FCOSR: A Simple Anchor-free Rotated Detector for Aerial Object Detection

Related tags

Deep LearningFCOSR
Overview

FCOSR: A Simple Anchor-free Rotated Detector for Aerial Object Detection

FCOSR: A Simple Anchor-free Rotated Detector for Aerial Object Detection
arXiv preprint (arXiv:2111.10780).

This implement is modified from mmdetection. We also refer to the codes of ReDet, PIoU, and ProbIoU.

In the process of implementation, we find that only Python code processing will produce huge memory overhead on Nvidia devices. Therefore, we directly write the label assignment module proposed in this paper in the form of CUDA extension of Pytorch. The program could not work effectively when we migrate it to cuda 11 (only support cuda10). By applying CUDA expansion, the memory utilization is improved and a lot of unnecessary calculations are reduced. We also try to train FCOSR-M on 2080ti (4 images per device), which can basically fill memory of graphics card.

Install

Please refer to install.md for installation and dataset preparation.

Getting Started

Please see get_started.md for the basic usage.

Model Zoo

benchmark

The password of baiduPan is ABCD

FCOSR serise DOTA 1.0 result.FPS(2080ti) Detail

Model backbone MS Sched. Param. Input GFLOPs FPS mAP download
FCOSR-S Mobilenet v2 - 3x 7.32M 1024×1024 101.42 23.7 74.05 model/cfg
FCOSR-S Mobilenet v2 ✓ 3x 7.32M 1024×1024 101.42 23.7 76.11 model/cfg
FCOSR-M ResNext50-32x4 - 3x 31.4M 1024×1024 210.01 14.6 77.15 model/cfg
FCOSR-M ResNext50-32x4 ✓ 3x 31.4M 1024×1024 210.01 14.6 79.25 model/cfg
FCOSR-L ResNext101-64x4 - 3x 89.64M 1024×1024 445.75 7.9 77.39 model/cfg
FCOSR-L ResNext101-64x4 ✓ 3x 89.64M 1024×1024 445.75 7.9 78.80 model/cfg

FCOSR serise DOTA 1.5 result. FPS(2080ti) Detail

Model backbone MS Sched. Param. Input GFLOPs FPS mAP download
FCOSR-S Mobilenet v2 - 3x 7.32M 1024×1024 101.42 23.7 66.37 model/cfg
FCOSR-S Mobilenet v2 ✓ 3x 7.32M 1024×1024 101.42 23.7 73.14 model/cfg
FCOSR-M ResNext50-32x4 - 3x 31.4M 1024×1024 210.01 14.6 68.74 model/cfg
FCOSR-M ResNext50-32x4 ✓ 3x 31.4M 1024×1024 210.01 14.6 73.79 model/cfg
FCOSR-L ResNext101-64x4 - 3x 89.64M 1024×1024 445.75 7.9 69.96 model/cfg
FCOSR-L ResNext101-64x4 ✓ 3x 89.64M 1024×1024 445.75 7.9 75.41 model/cfg

FCOSR serise HRSC2016 result. FPS(2080ti)

Model backbone Rot. Sched. Param. Input GFLOPs FPS AP50(07) AP75(07) AP50(12) AP75(12) download
FCOSR-S Mobilenet v2 ✓ 40k iters 7.29M 800×800 61.57 35.3 90.08 76.75 92.67 75.73 model/cfg
FCOSR-M ResNext50-32x4 ✓ 40k iters 31.37M 800×800 127.87 26.9 90.15 78.58 94.84 81.38 model/cfg
FCOSR-L ResNext101-64x4 ✓ 40k iters 89.61M 800×800 271.75 15.1 90.14 77.98 95.74 80.94 model/cfg

Lightweight FCOSR test result on Jetson Xavier NX (DOTA 1.0 single-scale). Detail

Model backbone Head channels Sched. Param Size Input GFLOPs FPS mAP onnx TensorRT
FCOSR-lite Mobilenet v2 256 3x 6.9M 51.63MB 1024×1024 101.25 7.64 74.30 Wait rtr
FCOSR-tiny Mobilenet v2 128 3x 3.52M 23.2MB 1024×1024 35.89 10.68 73.93 Wait rtr
Owner
GitHub Repository
Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.

Modeling High-Frequency Limit Order Book Dynamics Using Machine Learning Framework to capture the dynamics of high-frequency limit order books. Overvi

Chang-Shu Chung 1.3k Jan 07, 2023
Cerberus Transformer: Joint Semantic, Affordance and Attribute Parsing

Cerberus Transformer: Joint Semantic, Affordance and Attribute Parsing Paper Introduction Multi-task indoor scene understanding is widely considered a

62 Dec 05, 2022
A web-based application for quick, scalable, and automated hyperparameter tuning and stacked ensembling in Python.

