Object Detection

Overview

This project implements object detection using deep learning models. The repository contains scripts for training, validating, and deploying an object detection model.

Features

• Train a custom object detection model
• Validate the trained model
• Run inference on new images
• Export the trained model for deployment

Installation

To get started, clone the repository and install the required dependencies:

# Clone the repository
git clone https://github.com/charan2217/object_detection.git
cd object_detection

# Install dependencies
pip install -r requirements.txt

Usage

Training the Model

To train the model, use the following command:

python train.py --data <path_to_data> --epochs <num_epochs>

Running Inference

To run inference on an image:

python detect.py --image <path_to_image>

Validating the Model

To validate the trained model:

python val.py --weights <path_to_model_weights>

Exporting the Model

To export the trained model:

python export.py --weights <path_to_model_weights>

Files and Directories

• detect.py - Runs inference on input images.
• train.py - Script for training the object detection model.
• val.py - Validates the trained model.
• export.py - Converts the trained model for deployment.
• requirements.txt - List of dependencies.
• hubconf.py - Model configuration file.
• tutorial.ipynb - Jupyter notebook with example usage.

License

This project is licensed under the AGPL-3.0 License.

Author

charan2217

Contributions

Contributions are welcome! Feel free to submit a pull request or open an issue.