FedCV: A Federated Learning Framework for Diverse Computer Vision Tasks

Related tags

Deep LearningFedCV
Overview

FedCV: A Federated Learning Framework for Diverse Computer Vision Tasks

Image Classification

Dataset: Google Landmark, COCO, ImageNet

Model: EfficientNetB0, MobileNetV3

Object Detection

Dataset: COCO

Model: YoLoV5

Google Doc: https://docs.google.com/document/d/1AU-3XT5vLKjLjvOOcdfPfTDwnww1C3xEaroA94pKaWU/edit#heading=h.xldeyzrvdr99

Image Segmentation

Dataset: COCO (Pretraining), Pascal (Fine-Tuning)

Model: DeepLabV3+, U-Net

https://docs.google.com/document/d/1TJi3os3oRQlm6rIwoYfHjUA80M_9IQZ0_iRApuRs4s8/edit

Installation

http://doc.fedml.ai/#/installation

After the clone of this repository, please run the following command to get FedML submodule to your local.

mkdir FedML
cd FedML
git submodule init
git submodule update

Code Structure of FedCV

  • FedML: a soft repository link generated using git submodule add https://github.com/FedML-AI/FedML.

  • data: provide data downloading scripts and store the downloaded datasets. Note that in FedML/data, there also exists datasets for research, but these datasets are used for evaluating federated optimizers (e.g., FedAvg) and platforms. FedNLP supports more advanced datasets and models.

  • data_preprocessing: data loaders

  • model: advanced CV models.

  • trainer: please define your own trainer.py by inheriting the base class in FedML/fedml-core/trainer/fedavg_trainer.py. Some tasks can share the same trainer.

  • experiments/distributed:

  1. experiments is the entry point for training. It contains experiments in different platforms. We start from distributed.
  2. Every experiment integrates FOUR building blocks FedML (federated optimizers), data_preprocessing, model, trainer.
  3. To develop new experiments, please refer the code at experiments/distributed/text-classification.
  • experiments/centralized:
  1. please provide centralized training script in this directory.
  2. This is used to get the reference model accuracy for FL.
  3. You may need to accelerate your training through distributed training on multi-GPUs and multi-machines. Please refer the code at experiments/centralized/DDP_demo.

Update FedML Submodule

cd FedML
git checkout master && git pull
cd ..
git add FedML
git commit -m "#<issue_id> - updating submodule FedML to latest"
git push
Owner
FedML-AI
FedML: A Research Library and Benchmark for Federated Machine Learning
FedML-AI
Source code for CAST - Crisis Domain Adaptation Using Sequence-to-sequence Transformers (Accepted to ISCRAM 2021, CorePaper).

Source code for CAST: Crisis Domain Adaptation UsingSequence-to-sequenceTransformers (Paper, BibTeX, Accepted to ISCRAM 2021, CorePaper) Quick start D

Congcong Wang 0 Jul 14, 2021
Fast Style Transfer in TensorFlow

Fast Style Transfer in TensorFlow Add styles from famous paintings to any photo in a fraction of a second! You can even style videos! It takes 100ms o

Jefferson 5 Oct 24, 2021
Normalization Calibration (NorCal) for Long-Tailed Object Detection and Instance Segmentation

NorCal Normalization Calibration (NorCal) for Long-Tailed Object Detection and Instance Segmentation On Model Calibration for Long-Tailed Object Detec

Tai-Yu (Daniel) Pan 24 Dec 25, 2022
Multi-Task Temporal Shift Attention Networks for On-Device Contactless Vitals Measurement (NeurIPS 2020)

MTTS-CAN: Multi-Task Temporal Shift Attention Networks for On-Device Contactless Vitals Measurement Paper Xin Liu, Josh Fromm, Shwetak Patel, Daniel M

Xin Liu 106 Dec 30, 2022
PyGCL: Graph Contrastive Learning Library for PyTorch

PyGCL: Graph Contrastive Learning for PyTorch PyGCL is an open-source library for graph contrastive learning (GCL), which features modularized GCL com

GCL: Graph Contrastive Learning Library for PyTorch 594 Jan 08, 2023
AI4Good project for detecting waste in the environment

