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ai-tod-r

https://github.com/chasel-tsui/ai-tod-r

Science Score: 44.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
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    Institutional organization owner
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    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (9.9%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

Basic Info
  • Host: GitHub
  • Owner: Chasel-Tsui
  • License: apache-2.0
  • Language: Python
  • Default Branch: main
  • Size: 66.1 MB
Statistics
  • Stars: 9
  • Watchers: 1
  • Forks: 0
  • Open Issues: 2
  • Releases: 0
Created over 1 year ago · Last pushed 12 months ago
Metadata Files
Readme License Citation

README.md

mmrotate-dcfl

Official method implementation for the paper: Oriented Tiny Object Detection: A Dataset, Benchmark, and Dynamic Unbiased Learning

Introduction

DCFL is a learning framework that can be plugged into one-stage and two-stage architectures for detecting oriented tiny objects.

demo image

Installation and Get Started

Required environments: - Linux - Python 3.7+ - PyTorch 1.10.0+ - CUDA 9.2+ - GCC 5+ - MMdet 2.23.0+ - MMCV-DCFL

Install: Note that this repository is based on the MMRotate. Assume that your environment has satisfied the above requirements, please follow the following steps for installation.

git clone https://github.com/Chasel-Tsui/AI-TOD-R.git cd AI-TOD-R pip install -r requirements/build.txt python setup.py develop

Visualization

Predictions of the RetinaNet-O are shown in the first row, predictions of the DCFL are shown in the second row. Note that the green box denotes the True Positive, the red box denotes the False Negative and the blue box denotes the False Positive predictions. demo_images

Citation

If you find this work helpful, please consider citing: bibtex @article{xu2024oriented, title={Oriented Tiny Object Detection: A Dataset, Benchmark, and Dynamic Unbiased Learning}, author={Xu, Chang and Zhang, Ruixiang and Yang, Wen and Zhu, Haoran and Xu, Fang and Ding, Jian and Xia, Gui-Song}, journal={arXiv preprint}, year={2024} }

Owner

  • Name: Chang Xu
  • Login: Chasel-Tsui
  • Kind: user
  • Location: Wuhan

Wuhan University

Citation (CITATION.cff) 

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
  - name: "MMRotate Contributors"
title: "OpenMMLab rotated object detection toolbox and benchmark"
date-released: 2022-02-18
url: "https://github.com/open-mmlab/mmrotate"
license: Apache-2.0

GitHub Events

Total
  • Issues event: 11
  • Watch event: 7
  • Issue comment event: 11
  • Push event: 3
Last Year
  • Issues event: 11
  • Watch event: 7
  • Issue comment event: 11
  • Push event: 3

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 6
  • Total pull requests: 0
  • Average time to close issues: 18 days
  • Average time to close pull requests: N/A
  • Total issue authors: 4
  • Total pull request authors: 0
  • Average comments per issue: 1.33
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 6
  • Pull requests: 0
  • Average time to close issues: 18 days
  • Average time to close pull requests: N/A
  • Issue authors: 4
  • Pull request authors: 0
  • Average comments per issue: 1.33
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
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Top Authors
Issue Authors
  • getup201 (3)
  • lwCVer (1)
  • LTXyyds (1)
  • wcy791 (1)
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Dependencies

docker/Dockerfile docker
  • pytorch/pytorch ${PYTORCH}-cuda${CUDA}-cudnn${CUDNN}-devel build
docker/serve/Dockerfile docker
  • pytorch/pytorch ${PYTORCH}-cuda${CUDA}-cudnn${CUDNN}-devel build
requirements/build.txt pypi
  • cython *
  • numpy *
requirements/docs.txt pypi
  • docutils ==0.16.0
  • myst-parser *
  • sphinx ==4.0.2
  • sphinx-copybutton *
  • sphinx_markdown_tables *
  • sphinx_rtd_theme ==0.5.2
requirements/mminstall.txt pypi
  • mmcv-full >=1.5.0
requirements/optional.txt pypi
  • imagecorruptions *
  • scipy *
  • sklearn *
requirements/readthedocs.txt pypi
  • e2cnn *
  • mmcv *
  • mmdet *
  • torch *
  • torchvision *
requirements/runtime.txt pypi
  • e2cnn *
  • matplotlib *
  • mmcv-full *
  • mmdet *
  • numpy *
  • pycocotools *
  • six *
  • terminaltables *
  • torch *
requirements/tests.txt pypi
  • asynctest * test
  • codecov * test
  • coverage * test
  • cython * test
  • e2cnn * test
  • flake8 * test
  • interrogate * test
  • isort ==4.3.21 test
  • kwarray * test
  • matplotlib * test
  • pytest * test
  • sklearn * test
  • ubelt * test
  • wheel * test
  • xdoctest >=0.10.0 test
  • yapf * test
requirements.txt pypi
setup.py pypi