Accuracy Aligned. Concise Implementation of Swin Transformer

Overview

Swin Transformer

Accuracy Aligned. Concise Implementation of Swin Transformer

This repository contains the implementation of Swin Transformer, and the training codes on ImageNet datasets. We have aligned the output of our network with the official one, that is, using the same input and random seed, the output is identical to the official one.

Our implementation is highly based on einops, which makes the implementation more concise, and easy to be understand. (Intuitively, we use only 200 lines of codes compared with ~600 lines of official codes.) Besides, our implementation keeps the same training speed.

Model Epoch [email protected](our) [email protected](our) [email protected](official) [email protected](official) pretrained model
Swin-T 300 81.3 95.5 81.2 95.5 here

Usage

Train on ImageNet:

Train Swin-T

python -m torch.distributed.launch --nproc_per_node=8 --use_env train.py --model Swin_T \
--batch-size 128 --drop-path 0.2 --data-path ~/ILSVRC2012/ --output_dir /data/SwinTransformer_exp/SwinT/

Train Swin-S

python -m torch.distributed.launch --nproc_per_node=8 --use_env train.py --model Swin_S \
--batch-size 128 --drop-path 0.3 --data-path ~/ILSVRC2012/ --output_dir /data/SwinTransformer_exp/SwinS/

Train Swin-B

python -m torch.distributed.launch --nproc_per_node=8 --use_env train.py --model Swin_B \
--batch-size 128 --drop-path 0.5 --data-path ~/ILSVRC2012/ --output_dir /data/SwinTransformer_exp/SwinB/

Reference

The training process involves many training and augmentation tricks, such as stochastic depth, mixup, cutmix and random erasing. I borrow large from Deit (https://github.com/facebookresearch/deit).

Citations

@misc{liu2021swin,
      title={Swin Transformer: Hierarchical Vision Transformer using Shifted Windows}, 
      author={Ze Liu and Yutong Lin and Yue Cao and Han Hu and Yixuan Wei and Zheng Zhang and Stephen Lin and Baining Guo},
      year={2021},
      eprint={2103.14030},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}
Owner
FengWang
FengWang
Vision Transformer and MLP-Mixer Architectures

Vision Transformer and MLP-Mixer Architectures Update (2.7.2021): Added the "When Vision Transformers Outperform ResNets..." paper, and SAM (Sharpness

Google Research 6.4k Jan 04, 2023
Python scripts performing class agnostic object localization using the Object Localization Network model in ONNX.

ONNX Object Localization Network Python scripts performing class agnostic object localization using the Object Localization Network model in ONNX. Ori

Ibai Gorordo 15 Oct 14, 2022
Official Implementation of PCT

Official Implementation of PCT Prerequisites python == 3.8.5 Please make sure you have the following libraries installed: numpy torch=1.4.0 torchvisi

32 Nov 21, 2022
codes for paper Combining Dynamic Local Context Focus and Dependency Cluster Attention for Aspect-level sentiment classification

DLCF-DCA codes for paper Combining Dynamic Local Context Focus and Dependency Cluster Attention for Aspect-level sentiment classification. submitted t

15 Aug 30, 2022
iPOKE: Poking a Still Image for Controlled Stochastic Video Synthesis

iPOKE: Poking a Still Image for Controlled Stochastic Video Synthesis iPOKE: Poking a Still Image for Controlled Stochastic Video Synthesis Andreas Bl

CompVis Heidelberg 36 Dec 25, 2022
The official PyTorch code implementation of "Human Trajectory Prediction via Counterfactual Analysis" in ICCV 2021.

Human Trajectory Prediction via Counterfactual Analysis (CausalHTP) The official PyTorch code implementation of "Human Trajectory Prediction via Count

46 Dec 03, 2022
Code for the ICML 2021 paper: "ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision"

ViLT Code for the paper: "ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision" Install pip install -r requirements.txt pip

Wonjae Kim 922 Jan 01, 2023
DECAF: Deep Extreme Classification with Label Features

DECAF DECAF: Deep Extreme Classification with Label Features @InProceedings{Mittal21, author = "Mittal, A. and Dahiya, K. and Agrawal, S. and Sain

46 Nov 06, 2022
Object tracking and object detection is applied to track golf puts in real time and display stats/games.

Putting_Game Object tracking and object detection is applied to track golf puts in real time and display stats/games. Works best with the Perfect Prac

Max 1 Dec 29, 2021
This package proposes simplified exporting pytorch models to ONNX and TensorRT, and also gives some base interface for model inference.

PyTorch Infer Utils This package proposes simplified exporting pytorch models to ONNX and TensorRT, and also gives some base interface for model infer

Alex Gorodnitskiy 11 Mar 20, 2022
ServiceX Transformer that converts flat ROOT ntuples into columnwise data

ServiceX_Uproot_Transformer ServiceX Transformer that converts flat ROOT ntuples into columnwise data Usage You can invoke the transformer from the co

Vis 0 Jan 20, 2022
PyTorch implementation for paper Neural Marching Cubes.

NMC PyTorch implementation for paper Neural Marching Cubes, Zhiqin Chen, Hao Zhang. Paper | Supplementary Material (to be updated) Citation If you fin

Zhiqin Chen 109 Dec 27, 2022
Fast image augmentation library and an easy-to-use wrapper around other libraries

Albumentations Albumentations is a Python library for image augmentation. Image augmentation is used in deep learning and computer vision tasks to inc

11.4k Jan 09, 2023
Baseline for the Spoofing-aware Speaker Verification Challenge 2022

Introduction This repository contains several materials that supplements the Spoofing-Aware Speaker Verification (SASV) Challenge 2022 including: calc

40 Dec 28, 2022
Proof of concept GnuCash Webinterface

Proof of Concept GnuCash Webinterface This may one day be a something truly great. Milestones [ ] Browse accounts and view transactions [ ] Record sim

Josh 14 Dec 28, 2022
PyTorch - Python + Nim

Master Release Pytorch - Py + Nim A Nim frontend for pytorch, aiming to be mostly auto-generated and internally using ATen. Because Nim compiles to C+

Giovanni Petrantoni 425 Dec 22, 2022
Interpretation of T cell states using reference single-cell atlases

Interpretation of T cell states using reference single-cell atlases ProjecTILs is a computational method to project scRNA-seq data into reference sing

Cancer Systems Immunology Lab 139 Jan 03, 2023
SFD implement with pytorch

S³FD: Single Shot Scale-invariant Face Detector A PyTorch Implementation of Single Shot Scale-invariant Face Detector Description Meanwhile train hand

Jun Li 251 Dec 22, 2022
A script written in Python that returns a consensus string and profile matrix of a given DNA string(s) in FASTA format.

A script written in Python that returns a consensus string and profile matrix of a given DNA string(s) in FASTA format.

Zain 1 Feb 01, 2022