DynamicUnet
Create a U-Net from a given architecture.
DynamicUnet( encoder, n_classes, img_size, blur = FALSE, blur_final = TRUE, self_attention = FALSE, y_range = NULL, last_cross = TRUE, bottle = FALSE, act_cls = nn()$ReLU, init = nn()$init$kaiming_normal_, norm_type = NULL )
encoder |
encoder |
n_classes |
number of classes |
img_size |
image size |
blur |
blur is used to avoid checkerboard artifacts at each layer. |
blur_final |
blur final is specific to the last layer. |
self_attention |
self_attention determines if we use a self attention layer at the third block before the end. |
y_range |
If y_range is passed, the last activations go through a sigmoid rescaled to that range. |
last_cross |
last cross |
bottle |
bottle |
act_cls |
activation |
init |
initializer |
norm_type |
normalization type |
None
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.