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ABD.pt

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README.md

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-license: mit
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+
+# 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:
+
+```bash
+pip install -r requirements.txt
+```
+
+## Installation
+
+1. Clone this repository:
+
+    ```bash
+    git clone https://github.com/Safi-ullah-majid/ABD-model.git
+    cd ABD-model
+    ```
+
+2. Install dependencies:
+
+    ```bash
+    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:
+
+```bash
+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.