Detect waste AI4Good project for detecting waste in environment. www.detectwaste.ml. Our latest results were published in Waste Management journal in

108 Dec 25, 2022
Official pytorch implementation of Active Learning for deep object detection via probabilistic modeling (ICCV 2021)

Active Learning for Deep Object Detection via Probabilistic Modeling This repository is the official PyTorch implementation of Active Learning for Dee

NVIDIA Research Projects 130 Jan 06, 2023
PyTorch Implementation of Small Lesion Segmentation in Brain MRIs with Subpixel Embedding (ORAL, MICCAIW 2021)

Small Lesion Segmentation in Brain MRIs with Subpixel Embedding PyTorch implementation of Small Lesion Segmentation in Brain MRIs with Subpixel Embedd

22 Oct 21, 2022
Quantile Regression DQN a Minimal Working Example, Distributional Reinforcement Learning with Quantile Regression

Quantile Regression DQN Quantile Regression DQN a Minimal Working Example, Distributional Reinforcement Learning with Quantile Regression (https://arx

Arsenii Senya Ashukha 80 Sep 17, 2022
This repo is to present various code demos on how to use our Graph4NLP library.

Deep Learning on Graphs for Natural Language Processing Demo The repository contains code examples for DLG4NLP tutorials at NAACL 2021, SIGIR 2021, KD

Graph4AI 143 Dec 23, 2022
Model of an AI powered sign language interpreter.

TEXT AND SPEECH TO SIGN LANGUAGE. A web application which takes in text or live audio speech recording as input, converts and displays the relevant Si

Mark Gatere 4 Mar 30, 2022
Code for "Solving Graph-based Public Good Games with Tree Search and Imitation Learning"

Code for "Solving Graph-based Public Good Games with Tree Search and Imitation Learning" This is the code for the paper Solving Graph-based Public Goo

Victor-Alexandru Darvariu 3 Dec 05, 2022
Hierarchical Attentive Recurrent Tracking

Hierarchical Attentive Recurrent Tracking This is an official Tensorflow implementation of single object tracking in videos by using hierarchical atte

Adam Kosiorek 147 Aug 07, 2021
A pytorch implementation of the CVPR2021 paper "VSPW: A Large-scale Dataset for Video Scene Parsing in the Wild"

VSPW: A Large-scale Dataset for Video Scene Parsing in the Wild A pytorch implementation of the CVPR2021 paper "VSPW: A Large-scale Dataset for Video

45 Nov 29, 2022
Scalable and Elastic Deep Reinforcement Learning Using PyTorch. Please star. πŸ”₯

ElegantRL β€œε°ι›…β€: Scalable and Elastic Deep Reinforcement Learning ElegantRL is developed for researchers and practitioners with the following advantage

AI4Finance Foundation 2.5k Jan 05, 2023
Full Resolution Residual Networks for Semantic Image Segmentation

Full-Resolution Residual Networks (FRRN) This repository contains code to train and qualitatively evaluate Full-Resolution Residual Networks (FRRNs) a

Toby Pohlen 274 Oct 27, 2022
SlotRefine: A Fast Non-Autoregressive Model forJoint Intent Detection and Slot Filling

SlotRefine: A Fast Non-Autoregressive Model for Joint Intent Detection and Slot Filling Reference Main paper to be cited (Di Wu et al., 2020) @article

Moore 34 Nov 03, 2022
πŸ€– Project template for your next awesome AI project. 🦾

πŸ€– AI Awesome Project Template πŸ‘‹ Template author You may want to adjust badge links in a README.md file. πŸ’Ž Installation with pip Installation is as

Wiktor Łazarski 18 Nov 23, 2022
Introduction to AI assignment 1 HCM University of Technology, term 211

Sokoban Bot Introduction to AI assignment 1 HCM University of Technology, term 211 Abstract This is basically a solver for Sokoban game using Breadth-

Quang Minh 4 Dec 12, 2022
Code for "Learning Skeletal Graph Neural Networks for Hard 3D Pose Estimation" ICCV'21

Skeletal-GNN Code for "Learning Skeletal Graph Neural Networks for Hard 3D Pose Estimation" ICCV'21 Various deep learning techniques have been propose

37 Oct 23, 2022