Implementation of Segformer, Attention + MLP neural network for segmentation, in Pytorch

Related tags

Deep Learning deep-learning artificial-intelligence segmentation image-segmentation attention-mechanism multilayer-perceptron
Overview

Segformer - Pytorch

Implementation of Segformer, Attention + MLP neural network for segmentation, in Pytorch.

Install

$ pip install segformer-pytorch

Usage

For example, MiT-B0

import torch
from segformer_pytorch import Segformer

model = Segformer(
    patch_size = 4,                 # patch size
    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

Make sure the keywords are at most a tuple of 4, as this repository is hard-coded to give the MiT 4 stages as done in the paper.

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}
}
You might also like...
Implementation of gMLP, an all-MLP replacement for Transformers, in Pytorch
Implementation of gMLP, an all-MLP replacement for Transformers, in Pytorch

Implementation of gMLP, an all-MLP replacement for Transformers, in Pytorch

Phil Wang 383 Jan 2, 2023
Pytorch implementation of MLP-Mixer with loading pre-trained models.

MLP-Mixer-Pytorch PyTorch implementation of MLP-Mixer: An all-MLP Architecture for Vision with the function of loading official ImageNet pre-trained p

Qiushi Yang 2 Sep 29, 2022
PyTorch code for our paper "Attention in Attention Network for Image Super-Resolution"

Under construction... Attention in Attention Network for Image Super-Resolution (A2N) This repository is an PyTorch implementation of the paper "Atten

Haoyu Chen 71 Dec 30, 2022
MLP-Like Vision Permutator for Visual Recognition (PyTorch)
MLP-Like Vision Permutator for Visual Recognition (PyTorch)

Vision Permutator: A Permutable MLP-Like Architecture for Visual Recognition (arxiv) This is a Pytorch implementation of our paper. We present Vision

Qibin (Andrew) Hou 162 Nov 28, 2022
Pytorch implementation of
Pytorch implementation of "Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling"

RNN-for-Joint-NLU Pytorch implementation of "Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling"

Kim SungDong 194 Dec 28, 2022
Unofficial Implementation of MLP-Mixer in TensorFlow
Unofficial Implementation of MLP-Mixer in TensorFlow

mlp-mixer-tf Unofficial Implementation of MLP-Mixer [abs, pdf] in TensorFlow. Note: This project may have some bugs in it. I'm still learning how to i

Rishabh Anand 24 Mar 23, 2022
Implementation of
Implementation of "A MLP-like Architecture for Dense Prediction"

A MLP-like Architecture for Dense Prediction (arXiv) Updates (22/07/2021) Initial release. Model Zoo We provide CycleMLP models pretrained on ImageNet

Shoufa Chen 244 Dec 27, 2022
Unofficial Implementation of MLP-Mixer, Image Classification Model
Unofficial Implementation of MLP-Mixer, Image Classification Model

MLP-Mixer Unoffical Implementation of MLP-Mixer, easy to use with terminal. Train and test easly. https://arxiv.org/abs/2105.01601 MLP-Mixer is an arc

Oğuzhan Ercan 6 Dec 5, 2022
MLP-Numpy - A simple modular implementation of Multi Layer Perceptron in pure Numpy.

MLP-Numpy A simple modular implementation of Multi Layer Perceptron in pure Numpy. I used the Iris dataset from scikit-learn library for the experimen

Soroush Omranpour 1 Jan 1, 2022
Comments
  • Something is wrong with your implementation.

    Something is wrong with your implementation.

    Hello!

    First of all, I really like the repo. The implementation is clean and so much easier to understand than the official repo. But after doing some digging, I realized that the number of parameters and layers (especially conv2d) is quite different from the official implementation. This is the case for all variants I have tested (B0 and B5).

    Check out the README in my repo here, and you'll see what I mean. I also included images of the execution graphs of the two different implementations in the 'src' folder, which could help to debug.

    I don't quite have time to dig into the source of the problem, but I just thought I'd share my observations with you.

    opened by camlaedtke 0
  • Models weights + model output HxW

    Models weights + model output HxW

    Hi,

    Could you please add the models weights so we can start training from them?

    Also, why you choose to train models with an output of size (H/4,W/4) and not the original (HxW) size?

