Knowledge Distillation Toolbox for Semantic Segmentation

Overview

SegDistill: Toolbox for Knowledge Distillation on Semantic Segmentation Networks

This repo contains the supported code and configuration files for SegDistill .It is based on mmsegmentaion.

Installation

conda create -n mmcv python=3.8 -y
conda activate mmcv

pip install torch==1.7.1+cu110 torchvision==0.8.2+cu110 torchaudio==0.7.2 -f https://download.pytorch.org/whl/torch_stable.html

pip install mmcv-full==1.2.2 -f https://download.openmmlab.com/mmcv/dist/cu110/torch1.7.0/index.html

pip install future tensorboard
pip install IPython
pip install attr
pip install timm

git clone https://github.com/wzpscott/SegDistill.git -b main
cd SegDistill
pip install -e .

Prepare Data

We conducted experiments on ADE20k dataset. The training and validation set of ADE20K could be download from this link. Test set can be download from here. After downloading the dataset, you need to arrange the structure of your dataset like:

mmsegmentation
├── mmseg
├── tools
├── configs
├── data
│   ├── ade
│   │   ├── ADEChallengeData2016
│   │   │   ├── annotations
│   │   │   │   ├── training
│   │   │   │   ├── validation
│   │   │   ├── images
│   │   │   │   ├── training
│   │   │   │   ├── validation
│   ├── ...

See here for more instructions on data preparation.

Prepare Models

We provide links to pretrained weights of models used in the paper.

Model Pretrained on ImageNet-1K Trained on ADE20k
Segformer link link
Swin-Transformer link link
PSPNet link link

Write configs for semantic segmentaion KD

We use mmcv-fashion configs to control the KD process.

Run an example config with the following command:

 bash tools/dist_train.sh distillation_configs/example_config.py {num_gpu}

See here for detailed instructions for custom KD process on various network architectures.

Channel Group Distillation

Our Channel Group Distillation (CGD) considers a more extensive range of correlations inthe activation map and works well fortransformer structures than previous KD methods.

Comparison to Other KD methods

Comparison to Other KD methods

Results on ADE20k

Qualitative segmentation results on ADE20k produced from Segformer B0: (a) raw images, (b) ground truth (GT), (c) outputof the original student model (d) Channel-wise Distillation (CD) and (e) Channel Group Distillation(CGD) Qualitative segmentation results

The CLRS Algorithmic Reasoning Benchmark

Learning representations of algorithms is an emerging area of machine learning, seeking to bridge concepts from neural networks with classical algorithms.

DeepMind 251 Jan 05, 2023
PrimitiveNet: Primitive Instance Segmentation with Local Primitive Embedding under Adversarial Metric (ICCV 2021)

PrimitiveNet Source code for the paper: Jingwei Huang, Yanfeng Zhang, Mingwei Sun. [PrimitiveNet: Primitive Instance Segmentation with Local Primitive

Jingwei Huang 47 Dec 06, 2022
HiFT: Hierarchical Feature Transformer for Aerial Tracking (ICCV2021)

HiFT: Hierarchical Feature Transformer for Aerial Tracking Ziang Cao, Changhong Fu, Junjie Ye, Bowen Li, and Yiming Li Our paper is Accepted by ICCV 2

Intelligent Vision for Robotics in Complex Environment 55 Nov 23, 2022
This is the official pytorch implementation of Student Helping Teacher: Teacher Evolution via Self-Knowledge Distillation(TESKD)

Student Helping Teacher: Teacher Evolution via Self-Knowledge Distillation (TESKD) By Zheng Li[1,4], Xiang Li[2], Lingfeng Yang[2,4], Jian Yang[2], Zh

Zheng Li 9 Sep 26, 2022
PyTorch implementation for our paper Learning Character-Agnostic Motion for Motion Retargeting in 2D, SIGGRAPH 2019

Learning Character-Agnostic Motion for Motion Retargeting in 2D We provide PyTorch implementation for our paper Learning Character-Agnostic Motion for

Rundi Wu 367 Dec 22, 2022
Anomaly detection in multi-agent trajectories: Code for training, evaluation and the OpenAI highway simulation.

