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⛵️ Implementation a variety of popular Image Classification Models using TensorFlow2. [ResNet, GoogLeNet, VGG, Inception-v3, Inception-v4, MobileNet, MobileNet-v2, ShuffleNet, ShuffleNet-v2, etc...]

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Convolutional Nets in TensorFlow2

ConvNets-TensorFlow2 is a repository that implements a variety of popular Deep Convolutional Network Architectures using TensorFlow2. The core of this repository is intuitive code and concise architecture. If you are a user of TensorFlow2 and want to study various and popular CNN architectures, this repository will be the best choice to study. ConvNets-TensorFlow2 is continuously updated and managed. This repository has been very much influenced by Cifar100-pytorch.

Usage

$ python main.py 
    --nets={NETS} 
    --batch_size={BATCH_SIZE} 
    --lr={LEARNING_RATE} 
    --epochs={EPOCHS}

Models


VGG

Paper Very Deep Convolutional Networks for Large-Scale Image Recognition
Author Karen Simonyan, Andrew Zissermanr
Code VGG.py

Model Options

--nets {VGG11 or VGG13 or VGG16 or VGG19}

GoogLeNet

Paper Going Deeper with Convolutions
Author Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, Andrew Rabinovich
Code GoogLeNet.py

Model Options

--nets {GoogLeNet}

ResNet

Paper Deep Residual Learning for Image Recognition
Author Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun
Code ResNet.py

Model Options

--nets {ResNet18 or ResNet34 ResNet50 ResNet101 ResNet 152}

DenseNet

Paper Densely Connected Convolutional Networks
Author Gao Huang, Zhuang Liu, Laurens van der Maaten, Kilian Q. Weinberger
Code DenseNet.py

Model Options

--nets {DenseNet121 or DenseNet169 or DenseNet201 or DenseNet161}

InceptionV3

Paper Rethinking the Inception Architecture for Computer Vision
Author Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jonathon Shlens, Zbigniew Wojna
Code InceptionV3.py

Model Options

--nets {InceptionV3}

InceptionV4

Paper Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
Author Christian Szegedy, Sergey Ioffe, Vincent Vanhoucke, Alex Alemi
Code InceptionV4.py

Model Options

--nets {InceptionV4}

MobileNet

Paper MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
Author Andrew G. Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, Tobias Weyand, Marco Andreetto, Hartwig Adam
Code MobileNet.py

Model Options

--nets {MobileNet}

MobileNetV2

Paper MobileNetV2: Inverted Residuals and Linear Bottlenecks
Author Mark Sandler, Andrew Howard, Menglong Zhu, Andrey Zhmoginov, Liang-Chieh Chen
Code MobileNetV2.py

Model Options

--nets {MobileNetV2}

SqueezeNet

Paper SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size
Author Forrest N. Iandola, Song Han, Matthew W. Moskewicz, Khalid Ashraf, William J. Dally, Kurt Keutzer
Code SqueezeNet.py

Model Options

--nets {SqueezeNet}

SENet

Paper Squeeze-and-Excitation Networks
Author Jie Hu, Li Shen, Samuel Albanie, Gang Sun, Enhua Wu
Code SEResNet.py

Model Options

--nets {SEResNet18 or SEResNet34 or SEResNet50 or SEResNet101 or SEResNet152}

ShuffleNet

Paper ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
Author Xiangyu Zhang, Xinyu Zhou, Mengxiao Lin, Jian Sun
Code Coming Soon

Model Options

// Coming Soon

CondenseNet

Paper CondenseNet: An Efficient DenseNet using Learned Group Convolutions
Author Gao Huang, Shichen Liu, Laurens van der Maaten, Kilian Q. Weinberger
Code Coming Soon

Model Options

// Coming Soon

Xception

Paper Xception: Deep Learning with Depthwise Separable Convolutions
Author François Chollet
Code Coming Soon

Model Options

// Coming Soon

PreActResNet

Paper Identity Mappings in Deep Residual Networks
Author Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun
Code Coming Soon

Model Options

// Coming Soon

ResAttNet

Paper Residual Attention Network for Image Classification
Author Fei Wang, Mengqing Jiang, Chen Qian, Shuo Yang, Cheng Li, Honggang Zhang, Xiaogang Wang, Xiaoou Tang
Code Coming Soon

Model Options

// Coming Soon

PolyNet

Paper PolyNet: A Pursuit of Structural Diversity in Very Deep Networks
Author Xingcheng Zhang, Zhizhong Li, Chen Change Loy, Dahua Lin
Code Coming Soon

Model Options

// Coming Soon

PyramidNet

Paper Deep Pyramidal Residual Networks
Author Dongyoon Han, Jiwhan Kim, Junmo Kim
Code Coming Soon

Model Options

// Coming Soon

Reference

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⛵️ Implementation a variety of popular Image Classification Models using TensorFlow2. [ResNet, GoogLeNet, VGG, Inception-v3, Inception-v4, MobileNet, MobileNet-v2, ShuffleNet, ShuffleNet-v2, etc...]

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