Code for the ICCV 2021 Workshop paper: A Unified Efficient Pyramid Transformer for Semantic Segmentation.

Overview

Unified-EPT

Code for the ICCV 2021 Workshop paper: A Unified Efficient Pyramid Transformer for Semantic Segmentation.

Installation

  • Linux, CUDA>=10.0, GCC>=5.4
  • Python>=3.7
  • Create a conda environment:
    conda create -n unept python=3.7 pip

Then, activate the environment:

    conda activate unept
  • PyTorch>=1.5.1, torchvision>=0.6.1 (following instructions here)

For example:

conda install pytorch==1.5.1 torchvision==0.6.1 cudatoolkit=10.2 -c pytorch
pip install -r requirements.txt

Data Preparation

Please following the code from openseg to generate ground truth for boundary refinement.

The data format should be like this.

ADE20k

You can download the processed dt_offset file here.

path/to/ADEChallengeData2016/
  images/
    training/
    validation/
  annotations/ 
    training/
    validation/
  dt_offset/
    training/
    validation/

PASCAL-Context

You can download the processed dataset here.

path/to/PASCAL-Context/
  train/
    image/
    label/
    dt_offset/
  val/
    image/
    label/
    dt_offset/

Usage

Training

The default is for multi-gpu, DistributedDataParallel training.

python -m torch.distributed.launch --nproc_per_node=8 \ # specify gpu number
--master_port=29500  \
train.py  --launcher pytorch \
--config /path/to/config_file 
  • specify the data_root in the config file;
  • log dir will be created in ./work_dirs;
  • download the DeiT pretrained model and specify the pretrained path in the config file.

Evaluation

# single-gpu testing
python test.py --checkpoint /path/to/checkpoint \
--config /path/to/config_file \
--eval mIoU \
[--out ${RESULT_FILE}] [--show] \
--aug-test \ # for multi-scale flip aug

# multi-gpu testing (4 gpus, 1 sample per gpu)
python -m torch.distributed.launch --nproc_per_node=4 --master_port=29500 \
test.py  --launcher pytorch --eval mIoU \
--config_file /path/to/config_file \
--checkpoint /path/to/checkpoint \
--aug-test \ # for multi-scale flip aug

Results

We report results on validation sets.

Backbone Crop Size Batch Size Dataset Lr schd Mem(GB) mIoU(ms+flip) config
Res-50 480x480 16 ADE20K 160K 7.0G 46.1 config
DeiT 480x480 16 ADE20K 160K 8.5G 50.5 config
DeiT 480x480 16 PASCAL-Context 160K 8.5G 55.2 config

Security

See CONTRIBUTING for more information.

License

This project is licensed under the Apache-2.0 License.

Citation

If you use this code and models for your research, please consider citing:

@article{zhu2021unified,
  title={A Unified Efficient Pyramid Transformer for Semantic Segmentation},
  author={Zhu, Fangrui and Zhu, Yi and Zhang, Li and Wu, Chongruo and Fu, Yanwei and Li, Mu},
  journal={arXiv preprint arXiv:2107.14209},
  year={2021}
}

Acknowledgment

We thank the authors and contributors of MMCV, MMSegmentation, timm and Deformable DETR.

Code base for the paper "Scalable One-Pass Optimisation of High-Dimensional Weight-Update Hyperparameters by Implicit Differentiation"

This repository contains code for the paper Scalable One-Pass Optimisation of High-Dimensional Weight-Update Hyperparameters by Implicit Differentiati

8 Aug 28, 2022
Python implementation of Lightning-rod Agent, the Stack4Things board-side probe

Iotronic Lightning-rod Agent Python implementation of Lightning-rod Agent, the Stack4Things board-side probe. Free software: Apache 2.0 license Websit

2 May 19, 2022
Ray tracing of a Schwarzschild black hole written entirely in TensorFlow.

TensorGeodesic Ray tracing of a Schwarzschild black hole written entirely in TensorFlow. Dependencies: Python 3 TensorFlow 2.x numpy matplotlib About

5 Jan 15, 2022
Implementation of Uformer, Attention-based Unet, in Pytorch

Uformer - Pytorch Implementation of Uformer, Attention-based Unet, in Pytorch. It will only offer the concat-cross-skip connection. This repository wi