    Great job for the paper, very interesting :)

    opened by isega24 2
  • The model configurations for all the SegFormer B0 ~ B5

    The model configurations for all the SegFormer B0 ~ B5

    Hello How are you? Thanks for contributing to this project. Is the model configuration in README MiT-B0 correctly? That's because the total number of params for the model is 36M. Could u provide all the model configurations for SegFormer B0 ~ B5?

    opened by rose-jinyang 5
  • a question about kv reshape in Efficient Self-Attention

    a question about kv reshape in Efficient Self-Attention

    Thanks for sharing your work, your code is so elegant, and inspired me a lot. Here is a question about the implementation of Efficient Self-Attention

    It seems you use a "mean op" to reshape k,v. and the official implementation uses a (learnable) linear mapping to reshape k,v

    may I ask, whether this difference significantly matters in your experiment ?

    in your code:

    k, v = map(lambda t: reduce(t, 'b c (h r1) (w r2) -> b c h w', 'mean', r1 = r, r2 = r), (k, v))

    the original implementation uses:

    self.kv = nn.Linear(dim, dim * 2, bias=qkv_bias)
self.sr = nn.Conv2d(dim, dim, kernel_size=sr_ratio, stride=sr_ratio)
self.norm = nn.LayerNorm(dim)

x_ = x.permute(0, 2, 1).reshape(B, C, H, W)
x_ = self.sr(x_).reshape(B, C, -1).permute(0, 2, 1)
x_ = self.norm(x_)
kv = self.kv(x_).reshape(B, -1, 2, self.num_heads, C // self.num_heads).permute(2, 0, 3, 1, 4)
k, v = kv[0], kv[1]
    opened by masszhou 1
Releases(0.0.6)
Owner
Phil Wang
Working with Attention
Phil Wang
GitHub
Unofficial implementation of MLP-Mixer: An all-MLP Architecture for Vision

MLP-Mixer: An all-MLP Architecture for Vision This repo contains PyTorch implementation of MLP-Mixer: An all-MLP Architecture for Vision. Usage : impo

Rishikesh (ऋषिकेश) 175 Dec 23, 2022
Implementation for paper MLP-Mixer: An all-MLP Architecture for Vision

MLP Mixer Implementation for paper MLP-Mixer: An all-MLP Architecture for Vision. Give us a star if you like this repo. Author: Github: bangoc123 Emai

Ngoc Nguyen Ba 86 Dec 10, 2022
This is an official implementation for "AS-MLP: An Axial Shifted MLP Architecture for Vision".

AS-MLP architecture for Image Classification Model Zoo Image Classification on ImageNet-1K Network Resolution Top-1 (%) Params FLOPs Throughput (image

SVIP Lab 106 Dec 12, 2022
Implements MLP-Mixer: An all-MLP Architecture for Vision.

MLP-Mixer-CIFAR10 This repository implements MLP-Mixer as proposed in MLP-Mixer: An all-MLP Architecture for Vision. The paper introduces an all MLP (

Sayak Paul 51 Jan 4, 2023
Official implementation of "SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers"

SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers Figure 1: Performance of SegFormer-B0 to SegFormer-B5. Project page

NVIDIA Research Projects 1.4k Dec 31, 2022
The code uses SegFormer for Semantic Segmentation on Drone Dataset.

SegFormer_Segmentation The code uses SegFormer for Semantic Segmentation on Drone Dataset. The details for the SegFormer can be obtained from the foll

Dr. Sander Ali Khowaja 1 May 8, 2022
🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐

?? Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐

xmu-xiaoma66 7.7k Jan 5, 2023
Keras attention models including botnet,CoaT,CoAtNet,CMT,cotnet,halonet,resnest,resnext,resnetd,volo,mlp-mixer,resmlp,gmlp,levit

Keras_cv_attention_models Keras_cv_attention_models Usage Basic Usage Layers Model surgery AotNet ResNetD ResNeXt ResNetQ BotNet VOLO ResNeSt HaloNet

null 319 Dec 28, 2022
PyTorch implementation of MLP-Mixer

PyTorch implementation of MLP-Mixer MLP-Mixer: an all-MLP architecture composed of alternate token-mixing and channel-mixing operations. The token-mix

Duo Li 33 Nov 27, 2022
Implementation of ResMLP, an all MLP solution to image classification, in Pytorch

ResMLP - Pytorch Implementation of ResMLP, an all MLP solution to image classification out of Facebook AI, in Pytorch Install $ pip install res-mlp-py

Phil Wang 178 Dec 2, 2022