https://github.com/kumar-shridhar/cnn_architectures

Keras Implementation of major CNN architectures
https://github.com/kumar-shridhar/cnn_architectures

convolutional-neural-networks densenet-keras inception-resnet-v2 keras resnet-50

Last synced: 3 months ago
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Keras Implementation of major CNN architectures

• Host: GitHub
• URL: https://github.com/kumar-shridhar/cnn_architectures
• Owner: kumar-shridhar
• License: gpl-3.0
• Created: 2018-01-20T21:00:21.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2018-07-03T19:42:57.000Z (over 7 years ago)
• Last Synced: 2025-04-12T19:40:00.932Z (6 months ago)
• Topics: convolutional-neural-networks, densenet-keras, inception-resnet-v2, keras, resnet-50
• Language: Jupyter Notebook
• Homepage:
• Size: 50.8 KB
• Stars: 15
• Watchers: 1
• Forks: 3
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Keras Implementation of all major CNN Architectures

## Requirements

  * NumPy >= 1.11.1

  * Keras >= 2.0 (Using TensorFlow in backend)

  * Python >= 3.4

## Available Architectures

  * VGG 16

  * Inception V3

  * ResNet 50

  * DenseNet

  * Inception V4

  * InceptionResnet V2 

  * NASNet

## Steps

  * In the first line Import the name of the model by using the import command and specifying the model name:

	* for Resnet 

  * Specify the dir path of the training and validation dataset in the PATH and size of the image in sz and the batch size. 

  *