Phil Wang 72 Dec 19, 2022
MatchGAN: A Self-supervised Semi-supervised Conditional Generative Adversarial Network

MatchGAN: A Self-supervised Semi-supervised Conditional Generative Adversarial Network This repository is the official implementation of MatchGAN: A S

Justin Sun 12 Dec 27, 2022
Invariant Causal Prediction for Block MDPs

MISA Abstract Generalization across environments is critical to the successful application of reinforcement learning algorithms to real-world challeng

Meta Research 41 Sep 17, 2022
Pseudo-Visual Speech Denoising

Pseudo-Visual Speech Denoising This code is for our paper titled: Visual Speech Enhancement Without A Real Visual Stream published at WACV 2021. Autho

Sindhu 94 Oct 22, 2022
FairEdit: Preserving Fairness in Graph Neural Networks through Greedy Graph Editing

FairEdit Relevent Publication FairEdit: Preserving Fairness in Graph Neural Networks through Greedy Graph Editing

5 Feb 04, 2022
HeatNet is a python package that provides tools to build, train and evaluate neural networks designed to predict extreme heat wave events globally on daily to subseasonal timescales.

HeatNet HeatNet is a python package that provides tools to build, train and evaluate neural networks designed to predict extreme heat wave events glob

Google Research 6 Jul 07, 2022
The codes and related files to reproduce the results for Image Similarity Challenge Track 2.

ISC-Track2-Submission The codes and related files to reproduce the results for Image Similarity Challenge Track 2. Required dependencies To begin with

Wenhao Wang 89 Jan 02, 2023
Optimal Camera Position for a Practical Application of Gaze Estimation on Edge Devices,

Optimal Camera Position for a Practical Application of Gaze Estimation on Edge Devices, Linh Van Ma, Tin Trung Tran, Moongu Jeon, ICAIIC 2022 (The 4th

Linh 11 Oct 10, 2022
Can we learn gradients by Hamiltonian Neural Networks?

Can we learn gradients by Hamiltonian Neural Networks? This project was carried out as part of the Optimization for Machine Learning course (CS-439) a

2 Aug 22, 2022
Cancer Drug Response Prediction via a Hybrid Graph Convolutional Network

DeepCDR Cancer Drug Response Prediction via a Hybrid Graph Convolutional Network This work has been accepted to ECCB2020 and was also published in the

Qiao Liu 50 Dec 18, 2022
Official Implementation of "Transformers Can Do Bayesian Inference"

Official Code for the Paper "Transformers Can Do Bayesian Inference" We train Transformers to do Bayesian Prediction on novel datasets for a large var

AutoML-Freiburg-Hannover 103 Dec 25, 2022
My personal code and solution to the Synacor Challenge from 2012 OSCON.

Synacor OSCON Challenge Solution (2012) This repository contains my code and solution to solve the Synacor OSCON 2012 Challenge. If you are interested

2 Mar 20, 2022
Deep Learning Based Fasion Recommendation System for Ecommerce

Project Name: Fasion Recommendation System for Ecommerce A Deep learning based streamlit web app which can recommened you various types of fasion prod

BAPPY AHMED 13 Dec 13, 2022
Team Enigma at ArgMining 2021 Shared Task: Leveraging Pretrained Language Models for Key Point Matching

Team Enigma at ArgMining 2021 Shared Task: Leveraging Pretrained Language Models for Key Point Matching This is our attempt of the shared task on Quan

Manav Nitin Kapadnis 12 Jul 08, 2022
A Python implementation of the Locality Preserving Matching (LPM) method for pruning outliers in image matching.

LPM_Python A Python implementation of the Locality Preserving Matching (LPM) method for pruning outliers in image matching. The code is established ac

AoxiangFan 11 Nov 07, 2022
Satellite labelling tool for manual labelling of storm top features such as overshooting tops, above-anvil plumes, cold U/Vs, rings etc.

Satellite labelling tool About this app A tool for manual labelling of storm top features such as overshooting tops, above-anvil plumes, cold U/Vs, ri

Czech Hydrometeorological Institute - Satellite Department 10 Sep 14, 2022
Multi-Scale Geometric Consistency Guided Multi-View Stereo

ACMM [News] The code for ACMH is released!!! [News] The code for ACMP is released!!! About ACMM is a multi-scale geometric consistency guided multi-vi

Qingshan Xu 118 Jan 04, 2023