Bunch of different tools which helps visualizing and annotating images for semantic/instance segmentation tasks

Overview

Data Framework for Semantic/Instance Segmentation

Bunch of different tools which helps visualizing, transforming and annotating images for semantic/instance segmentation tasks. Check each folder to find these different tools.

Ground Truth Generation

Labeling tool that creates masks for your semantic segmentation problem. It uses watershed algorithm to boost annotation speed.

Ground Truth Generation with Object Detection

Labeling tool that leverages some Object Detection Model which already give the masks for your problem. Then you just need to assign the classes for each generated mask (check inside the folder for more details).

Ground Truth Analysis

Checks class histogram from a semantic segmentation dataset and verify images size distribution.

Data Inspection

Go through your whole dataset and choose which images are good or bad. This is a very important tool if you need clean data and wants to build a project with Data-Centric approach.

Dataset Stratification

Multi label dataset stratification can be really hard to execute. I propose a simple approach that keeps the class balance of your trainset and testset.

Class weights

If your dataset suffers from class imbalance, you need to calculate the weights if you want to apply them to your loss function or your Dataloader Sampler.

Any question you can get in contact

Linkedin: https://www.linkedin.com/in/brunofcarvalho1996/ Email: [email protected]

Owner
Bruno Fernandes Carvalho
Mechatronic Engineer specialized in Artificial Intelligence. Always searching for knowlegde and seeking to understand things from different areas of science.
Bruno Fernandes Carvalho
Exploring Simple Siamese Representation Learning

G-SimSiam A PyTorch implementation which refers to repo for the paper Exploring Simple Siamese Representation Learning by Xinlei Chen & Kaiming He Add

zhuyun 1 Dec 19, 2021
Code for Environment Inference for Invariant Learning (ICML 2020 UDL Workshop Paper)

Environment Inference for Invariant Learning This code accompanies the paper Environment Inference for Invariant Learning, which appears at ICML 2021.

Elliot Creager 40 Dec 09, 2022
Old Photo Restoration (Official PyTorch Implementation)

Bringing Old Photo Back to Life (CVPR 2020 oral)

Microsoft 11.3k Dec 30, 2022
XtremeDistil framework for distilling/compressing massive multilingual neural network models to tiny and efficient models for AI at scale

XtremeDistilTransformers for Distilling Massive Multilingual Neural Networks ACL 2020 Microsoft Research [Paper] [Video] Releasing [XtremeDistilTransf

Microsoft 125 Jan 04, 2023
Learning to Adapt Structured Output Space for Semantic Segmentation, CVPR 2018 (spotlight)

Learning to Adapt Structured Output Space for Semantic Segmentation Pytorch implementation of our method for adapting semantic segmentation from the s

Yi-Hsuan Tsai 782 Dec 30, 2022
Reproduced Code for Image Forgery Detection papers.

Image Forgery Detection With over 4.5 billion active internet users, the amount of multimedia content being shared every day has surpassed everyone’s

Umar Masud 15 Dec 06, 2022
House_prices_kaggle - Predict sales prices and practice feature engineering, RFs, and gradient boosting

House Prices - Advanced Regression Techniques Predicting House Prices with Machine Learning This project is build to enhance my knowledge about machin

Gurpreet Singh 1 Jan 01, 2022
Official implementation of "A Shared Representation for Photorealistic Driving Simulators" in PyTorch.

A Shared Representation for Photorealistic Driving Simulators The official code for the paper: "A Shared Representation for Photorealistic Driving Sim

VITA lab at EPFL 7 Oct 13, 2022
An implementation of chunked, compressed, N-dimensional arrays for Python.

Zarr Latest Release Package Status License Build Status Coverage Downloads Gitter Citation What is it? Zarr is a Python package providing an implement

Zarr Developers 1.1k Dec 30, 2022
Replication Code for "Self-Supervised Bug Detection and Repair" NeurIPS 2021

Self-Supervised Bug Detection and Repair This is the reference code to replicate the research in Self-Supervised Bug Detection and Repair in NeurIPS 2

Microsoft 85 Dec 24, 2022
SberSwap Video Swap base on deep learning

SberSwap Video Swap base on deep learning

Sber AI 431 Jan 03, 2023
Prometheus exporter for Cisco Unified Computing System (UCS) Manager

prometheus-ucs-exporter Overview Use metrics from the UCS API to export relevant metrics to Prometheus This repository is a fork of Drew Stinnett's or

Marshall Wace 6 Nov 07, 2022
Grammar Induction using a Template Tree Approach

Gitta Gitta ("Grammar Induction using a Template Tree Approach") is a method for inducing context-free grammars. It performs particularly well on data

Thomas Winters 36 Nov 15, 2022
Do Smart Glasses Dream of Sentimental Visions? Deep Emotionship Analysis for Eyewear Devices

EMOShip This repository contains the EMO-Film dataset described in the paper "Do Smart Glasses Dream of Sentimental Visions? Deep Emotionship Analysis

1 Nov 18, 2022
Square Root Bundle Adjustment for Large-Scale Reconstruction

RootBA: Square Root Bundle Adjustment Project Page | Paper | Poster | Video | Code Table of Contents Citation Dependencies Installing dependencies on

Nikolaus Demmel 205 Dec 20, 2022
LSTM model trained on a small dataset of 3000 names written in PyTorch

LSTM model trained on a small dataset of 3000 names. Model generates names from model by selecting one out of top 3 letters suggested by model at a time until an EOS (End Of Sentence) character is no

Sahil Lamba 1 Dec 20, 2021
[SIGGRAPH 2022 Journal Track] AvatarCLIP: Zero-Shot Text-Driven Generation and Animation of 3D Avatars

AvatarCLIP: Zero-Shot Text-Driven Generation and Animation of 3D Avatars Fangzhou Hong1*  Mingyuan Zhang1*  Liang Pan1  Zhongang Cai1,2,3  Lei Yang2 

Fangzhou Hong 749 Jan 04, 2023
This repository holds code and data for our PETS'22 article 'From "Onion Not Found" to Guard Discovery'.

From "Onion Not Found" to Guard Discovery (PETS'22) This repository holds the code and data for our PETS'22 paper titled 'From "Onion Not Found" to Gu

Lennart Oldenburg 3 May 04, 2022
This is an official implementation for "Self-Supervised Learning with Swin Transformers".

Self-Supervised Learning with Vision Transformers By Zhenda Xie*, Yutong Lin*, Zhuliang Yao, Zheng Zhang, Qi Dai, Yue Cao and Han Hu This repo is the

Swin Transformer 529 Jan 02, 2023
This is the code repository for the paper A hierarchical semantic segmentation framework for computer-vision-based bridge column damage detection

Bridge-damage-segmentation This is the code repository for the paper A hierarchical semantic segmentation framework for computer-vision-based bridge c

Jingxiao Liu 5 Dec 07, 2022