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
SCI-AIDE : High-fidelity Few-shot Histopathology Image Synthesis for Rare Cancer Diagnosis

SCI-AIDE : High-fidelity Few-shot Histopathology Image Synthesis for Rare Cancer Diagnosis Pretrained Models In this work, we created synthetic tissue

Emirhan Kurtuluş 1 Feb 07, 2022
Code for CMaskTrack R-CNN (proposed in Occluded Video Instance Segmentation)

CMaskTrack R-CNN for OVIS This repo serves as the official code release of the CMaskTrack R-CNN model on the Occluded Video Instance Segmentation data

Q . J . Y 61 Nov 25, 2022
[ICCV'2021] Image Inpainting via Conditional Texture and Structure Dual Generation

[ICCV'2021] Image Inpainting via Conditional Texture and Structure Dual Generation

Xiefan Guo 122 Dec 11, 2022
PyTorch implementation for our paper "Deep Facial Synthesis: A New Challenge"

FSGAN Here is the official PyTorch implementation for our paper "Deep Facial Synthesis: A New Challenge". This project achieve the translation between

Deng-Ping Fan 32 Oct 10, 2022
A Deep Reinforcement Learning Framework for Stock Market Trading

DQN-Trading This is a framework based on deep reinforcement learning for stock market trading. This project is the implementation code for the two pap

61 Jan 01, 2023
Aws-machine-learning-university-accelerated-tab - Machine Learning University: Accelerated Tabular Data Class

Machine Learning University: Accelerated Tabular Data Class This repository contains slides, notebooks, and datasets for the Machine Learning Universi

AWS Samples 916 Dec 23, 2022
Official Implementation and Dataset of "PPR10K: A Large-Scale Portrait Photo Retouching Dataset with Human-Region Mask and Group-Level Consistency", CVPR 2021

Portrait Photo Retouching with PPR10K Paper | Supplementary Material PPR10K: A Large-Scale Portrait Photo Retouching Dataset with Human-Region Mask an

184 Dec 11, 2022
The code is an implementation of Feedback Convolutional Neural Network for Visual Localization and Segmentation.

Feedback Convolutional Neural Network for Visual Localization and Segmentation The code is an implementation of Feedback Convolutional Neural Network

19 Dec 04, 2022
PyTorch3D is FAIR's library of reusable components for deep learning with 3D data

Introduction PyTorch3D provides efficient, reusable components for 3D Computer Vision research with PyTorch. Key features include: Data structure for

Facebook Research 6.8k Jan 01, 2023
A collection of easy-to-use, ready-to-use, interesting deep neural network models

Interesting and reproducible research works should be conserved. This repository wraps a collection of deep neural network models into a simple and un

Aria Ghora Prabono 16 Jun 16, 2022
SimDeblur is a simple framework for image and video deblurring, implemented by PyTorch

SimDeblur (Simple Deblurring) is an open source framework for image and video deblurring toolbox based on PyTorch, which contains most deep-learning based state-of-the-art deblurring algorithms. It i

220 Jan 07, 2023
MAg: a simple learning-based patient-level aggregation method for detecting microsatellite instability from whole-slide images

MAg Paper Abstract File structure Dataset prepare Data description How to use MAg? Why not try the MAg_lib! Trained models Experiment and results Some

Calvin Pang 3 Apr 08, 2022
Code for our SIGCOMM'21 paper "Network Planning with Deep Reinforcement Learning".

0. Introduction This repository contains the source code for our SIGCOMM'21 paper "Network Planning with Deep Reinforcement Learning". Notes The netwo

NetX Group 68 Nov 24, 2022
Deep Learning for Natural Language Processing SS 2021 (TU Darmstadt)

Deep Learning for Natural Language Processing SS 2021 (TU Darmstadt) Task Training huge unsupervised deep neural networks yields to strong progress in

Oliver Hahn 1 Jan 26, 2022
Face Library is an open source package for accurate and real-time face detection and recognition

Face Library Face Library is an open source package for accurate and real-time face detection and recognition. The package is built over OpenCV and us

52 Nov 09, 2022
An AI Assistant More Than a Toolkit

tymon An AI Assistant More Than a Toolkit The reason for creating framework tymon is simple. making AI more like an assistant, helping us to complete

TymonXie 46 Oct 24, 2022
A PyTorch Implementation of Single Shot MultiBox Detector

SSD: Single Shot MultiBox Object Detector, in PyTorch A PyTorch implementation of Single Shot MultiBox Detector from the 2016 paper by Wei Liu, Dragom

Max deGroot 4.8k Jan 07, 2023
Video Autoencoder: self-supervised disentanglement of 3D structure and motion

Video Autoencoder: self-supervised disentanglement of 3D structure and motion This repository contains the code (in PyTorch) for the model introduced

157 Dec 22, 2022
Continuous Conditional Random Field Convolution for Point Cloud Segmentation

CRFConv This repository is the implementation of "Continuous Conditional Random Field Convolution for Point Cloud Segmentation" 1. Setup 1) Building c

Fei Yang 8 Dec 08, 2022
shufflev2-yolov5:lighter, faster and easier to deploy

shufflev2-yolov5: lighter, faster and easier to deploy. Evolved from yolov5 and the size of model is only 1.7M (int8) and 3.3M (fp16). It can reach 10+ FPS on the Raspberry Pi 4B when the input size

pogg 1.5k Jan 05, 2023