Le dataset des images du projet d'IA de 2021

Overview

face-mask-dataset-ilc-2021

Le dataset des images du projet d'IA de 2021, Indiquez vos id git dans la issue pour les droits

TL;DR:

  • Choisir 200 images JPEG avec environ 1/3 sans masque, 1/3 avec masque, et 1/3 mal mis
  • Renommer les images avec le hash md5 du fichier
  • Annoter avec labelimg (ou autre pour fichier xml au format PASCAL-VOC)
  • commit sur votre branch "contrib_NOM1_NOM2"
  • Une fois toutes les images annotées, => Pull requests vers branche VALID
  • Le discord ILC est pratique pour échanger

1. Répartition

Les images sont repertoriées en 3 catégories :

  • "with_mask", un masque correctment porté et qui recouvre la bouche et le nez
  • "with_incorrect_mask", un masque porté sous le nez, ou de facon pas très covid-friendly
  • "without_mask, Un visage sans masque

Le dataset doit faire environ 2300 images qui répartit par 23 doit donner environ 100 images à annoter par personne

2. Gestion des images

Les images doivent être traitées de la sorte :

  • Le nom correspond au md5sum du fichier
  • Les masques rajoutés en mode photoshop sont à proscrire pour des raisons de performances
  • on recherche les images similaires par exemple à l’aide du script python compare_images
  • La répartition des images doivent être équilibrés (environ le même nombre d'image dans chaque catégorie à 100 images près)

3. Pour commit

L'idée va être d'avoir une branche "VALID" pour ajouter toutes les images en attentes de validation et de ne garder la branche "main" que pour le résultat final. Pensez à bien mettre renseigner vos avancés dans vos commits et pull request. -> Chaque binome ajoutera sur sa branche "contrib_NOM1_NOM2", et on effectuera un pull request vers la branche "VALID" une fois les 200 images ajoutées et annotées

4. Les outils qui vont bien

  • Pour annoter les images : labelimg
  • Pour trouver les doublons dans les images : Le script "compare_images.py" (run n'importe ou), et lui passer les deux dossier source(les images des autres) et to_add (les votres à ajouter)
  • Pour renommer toutes ses images en leur hash MD5 (A faire avant d'annoter) : le script "rename_dir_md5.py" (à déplacer dans le dossier JPEGImages pour run)
Owner
Jonathan Lignier
Invasive Plant Species Identification

Invasive_Plant_Species_Identification Used LiDAR Odometry and Mapping (LOAM) to create a 3D point cloud map which can be used to identify invasive pla

2 May 12, 2022
Simple and ready-to-use tutorials for TensorFlow

TensorFlow World To support maintaining and upgrading this project, please kindly consider Sponsoring the project developer. Any level of support is a

Amirsina Torfi 4.5k Dec 23, 2022
YOLOv5 🚀 is a family of object detection architectures and models pretrained on the COCO dataset

YOLOv5 🚀 is a family of object detection architectures and models pretrained on the COCO dataset, and represents Ultralytics open-source research int

阿才 73 Dec 16, 2022
Gradient Inversion with Generative Image Prior

Gradient Inversion with Generative Image Prior This repository is an implementation of "Gradient Inversion with Generative Image Prior", accepted to N

MLLab @ Postech 25 Jan 09, 2023
This package implements THOR: Transformer with Stochastic Experts.

THOR: Transformer with Stochastic Experts This PyTorch package implements Taming Sparsely Activated Transformer with Stochastic Experts. Installation

Microsoft 45 Nov 22, 2022
KGDet: Keypoint-Guided Fashion Detection (AAAI 2021)

KGDet: Keypoint-Guided Fashion Detection (AAAI 2021) This is an official implementation of the AAAI-2021 paper "KGDet: Keypoint-Guided Fashion Detecti

Qian Shenhan 35 Dec 29, 2022
Least Square Calibration for Peer Reviews

Least Square Calibration for Peer Reviews Requirements gurobipy - for solving convex programs GPy - for Bayesian baseline numpy pandas To generate p

Sigma <a href=[email protected]"> 1 Nov 01, 2021
A TensorFlow implementation of FCN-8s

FCN-8s implementation in TensorFlow Contents Overview Examples and demo video Dependencies How to use it Download pre-trained VGG-16 Overview This is

Pierluigi Ferrari 50 Aug 08, 2022
DA2Lite is an automated model compression toolkit for PyTorch.

DA2Lite (Deep Architecture to Lite) is a toolkit to compress and accelerate deep network models. ⭐ Star us on GitHub — it helps!! Frameworks & Librari

Sinhan Kang 7 Mar 22, 2022
Housing Price Prediction

This project aim was to predict the price of houses in the Boston area during the great financial crisis through regression, as well as classify houses into different quality categories according to

Florian Klement 1 Jan 27, 2022
Awesome Weak-Shot Learning

Awesome Weak-Shot Learning In weak-shot learning, all categories are split into non-overlapped base categories and novel categories, in which base cat

BCMI 162 Dec 30, 2022
《Dual-Resolution Correspondence Network》(NeurIPS 2020)

Dual-Resolution Correspondence Network Dual-Resolution Correspondence Network, NeurIPS 2020 Dependency All dependencies are included in asset/dualrcne

Active Vision Laboratory 45 Nov 21, 2022
Official PyTorch code of Holistic 3D Scene Understanding from a Single Image with Implicit Representation (CVPR 2021)

Implicit3DUnderstanding (Im3D) [Project Page] Holistic 3D Scene Understanding from a Single Image with Implicit Representation Cheng Zhang, Zhaopeng C

Cheng Zhang 149 Jan 08, 2023
Machine Learning University: Accelerated Computer Vision Class

Machine Learning University: Accelerated Computer Vision Class This repository contains slides, notebooks, and datasets for the Machine Learning Unive

AWS Samples 1.3k Dec 28, 2022
Self-Supervised Generative Style Transfer for One-Shot Medical Image Segmentation

Self-Supervised Generative Style Transfer for One-Shot Medical Image Segmentation This repository contains the Pytorch implementation of the proposed

Devavrat Tomar 19 Nov 10, 2022
PyTorch implementation of Decoupling Value and Policy for Generalization in Reinforcement Learning

PyTorch implementation of Decoupling Value and Policy for Generalization in Reinforcement Learning

48 Dec 08, 2022
SimDeblur is a simple framework for image and video deblurring, implemented by PyTorch

SimDeblur (Simple Deblurring) is an open source framework for image and video deblurring toolbox based on PyTorch, which contains most deep-learning based state-of-the-art deblurring algorithms. It i

220 Jan 07, 2023
Python PID Tuner - Based on a FOPDT model obtained using a Open Loop Process Reaction Curve

PythonPID_Tuner Step 1: Takes a Process Reaction Curve in csv format - assumes data at 100ms interval (column names CV and PV) Step 2: Makes a rough e

6 Jan 14, 2022
An implementation of the [Hierarchical (Sig-Wasserstein) GAN] algorithm for large dimensional Time Series Generation

Hierarchical GAN for large dimensional financial market data Implementation This repository is an implementation of the [Hierarchical (Sig-Wasserstein

11 Nov 29, 2022
Uni-Fold: Training your own deep protein-folding models

Uni-Fold: Training your own deep protein-folding models. This package provides an implementation of a trainable, Transformer-based deep protein foldin

DP Technology 187 Jan 04, 2023