Xcessiv Xcessiv is a tool to help you create the biggest, craziest, and most excessive stacked ensembles you can think of. Stacked ensembles are simpl

Reiichiro Nakano 1.3k Nov 17, 2022
Statistical and Algorithmic Investing Strategies for Everyone

Eiten - Algorithmic Investing Strategies for Everyone Eiten is an open source toolkit by Tradytics that implements various statistical and algorithmic

Tradytics 2.5k Jan 02, 2023
Minimal implementation of Denoised Smoothing: A Provable Defense for Pretrained Classifiers in TensorFlow.

Denoised-Smoothing-TF Minimal implementation of Denoised Smoothing: A Provable Defense for Pretrained Classifiers in TensorFlow. Denoised Smoothing is

Sayak Paul 19 Dec 11, 2022
Instance Segmentation in 3D Scenes using Semantic Superpoint Tree Networks

SSTNet Instance Segmentation in 3D Scenes using Semantic Superpoint Tree Networks(ICCV2021) by Zhihao Liang, Zhihao Li, Songcen Xu, Mingkui Tan, Kui J

83 Nov 29, 2022
OpenMMLab Video Perception Toolbox. It supports Video Object Detection (VID), Multiple Object Tracking (MOT), Single Object Tracking (SOT), Video Instance Segmentation (VIS) with a unified framework.

English | 简体中文 Documentation: https://mmtracking.readthedocs.io/ Introduction MMTracking is an open source video perception toolbox based on PyTorch.

OpenMMLab 2.7k Jan 08, 2023
This repository includes code of my study about Asynchronous in Frequency domain of GAN images.

Exploring the Asynchronous of the Frequency Spectra of GAN-generated Facial Images Binh M. Le & Simon S. Woo, "Exploring the Asynchronous of the Frequ

4 Aug 06, 2022
YOLOX-CondInst - Implement CondInst which is a instances segmentation method on YOLOX

YOLOX CondInst -- YOLOX 实例分割 前言 本项目是自己学习实例分割时，复现的代码. 通过自己编程，让自己对实例分割有更进一步的了解。 若想

DDGRCF 16 Nov 18, 2022
Multi-Task Pre-Training for Plug-and-Play Task-Oriented Dialogue System

Multi-Task Pre-Training for Plug-and-Play Task-Oriented Dialogue System Authors: Yixuan Su, Lei Shu, Elman Mansimov, Arshit Gupta, Deng Cai, Yi-An Lai

Amazon Web Services - Labs 123 Dec 23, 2022
Static Features Classifier - A static features classifier for Point-Could clusters using an Attention-RNN model

Static Features Classifier This is a static features classifier for Point-Could

ABDALKARIM MOHTASIB 1 Jan 25, 2022
A simple python program that can be used to implement user authentication tokens into your program...

token-generator A simple python module that can be used by developers to implement user authentication tokens into your program... code examples creat

octo 6 Apr 18, 2022
Camera Distortion-aware 3D Human Pose Estimation in Video with Optimization-based Meta-Learning

Camera Distortion-aware 3D Human Pose Estimation in Video with Optimization-based Meta-Learning This is the official repository of "Camera Distortion-

Hanbyel Cho 12 Oct 06, 2022
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.

The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate. Website • Key Features • How To Use • Docs •

Pytorch Lightning 21.1k Jan 01, 2023
An experiment on the performance of homemade Q-learning AIs in Agar.io depending on their state representation and available actions

Agar.io_Q-Learning_AI An experiment on the performance of homemade Q-learning AIs in Agar.io depending on their state representation and available act

1 Jun 09, 2022
Consistency Regularization for Adversarial Robustness

Consistency Regularization for Adversarial Robustness Official PyTorch implementation of Consistency Regularization for Adversarial Robustness by Jiho

40 Dec 17, 2022
DenseNet Implementation in Keras with ImageNet Pretrained Models

DenseNet-Keras with ImageNet Pretrained Models This is an Keras implementation of DenseNet with ImageNet pretrained weights. The weights are converted

Felix Yu 568 Oct 31, 2022
DropNAS: Grouped Operation Dropout for Differentiable Architecture Search

DropNAS: Grouped Operation Dropout for Differentiable Architecture Search DropNAS, a grouped operation dropout method for one-level DARTS, with better

weijunhong 4 Aug 15, 2022
Research code for Arxiv paper "Camera Motion Agnostic 3D Human Pose Estimation"

GMR(Camera Motion Agnostic 3D Human Pose Estimation) This repo provides the source code of our arXiv paper: Seong Hyun Kim, Sunwon Jeong, Sungbum Park

Seong Hyun Kim 1 Feb 07, 2022
Optimal Adaptive Allocation using Deep Reinforcement Learning in a Dose-Response Study

Optimal Adaptive Allocation using Deep Reinforcement Learning in a Dose-Response Study Supplementary Materials for Kentaro Matsuura, Junya Honda, Imad

Kentaro Matsuura 4 Nov 01, 2022