training script for space time memory network

Overview

Trainig Script for Space Time Memory Network

This codebase implemented training code for Space Time Memory Network with some cyclic features.

sample results

Requirement

python package

  • torch
  • python-opencv
  • pillow
  • yaml
  • imgaug
  • yacs
  • progress
  • nvidia-dali (optional)

GPU support

  • GPU Memory >= 12GB
  • CUDA >= 10.0

Data

See the doc DATASET.md for more details on data organization of our prepared dataset.

Release

We provide pre-trained model with different backbone in our codebase, results are validated on DAVIS17-val with gradient correction.

model backbone data backend J F J & F link FPS
STM-Cycle Resnet18 DALI 65.3 70.8 68.1 Google Drive 14.8
STM-Cycle Resnet50 PIL 70.5 76.3 73.4 Google Drive 9.3

Runing

Appending the root folder to the search path of python interpreter

export PYTHONPATH=${PYTHONPATH}:./

To train the STM network, run following command.

python3 train.py --cfg config.yaml OPTION_KEY OPTION_VAL

To test the STM network, run following command

python3 test.py --cfg config.yaml initial ${PATH_TO_MODEL} OPTION_KEY OPTION_VAL

The test results will be saved as indexed png file at ${ROOT}/${output_dir}/${valset}.

To run a segmentation demo, run following command

python3 demo/demo.py --cfg demo/demo.yaml OPTION_KEY OPTION_VAL

The segmentation results will be saved at ${output_dir}.

Acknowledgement

This codebase borrows the code and structure from official STM repository

Reference

The codebase is built based on following works

@InProceedings{Oh_2019_ICCV,
author = {Oh, Seoung Wug and Lee, Joon-Young and Xu, Ning and Kim, Seon Joo},
title = {Video Object Segmentation Using Space-Time Memory Networks},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = {October},
year = {2019}
}

@InProceedings{Li_2020_NeurIPS,
author = {Li, Yuxi and Xu, Ning and Peng Jinlong and John See and Lin Weiyao},
title = {Delving into the Cyclic Mechanism in Semi-supervised Video Object Segmentation},
booktitle = {Neural Information Processing System (NeurIPS)},
year = {2020}
}
Owner
Yuxi Li
Yuxi Li
HiddenMarkovModel implements hidden Markov models with Gaussian mixtures as distributions on top of TensorFlow

Class HiddenMarkovModel HiddenMarkovModel implements hidden Markov models with Gaussian mixtures as distributions on top of TensorFlow 2.0 Installatio

Susara Thenuwara 2 Nov 03, 2021
[ICLR 2021] "Neural Architecture Search on ImageNet in Four GPU Hours: A Theoretically Inspired Perspective" by Wuyang Chen, Xinyu Gong, Zhangyang Wang

Neural Architecture Search on ImageNet in Four GPU Hours: A Theoretically Inspired Perspective [PDF] Wuyang Chen, Xinyu Gong, Zhangyang Wang In ICLR 2

VITA 156 Nov 28, 2022
MusicYOLO framework uses the object detection model, YOLOx, to locate notes in the spectrogram.

MusicYOLO MusicYOLO framework uses the object detection model, YOLOX, to locate notes in the spectrogram. Its performance on the ISMIR2014 dataset, MI

Xianke Wang 2 Aug 02, 2022
Codes for SIGIR'22 Paper 'On-Device Next-Item Recommendation with Self-Supervised Knowledge Distillation'

OD-Rec Codes for SIGIR'22 Paper 'On-Device Next-Item Recommendation with Self-Supervised Knowledge Distillation' Paper, saved teacher models and Andro

Xin Xia 11 Nov 22, 2022
The official PyTorch implementation of recent paper - SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training

This repository is the official PyTorch implementation of SAINT. Find the paper on arxiv SAINT: Improved Neural Networks for Tabular Data via Row Atte

Gowthami Somepalli 284 Dec 21, 2022
Deep learning with TensorFlow and earth observation data.

