Multispectral Object Detection with Yolov5

Overview

Multispectral-Object-Detection

Intro

Official Code for Cross-Modality Fusion Transformer for Multispectral Object Detection.

Multispectral Object Detection with Transformer and Yolov5

Citation

If you use this repo for your research, please cite our paper:

@article{fang2021cross,
  title={Cross-Modality Fusion Transformer for Multispectral Object Detection},
  author={Fang Qingyun and Han Dapeng and Wang Zhaokui},
  journal={arXiv preprint arXiv:2111.00273},
  year={2021}
}

Installation

Python>=3.6.0 is required with all requirements.txt installed including PyTorch>=1.7 (The same as yolov5 https://github.com/ultralytics/yolov5 ).

Clone the repo

git clone https://github.com/DocF/multispectral-object-detection

Install requirements

$ cd  multispectral-object-detection
$ pip install -r requirements.txt

Dataset

-[FLIR] download A new aligned version.

-[LLVIP] download

-[VEDAI] download

Run

Download the pretrained weights

yolov5 weights:

CFT weights:

Add the some file

create runs/train, runs/test and runs/detect three files for save the results.

Change the data cfg

some example in data/multispectral/

Train Test and Detect

train: python train.py

test: python test.py

detect: python detect_twostream.py

Results

Dataset CFT mAP50 mAP75 mAP
FLIR 73.0 32.0 37.4
FLIR ✔️ 77.7 (Δ4.7) 34.8 (Δ2.8) 40.0 (Δ2.6)
LLVIP 95.8 71.4 62.3
LLVIP ✔️ 97.5 (Δ1.7) 72.9 (Δ1.5) 63.6 (Δ1.3)
VEDAI 79.7 47.7 46.8
VEDAI ✔️ 85.3 (Δ5.6) 65.9(Δ18.2) 56.0 (Δ9.2)
Owner
Richard Fang
Richard Fang
Detecting Blurred Ground-based Sky/Cloud Images

Detecting Blurred Ground-based Sky/Cloud Images With the spirit of reproducible research, this repository contains all the codes required to produce t

1 Oct 20, 2021
Omniverse sample scripts - A guide for developing with Python scripts on NVIDIA Ominverse

Omniverse sample scripts ここでは、NVIDIA Omniverse ( https://www.nvidia.com/ja-jp/om

ft-lab (Yutaka Yoshisaka) 37 Nov 17, 2022
A pytorch implementation of the CVPR2021 paper "VSPW: A Large-scale Dataset for Video Scene Parsing in the Wild"

VSPW: A Large-scale Dataset for Video Scene Parsing in the Wild A pytorch implementation of the CVPR2021 paper "VSPW: A Large-scale Dataset for Video

45 Nov 29, 2022
rastrainer is a QGIS plugin to training remote sensing semantic segmentation model based on PaddlePaddle.

rastrainer rastrainer is a QGIS plugin to training remote sensing semantic segmentation model based on PaddlePaddle. UI TODO Init UI. Add Block. Add l

deepbands 5 Mar 04, 2022
Multi-Scale Progressive Fusion Network for Single Image Deraining

Multi-Scale Progressive Fusion Network for Single Image Deraining (MSPFN) This is an implementation of the MSPFN model proposed in the paper (Multi-Sc

Kuijiang 128 Nov 21, 2022
Python-kafka-reset-consumergroup-offset-example - Python Kafka reset consumergroup offset example

Python Kafka reset consumergroup offset example This is a simple example of how

Willi Carlsen 1 Feb 16, 2022
Keras implementation of Normalizer-Free Networks and SGD - Adaptive Gradient Clipping

Keras implementation of Normalizer-Free Networks and SGD - Adaptive Gradient Clipping

Yam Peleg 63 Sep 21, 2022
CaFM-pytorch ICCV ACCEPT Introduction of dataset VSD4K

CaFM-pytorch ICCV ACCEPT Introduction of dataset VSD4K Our dataset VSD4K includes 6 popular categories: game, sport, dance, vlog, interview and city.

96 Jul 05, 2022
MCMC samplers for Bayesian estimation in Python, including Metropolis-Hastings, NUTS, and Slice

Sampyl May 29, 2018: version 0.3 Sampyl is a package for sampling from probability distributions using MCMC methods. Similar to PyMC3 using theano to

Mat Leonard 304 Dec 25, 2022
A distributed, plug-n-play algorithm for multi-robot applications with a priori non-computable objective functions

A distributed, plug-n-play algorithm for multi-robot applications with a priori non-computable objective functions Kapoutsis, A.C., Chatzichristofis,

Athanasios Ch. Kapoutsis 5 Oct 15, 2022
HTSeq is a Python library to facilitate processing and analysis of data from high-throughput sequencing (HTS) experiments.

HTSeq DEVS: https://github.com/htseq/htseq DOCS: https://htseq.readthedocs.io A Python library to facilitate programmatic analysis of data from high-t

HTSeq 57 Dec 20, 2022
Submission to Twitter's algorithmic bias bounty challenge

Twitter Ethics Challenge: Pixel Perfect Submission to Twitter's algorithmic bias bounty challenge, by Travis Hoppe (@metasemantic). Abstract We build

Travis Hoppe 4 Aug 19, 2022
More than a hundred strange attractors

dysts Analyze more than a hundred chaotic systems. Basic Usage Import a model and run a simulation with default initial conditions and parameter value

William Gilpin 185 Dec 23, 2022
The world's simplest facial recognition api for Python and the command line

Face Recognition You can also read a translated version of this file in Chinese 简体中文版 or in Korean 한국어 or in Japanese 日本語. Recognize and manipulate fa

Adam Geitgey 46.9k Jan 03, 2023
Official Repo for Ground-aware Monocular 3D Object Detection for Autonomous Driving

Visual 3D Detection Package: This repo aims to provide flexible and reproducible visual 3D detection on KITTI dataset. We expect scripts starting from

Yuxuan Liu 305 Dec 19, 2022
Code for the prototype tool in our paper "CoProtector: Protect Open-Source Code against Unauthorized Training Usage with Data Poisoning".

CoProtector Code for the prototype tool in our paper "CoProtector: Protect Open-Source Code against Unauthorized Training Usage with Data Poisoning".

Zhensu Sun 1 Oct 26, 2021
This repo contains the pytorch implementation for Dynamic Concept Learner (accepted by ICLR 2021).

DCL-PyTorch Pytorch implementation for the Dynamic Concept Learner (DCL). More details can be found at the project page. Framework Grounding Physical

Zhenfang Chen 31 Jan 06, 2023
[MICCAI'20] AlignShift: Bridging the Gap of Imaging Thickness in 3D Anisotropic Volumes

AlignShift NEW: Code for our new MICCAI'21 paper "Asymmetric 3D Context Fusion for Universal Lesion Detection" will also be pushed to this repository

Medical 3D Vision 42 Jan 06, 2023
Analyzing basic network responses to novel classes

novelty-detection Analyzing how AlexNet responds to novel classes with varying degrees of similarity to pretrained classes from ImageNet. If you find

Noam Eshed 34 Oct 02, 2022
The code for our CVPR paper PISE: Person Image Synthesis and Editing with Decoupled GAN, Project Page, supp.

PISE The code for our CVPR paper PISE: Person Image Synthesis and Editing with Decoupled GAN, Project Page, supp. Requirement conda create -n pise pyt

jinszhang 110 Nov 21, 2022