DenseNet

This is the API reference for the DenseNet model present in Metalhead.jl.

The higher level model

Metalhead.DenseNet — Type

DenseNet(config::Integer; pretrain::Bool = false, growth_rate::Integer = 32,
         reduction = 0.5, inchannels::Integer = 3, nclasses::Integer = 1000)

Create a DenseNet model with specified configuration. Currently supported values are (121, 161, 169, 201) (reference).

Arguments

- `config`: the configuration of the model
- `pretrain`: whether to load the model with pre-trained weights for ImageNet.
- `growth_rate`: the output feature map growth probability of dense blocks (i.e. `k` in the ref)
- `reduction`: the factor by which the number of feature maps is scaled across each transition
- `inchannels`: the number of input channels
- `nclasses`: the number of output classes

Warning

DenseNet does not currently support pretrained weights.

The core function

Metalhead.densenet — Function

densenet(nblocks::AbstractVector{<:Integer}; growth_rate::Integer = 32,
         reduction = 0.5, dropout_prob = nothing, inchannels::Integer = 3,
         nclasses::Integer = 1000)

Create a DenseNet model (reference).

Arguments

nblocks: number of dense blocks between transitions
growth_rate: the output feature map growth probability of dense blocks (i.e. k in the ref)
reduction: the factor by which the number of feature maps is scaled across each transition
dropout_prob: the dropout probability for the classifier head. Set to nothing to disable dropout
inchannels: the number of input channels
nclasses: the number of output classes

source