Deep Learning with TensorFlow and EO Data Complete file set for Jupyter Book Autor: Development Seed Date: 04 October 2021 ISBN: (to come) Notebook tu

Development Seed 20 Nov 16, 2022
Official Implementation of HRDA: Context-Aware High-Resolution Domain-Adaptive Semantic Segmentation

HRDA: Context-Aware High-Resolution Domain-Adaptive Semantic Segmentation by Lukas Hoyer, Dengxin Dai, and Luc Van Gool [Arxiv] [Paper] Overview Unsup

Lukas Hoyer 149 Dec 28, 2022
[CVPR2022] Representation Compensation Networks for Continual Semantic Segmentation

RCIL [CVPR2022] Representation Compensation Networks for Continual Semantic Segmentation Chang-Bin Zhang1, Jia-Wen Xiao1, Xialei Liu1, Ying-Cong Chen2

Chang-Bin Zhang 71 Dec 28, 2022
Code for the IJCAI 2021 paper "Structure Guided Lane Detection"

SGNet Project for the IJCAI 2021 paper "Structure Guided Lane Detection" Abstract Recently, lane detection has made great progress with the rapid deve

Jinming Su 27 Dec 08, 2022
Worktory is a python library created with the single purpose of simplifying the inventory management of network automation scripts.

Worktory is a python library created with the single purpose of simplifying the inventory management of network automation scripts.

Renato Almeida de Oliveira 18 Aug 31, 2022
Band-Adaptive Spectral-Spatial Feature Learning Neural Network for Hyperspectral Image Classification

Band-Adaptive Spectral-Spatial Feature Learning Neural Network for Hyperspectral Image Classification

258 Dec 29, 2022
ELSED: Enhanced Line SEgment Drawing

ELSED: Enhanced Line SEgment Drawing This repository contains the source code of ELSED: Enhanced Line SEgment Drawing the fastest line segment detecto

Iago Suárez 125 Dec 31, 2022
Code for "PV-RAFT: Point-Voxel Correlation Fields for Scene Flow Estimation of Point Clouds", CVPR 2021

PV-RAFT This repository contains the PyTorch implementation for paper "PV-RAFT: Point-Voxel Correlation Fields for Scene Flow Estimation of Point Clou

Yi Wei 43 Dec 05, 2022
Stock-Prediction - prediction of stock market movements using sentiment analysis and deep learning.

Stock-Prediction- In this project, we aim to enhance the prediction of stock market movements using sentiment analysis and deep learning. We divide th

5 Jan 25, 2022
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

NNI Doc | 简体中文 NNI (Neural Network Intelligence) is a lightweight but powerful toolkit to help users automate Feature Engineering, Neural Architecture

Microsoft 12.4k Dec 31, 2022
Specificity-preserving RGB-D Saliency Detection

Specificity-preserving RGB-D Saliency Detection Authors: Tao Zhou, Huazhu Fu, Geng Chen, Yi Zhou, Deng-Ping Fan, and Ling Shao. 1. Preface This reposi

Tao Zhou 35 Jan 08, 2023
Localizing Visual Sounds the Hard Way

Localizing-Visual-Sounds-the-Hard-Way Code and Dataset for "Localizing Visual Sounds the Hard Way". The repo contains code and our pre-trained model.

Honglie Chen 58 Dec 07, 2022
Notes taking website build with Docker + Django + React.

Notes website. Try it in browser! / But how to run? Description. This is monorepository with notes website. Website provides web interface for creatin

Kirill Zhosul 2 Jul 27, 2022
The description of FMFCC-A (audio track of FMFCC) dataset and Challenge resluts.

FMFCC-A This project is the description of FMFCC-A (audio track of FMFCC) dataset and Challenge resluts. The FMFCC-A dataset is shared through BaiduCl

18 Dec 24, 2022
codes for "Scheduled Sampling Based on Decoding Steps for Neural Machine Translation" (long paper of EMNLP-2022)

Scheduled Sampling Based on Decoding Steps for Neural Machine Translation (EMNLP-2021 main conference) Contents Overview Background Quick to Use Furth

Adaxry 13 Jul 25, 2022