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VGG HUB

architecture

Overview

VGG-Hub is a comprehensive collection of PyTorch implementations for the VGG (Visual Geometry Group) models. This project aims to provide a centralized hub for researchers, developers, and enthusiasts to access, train, and experiment with VGG architectures for various computer vision tasks.

Key Features

  • PyTorch Implementation: All VGG models are implemented using PyTorch, a popular deep learning framework, ensuring flexibility and ease of use.

  • Trainable: VGG-Hub allows users to train the models on their own datasets, facilitating experimentation and adaptation to specific tasks.

  • Model Variants: The repository includes various VGG model variants, enabling users to choose the architecture that best suits their needs.

  • Easy-to-Use Interface: A user-friendly interface and well-documented code make it straightforward to integrate VGG models into your projects.

Installation

# Clone the repository
git clone https://github.com/gorkemgul/VGG-Hub.git

# Move to the working directory
cd VGG-Hub

# Install dependencies
pip install -r requirements.txt

Training

python train.py