MrinalJain17 / VGG

Keras implementation of VGG from the paper "Very Deep Convolutional Networks for Large-Scale Image Recognition" - https://arxiv.org/abs/1409.1556

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VGG

Keras implementation of VGG from the paper Very Deep Convolutional Networks for Large-Scale Image Recognition

Insturctions

  1. Clone the repository and navigate to the downloaded folder.
	git clone https://github.com/MrinalJain17/VGG.git
	cd VGG
  1. Import the module and get the required model.
	from vgg import VGG
	
	# Getting VGG-16 (16-layer VGG model) for a dataset with 20 classes
	model = VGG(model_type='D', num_classes=20)
	model.summary()
  1. The model was tested on the cifar-10 dataset.
    For further details, view the jupyter notebook by running the command:
	jupyter notebook cifar-10.py

Requirements

Python 3.x (preferably from the Anaconda Distribution)

Additional Libraries to install

	pip install keras

(With backend as Tensorflow)
For installation of Tensorflow, view instructions on their site here.

About

Keras implementation of VGG from the paper "Very Deep Convolutional Networks for Large-Scale Image Recognition" - https://arxiv.org/abs/1409.1556

License:MIT License


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