ABD-model: Atom and Bond Detection Model

This repository contains a deep learning-based model designed for detecting atoms and bonds in molecular images. It can be used for various applications in molecular chemistry and image analysis.

Overview

The ABD-model is a YOLO-based deep learning model designed to detect atoms (e.g., C, O, H, N) and bond types (single, double, triple) in molecular structure images. The model can extract useful data from 2D molecular representations, aiding in further computational chemistry analysis.

Features

• Atom Detection: Detects atoms like Carbon (C), Oxygen (O), Nitrogen (N), and Hydrogen (H) in molecular images.
• Bond Detection: Identifies single, double, and triple bonds between atoms.
• Versatility: Works with a wide variety of molecular structure images.
• YOLO-based: Uses a YOLO (You Only Look Once) model for fast and accurate detection of atoms and bonds.
• Open-source: Easy to integrate into your own projects and customize.

Requirements

To run this model, you need to install the following dependencies:

• Python 3.x
• PyTorch
• OpenCV (for image processing)
• NumPy
• Any other libraries listed in requirements.txt

To install the dependencies, run:

pip install -r requirements.txt

Installation

1. Clone this repository:

   git clone https://github.com/Safi-ullah-majid/ABD-model.git
   cd ABD-model
   

2. Install dependencies:

   pip install -r requirements.txt
   

3. Download the model file ABD.pt and place it in the correct directory.

Usage

To make predictions using the model, run the predict.py script:

python predict.py --input_path path/to/image.png

Ensure that:

• The input image is in .png format.
• The model (ABD.pt) is loaded correctly.
• The input image is a valid .png file representing a molecular structure.

License

This repository is licensed under the MIT License - see the LICENSE file for details.