sssegmentation is a general framework for our research on strongly supervised semantic segmentation.

Last update: Jan 02, 2023

Overview

Introduction

sssegmentation is a general framework for our research on strongly supervised semantic segmentation.

Documents

In English

https://sssegmentation.readthedocs.io/en/latest/

Supported

Supported Backbones

Supported Models

Supported Datasets

Citation

If you use this framework in your research, please cite this project.

@misc{ssseg2020,
    author = {Zhenchao Jin},
    title = {SSSegmentation: A general framework for strongly supervised semantic segmentation},
    year = {2020},
    publisher = {GitHub},
    journal = {GitHub repository},
    howpublished = {\url{https://github.com/SegmentationBLWX/sssegmentation}},
}

References

[1]. https://github.com/open-mmlab/mmcv
[2]. https://github.com/open-mmlab/mmsegmentation

Comments

Training on custom dataset with 4 channels

Hi, I want to train my own dataset which has images in 4 channels - RGB images and IR(infrared) images. Could you help me out with that? How can i modify the codes of this repo to accommodate that extra channel?

opened by cspearl 4
how to train with multi-gpu in one machine

hi，i wanna train the model with 4 gpus in one machine however, your code 'distrain.sh' and 'train.py' can only train with distributed mode in multi-machine how can i modify the code ?

opened by Kenneth-X 3
isnet:imagelevel.py

imagelevel.py : 47: feats_il = self.correlate_net(x, torch.cat([x_global, x], dim=1))

isanet.py： 47：context = super(SelfAttentionBlock, self).forward(x, x)

is there any problem？ bug？

opened by shujunyy123 3
How to modify parameters to use single card training?

How to modify parameters to use single card training?

In addition to modifying the following in config:

SEGMENTOR_CFG.update(distributed{'is_on':False})

opened by kakamie 1
SWIN-B with DeepLabv3+ training on custom dataset

Hi, I am learning about Segmentation and want to try out the segmentation my custom data set. Could you please provide steps on how to use supported backbones with some particular architectures?

If I want to use SWIN-B as my backbone on DeepLabV3+ using a custom dataset, what should be the commands and all. I could not find anything on the docs and on the github page. Could you please help.

opened by deshwalmahesh 1
Is there should be 'continue'?

https://github.com/SegmentationBLWX/sssegmentation/blob/7a405b1a4949606deae067223ebd68cceec6b225/ssseg/modules/models/memorynet/memory.py#L176

If there are more than one 'num_feats_per_cls' in the furture, 'break' will make this for loop only update the first memory_feature?

opened by EricKani 1
医学图像分割也很有意义，我想给你一些公开的医学图像数据集。哈哈哈哈
Hi @CharlesPikachu ！UNet 也是大名鼎鼎的分割模型啊，它在医学图像分割领域是 SOTA，个人认为 Supported Models 列表里应该有名字，而且应该在 FCN 之后。哈哈哈 🥇

虽然 PyTorch Hub 已经有预训练的 UNet 了，但我想要皮卡丘也有！ 🛩️

这里提供一些医学数据集给你参考：

PyTorch Hub 里预训练 UNet 的数据集：LGG Segmentation Dataset

DDTI，已经按照下一个数据集的格式预处理过，百度网盘提取码：qxds

tn-scui2020，来自比赛 tn-scui2020

百度 AI Studio 医学影像数据集集锦

List of Medical Datasets，来自 GitHub
opened by S-HuaBomb 1

Releases(v1.0.0)

Owner

GitHub Repository

A few stylization coreML models that I've trained with CreateML

CoreML-StyleTransfer A few stylization coreML models that I've trained with CreateML You can open and use the .mlmodel files in the "models" folder in

8 Aug 18, 2022

Source code for our paper "Do Not Trust Prediction Scores for Membership Inference Attacks"

Do Not Trust Prediction Scores for Membership Inference Attacks Abstract: Membership inference attacks (MIAs) aim to determine whether a specific samp

[email protected]"> 3 Oct 25, 2022

C3DPO - Canonical 3D Pose Networks for Non-rigid Structure From Motion.

C3DPO: Canonical 3D Pose Networks for Non-Rigid Structure From Motion By: David Novotny, Nikhila Ravi, Benjamin Graham, Natalia Neverova, Andrea Vedal

309 Dec 16, 2022

GT4SD, an open-source library to accelerate hypothesis generation in the scientific discovery process.

The GT4SD (Generative Toolkit for Scientific Discovery) is an open-source platform to accelerate hypothesis generation in the scientific discovery process. It provides a library for making state-of-t

142 Dec 24, 2022

Efficient-GlobalPointer - Pytorch Efficient GlobalPointer

引言感谢苏神带来的模型，原文地址：https://spaces.ac.cn/archives/8877 如何运行对应模型EfficientGlobalPoi

40 Dec 14, 2022

Human Pose Detection on EdgeTPU

Coral PoseNet Pose estimation refers to computer vision techniques that detect human figures in images and video, so that one could determine, for exa

476 Dec 31, 2022

[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

749 Jan 04, 2023

Official PyTorch implementation of the paper "Self-Supervised Relational Reasoning for Representation Learning", NeurIPS 2020 Spotlight.

Official PyTorch implementation of the paper: "Self-Supervised Relational Reasoning for Representation Learning" (2020), Patacchiola, M., and Storkey,

135 Jan 03, 2023

PyTorch implementation of the supervised learning experiments from the paper Model-Agnostic Meta-Learning (MAML)

pytorch-maml This is a PyTorch implementation of the supervised learning experiments from the paper Model-Agnostic Meta-Learning (MAML): https://arxiv

516 Jan 05, 2023

Code for NAACL 2021 full paper "Efficient Attentions for Long Document Summarization"

LongDocSum Code for NAACL 2021 paper "Efficient Attentions for Long Document Summarization" This repository contains data and models needed to reprodu

56 Jan 02, 2023

From a body shape, infer the anatomic skeleton.

OSSO: Obtaining Skeletal Shape from Outside (CVPR 2022) This repository contains the official implementation of the skeleton inference from: OSSO: Obt

166 Dec 28, 2022

Contrastive unpaired image-to-image translation, faster and lighter training than cyclegan (ECCV 2020, in PyTorch)

Contrastive Unpaired Translation (CUT) video (1m) | video (10m) | website | paper We provide our PyTorch implementation of unpaired image-to-image tra

1.7k Dec 27, 2022

A chemical analysis of lipophilicities & molecule drawings including ML

A chemical analysis of lipophilicity & molecule drawings including a bit of ML analysis. This is a simple project that includes two Jupyter files (one

7 Nov 22, 2022

A Python implementation of active inference for Markov Decision Processes

A Python package for simulating Active Inference agents in Markov Decision Process environments. Please see our companion preprint on arxiv for an ove

235 Dec 21, 2022

A new version of the CIDACS-RL linkage tool suitable to a cluster computing environment.

Fully Distributed CIDACS-RL The CIDACS-RL is a brazillian record linkage tool suitable to integrate large amount of data with high accuracy. However,

5 Nov 04, 2022

Fast and scalable uncertainty quantification for neural molecular property prediction, accelerated optimization, and guided virtual screening.

Evidential Deep Learning for Guided Molecular Property Prediction and Discovery Ava Soleimany*, Alexander Amini*, Samuel Goldman*, Daniela Rus, Sangee

75 Dec 15, 2022