VGG(imsize = (224, 224); config, inchannels, batchnorm = false, nclasses, fcsize, dropout)

Create a VGG model (reference). See also vgg.

Arguments

• imsize: input image width and height as a tuple
• config: the configuration for the convolution layers (see Metalhead.vgg_convolutional_layers)
• inchannels: number of input channels
• batchnorm: set to true to use batch normalization after each convolution
• nclasses: number of output classes
• fcsize: intermediate fully connected layer size (see Metalhead.vgg_classifier_layers)
• dropout: dropout level between fully connected layers