One-Shot Video Object Segmentation (OSVOS)

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Welcome to the One-Shot Video Object Segmentation (OSVOS) repository! OSVOS is a project focused on the development and implementation of algorithms for performing one-shot video object segmentation tasks.

Table of Contents

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• Introduction
• Features
• Installation
• Usage
• Contributing
• License

Introduction

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The One-Shot Video Object Segmentation (OSVOS) project aims to provide a framework for segmenting objects in videos using one-shot learning techniques. It leverages deep learning models and computer vision algorithms to achieve accurate and efficient segmentation results.

Features

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• One-shot video object segmentation
• Integration with popular datasets
• Support for different deep learning architectures
• Evaluation metrics for assessing segmentation performance
• Visualization tools for analyzing segmentation results

Installation

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To install the OSVOS project, follow these steps:

1. Clone the repository to your local machine:

   git clone https://github.com/gargmegham/OSVOS.git

2. Navigate to the project directory:

   cd OSVOS

3. Install the required dependencies:

   pip install -r requirements.txt

Usage

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To use the OSVOS project, follow the instructions provided in the documentation.

Contributing

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We welcome contributions from the community to help improve and enhance the OSVOS project. Please refer to the contributing guidelines for detailed instructions on how to contribute.

License

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The OSVOS project is licensed under the MIT License. See the LICENSE file for more information.