each image.

Contributing

Contributions are welcome! If you want to improve the project, please follow these steps:

1. Fork the repository.
2. Create a new branch:

   git checkout -b feature-branch

3. Make your changes and commit them:

   git commit -m "Add new feature"

4. Push to the branch:

   git push origin feature-branch

5. Create a pull request.

License

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

Contact

For any questions or suggestions, feel free to reach out:

• Email: [email protected]
• GitHub: codewithmalcom

Releases

To download the latest releases, visit the Releases section. Here, you can find compiled binaries and additional resources.

If you encounter any issues or need specific files, check the "Releases" section for the latest updates.

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Thank you for visiting the Image Classification repository! I hope you find this project useful and informative.