Keras – Applications

Keras applications module is used to provide pre-trained model for deep neural networks. Keras models are used for prediction, feature extraction and fine tuning. This chapter explains about Keras applications in detail.

Pre-trained models

Trained model consists of two parts model Architecture and model Weights. Model weights are large file so we have to download and extract the feature from ImageNet database. Some of the popular pre-trained models are listed below,

• ResNet
• VGG16
• MobileNet
• InceptionResNetV2
• InceptionV3
  

  Loading a model

  Keras pre-trained models can be easily loaded as specified below −

  import keras
  import numpy as np
  from keras.applications import vgg16, inception_v3, resnet50, mobilenet
  #Load the VGG model
  vgg_mymodel = vgg16.VGG16(weights = 'imagenet')
  #Load the Inception_V3 model
  inception_mymodel = inception_v3.InceptionV3(weights = 'imagenet')
  #Load the ResNet50 model
  resnet_mymodel = resnet50.ResNet50(weights = 'imagenet')
  #Load the MobileNet model mobilenet_model = mobilenet.MobileNet(weights = 'imagenet')

  Once the model is loaded, we can immediately use it for prediction purpose. Let us check each pre-trained model in the upcoming chapters.