EVer - A Library for Earth Vision Researcher
EVer is a Pytorch-based Python library to simplify the training and inference of the deep learning model.
This is a beta version for research only.
Features
- Common codebase for reproducible research
- Accelerating our Earth Vision research
- Single workflow of "data-module-configs"
Installation
stable version (0.2.3)
pip install ever-beta
nightly version (master)
pip install --upgrade git+https://github.com/Z-Zheng/ever.git
Getting Started
SimpleCV
Projects using EVer orChange Detection
-
Change is Everywhere: Single-Temporal Supervised Object Change Detection in Remote Sensing Imagery, ICCV 2021. [
Paper
], [Code
] -
Building damage assessment for rapid disaster response with a deep object-based semantic change detection framework: from natural disasters to man-made disasters, RSE 2021. [
Paper
], [Code
]
Segmentation
-
Foreground-Aware Relation Network for Geospatial Object Segmentation in High Spatial Resolution Remote Sensing Imagery, CVPR 2020. [
Paper
], [Code
] -
Deep multisensor learning for missing-modality all-weather mapping, ISPRS P&RS 2021. [
Paper
], [Code
] -
FactSeg: Foreground Activation Driven Small Object Semantic Segmentation in Large-Scale Remote Sensing Imagery, TGRS 2021. [
Paper
], [Code
]
Hyperspectral Image Classification
-
FPGA: Fast Patch-Free Global Learning Framework for Fully End-to-End Hyperspectral Image Classification, TGRS 2020. [
Paper
], [Code
] -
A Spectral-Spatial-Dependent Global Learning Framework for Insufficient and Imbalanced Hyperspectral Image Classification, TCYB 2021. [
Paper
], [Code
]
License
EVer is released under the Apache License 2.0.
Copyright (c) Zhuo Zheng. All rights reserved.