Anomaly Detection in Multi-Agent Trajectories for Automated Driving This is the official project page including the paper, code, simulation, baseline

12 Dec 02, 2022
Train SN-GAN with AdaBelief

SNGAN-AdaBelief Train a state-of-the-art spectral normalization GAN with AdaBelief https://github.com/juntang-zhuang/Adabelief-Optimizer Acknowledgeme

Juntang Zhuang 10 Jun 11, 2022
CryptoFrog - My First Strategy for freqtrade

cryptofrog-strategies CryptoFrog - My First Strategy for freqtrade NB: (2021-04-20) You'll need the latest freqtrade develop branch otherwise you migh

Robert Davey 137 Jan 01, 2023
This repository contains the code to replicate the analysis from the paper "Moving On - Investigating Inventors' Ethnic Origins Using Supervised Learning"

Replication Code for 'Moving On' - Investigating Inventors' Ethnic Origins Using Supervised Learning This repository contains the code to replicate th

Matthias Niggli 0 Jan 04, 2022
Lighthouse: Predicting Lighting Volumes for Spatially-Coherent Illumination

Lighthouse: Predicting Lighting Volumes for Spatially-Coherent Illumination Pratul P. Srinivasan, Ben Mildenhall, Matthew Tancik, Jonathan T. Barron,

Pratul Srinivasan 65 Dec 14, 2022
Semi-supervised Semantic Segmentation with Directional Context-aware Consistency (CVPR 2021)

Semi-supervised Semantic Segmentation with Directional Context-aware Consistency (CAC) Xin Lai*, Zhuotao Tian*, Li Jiang, Shu Liu, Hengshuang Zhao, Li

Jia Research Lab 137 Dec 14, 2022
Learning Confidence for Out-of-Distribution Detection in Neural Networks

Learning Confidence Estimates for Neural Networks This repository contains the code for the paper Learning Confidence for Out-of-Distribution Detectio

235 Jan 05, 2023
Torch-based tool for quantizing high-dimensional vectors using additive codebooks

Trainable multi-codebook quantization This repository implements a utility for use with PyTorch, and ideally GPUs, for training an efficient quantizer

Daniel Povey 41 Jan 07, 2023
Streamlit App For Product Analysis - Streamlit App For Product Analysis

Streamlit_App_For_Product_Analysis Здравствуйте! Перед вами дашборд, позволяющий

Grigory Sirotkin 1 Jan 10, 2022
Tensorflow implementation of Fully Convolutional Networks for Semantic Segmentation

FCN.tensorflow Tensorflow implementation of Fully Convolutional Networks for Semantic Segmentation (FCNs). The implementation is largely based on the

Sarath Shekkizhar 1.3k Dec 25, 2022
Official code for paper Exemplar Based 3D Portrait Stylization.

3D-Portrait-Stylization This is the official code for the paper "Exemplar Based 3D Portrait Stylization". You can check the paper on our project websi

60 Dec 07, 2022
This repo is about to create the Streamlit application for given ML model.

HR-Attritiion-using-Streamlit This repo is about to create the Streamlit application for given ML model. Problem Statement: Managing peoples at workpl

Pavan Giri 0 Dec 10, 2021
A Kaggle competition: discriminate gender based on handwriting

Gender discrimination based on handwriting See http://fastml.com/gender-discrimination/ for description. prep_data.py - a first step chunk_by_authors.

Zygmunt Zając 22 Jul 20, 2022
Advantage Actor Critic (A2C): jax + flax implementation

Advantage Actor Critic (A2C): jax + flax implementation Current version supports only environments with continious action spaces and was tested on muj

Andrey 3 Jan 23, 2022
A Transformer-Based Feature Segmentation and Region Alignment Method For UAV-View Geo-Localization

University1652-Baseline [Paper] [Slide] [Explore Drone-view Data] [Explore Satellite-view Data] [Explore Street-view Data] [Video Sample] [中文介绍] This

Zhedong Zheng 335 Jan 06, 2023