segformer pytorch

Segmenteur - Pytorch

Implémentation du réseau neuronal Segformer, Attention + MLP pour la segmentation, dans Pytorch.

Installer

$ pip install segformer-pytorch

Usage

Par exemple, MiT-B0

 import torch
from segformer_pytorch import Segformer

model = Segformer (
    dims = ( 32 , 64 , 160 , 256 ),      # dimensions of each stage
    heads = ( 1 , 2 , 5 , 8 ),           # heads of each stage
    ff_expansion = ( 8 , 8 , 4 , 4 ),    # feedforward expansion factor of each stage
    reduction_ratio = ( 8 , 4 , 2 , 1 ), # reduction ratio of each stage for efficient attention
    num_layers = 2 ,                 # num layers of each stage
    decoder_dim = 256 ,              # decoder dimension
    num_classes = 4                 # number of segmentation classes
)

x = torch . randn ( 1 , 3 , 256 , 256 )
pred = model ( x ) # (1, 4, 64, 64)  # output is (H/4, W/4) map of the number of segmentation classes

Assurez-vous que les mots-clés sont au plus un tuple de 4, car ce référentiel est codé en dur pour donner au MiT 4 étapes comme cela est fait dans l'article.

Citations

 @misc { xie2021segformer ,
    title   = { SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers } , 
    author  = { Enze Xie and Wenhai Wang and Zhiding Yu and Anima Anandkumar and Jose M. Alvarez and Ping Luo } ,
    year    = { 2021 } ,
    eprint  = { 2105.15203 } ,
    archivePrefix = { arXiv } ,
    primaryClass = { cs.CV }
}