FairMOT for Multi-Class MOT using YOLOX as Detector

Overview

FairMOT-X

Project Overview

FairMOT-X is a multi-class multi object tracker, which has been tailored for training on the BDD100K MOT Dataset. It makes use of YOLOX as the detector from end-to-end, and uses DCN to perform feature fusion of PAFPN outputs to learn the ReID branch. This repo is a work in progress.

Acknowledgement

This project heavily uses code from the the original FairMOT, as well as MCMOT and YOLOv4 MCMOT.

Comments
  • Detailed readme

    Detailed readme

    Thanks for your excellent work!And i have the same idea with you but i can't implement it,Can you provide detailed insatallation in reame file or your contact information,that's a milestone in my research. Thank you in advance!

    opened by Soyad-yao 10
  • how to train on other datasets

    how to train on other datasets

    Hello ! First,thank you for your work! But I have a question. I want to train on other datasets not bdd100k , such as detrac, how to use? Thank you very much!

    opened by fafa114 2
  • Conda environment

    Conda environment

    Could you please share a working environment requirements list for this repo? I followed FairMOT installation procedure but I am unable to start a sample training. I got the following error:

    python3 ./src/train.py mot \

    --exp_id yolo-m --yolo_depth 0.67 --yolo_width 0.75 \
    --lr 7e-4 --lr_step 2 \
    --reid_dim 128 --augment --mosaic \
    --batch_size 16 --gpus 0 
    

    /home/fatih/miniconda3/envs/fairmot-x/lib/python3.8/site-packages/torchvision/io/image.py:13: UserWarning: Failed to load image Python extension: /home/fatih/miniconda3/envs/fairmot-x/lib/python3.8/site-packages/torchvision/image.so: undefined symbol: _ZNK3c106IValue23reportToTensorTypeErrorEv warn(f"Failed to load image Python extension: {e}") Traceback (most recent call last): File "./src/train.py", line 16, in from torchvision.transforms import transforms as T File "/home/fatih/miniconda3/envs/fairmot-x/lib/python3.8/site-packages/torchvision/init.py", line 7, in from torchvision import models File "/home/fatih/miniconda3/envs/fairmot-x/lib/python3.8/site-packages/torchvision/models/init.py", line 18, in from . import quantization File "/home/fatih/miniconda3/envs/fairmot-x/lib/python3.8/site-packages/torchvision/models/quantization/init.py", line 3, in from .mobilenet import * File "/home/fatih/miniconda3/envs/fairmot-x/lib/python3.8/site-packages/torchvision/models/quantization/mobilenet.py", line 1, in from .mobilenetv2 import * # noqa: F401, F403 File "/home/fatih/miniconda3/envs/fairmot-x/lib/python3.8/site-packages/torchvision/models/quantization/mobilenetv2.py", line 6, in from torch.ao.quantization import QuantStub, DeQuantStub ModuleNotFoundError: No module named 'torch.ao'

    opened by youonlytrackonce 0
  • How to get the tracking indicators, such as Mota

    How to get the tracking indicators, such as Mota

    I want to know how to get the tracking indicators, such as MOTA, only "python3 track.py"? But when I run track.py ,always show "[Warning]: No objects detected." I don't know why. And I can't get indicators . But I can get images after tracking on BDD100k MOT dataset.

    opened by fafa114 0
  • train log

    train log

    Thanks for your work! I follow your code and then implement yolox+fairmot in mmdetection. But the ReID loss does not descend. Would you mind uploading your train log as a reference ?

    opened by taofuyu 3
Releases(Weights)
Owner
Jonathan Tan
Mech. Engineering Undergraduate at NUS with deep interest in machine learning and robotics.
Jonathan Tan
An LSTM based GAN for Human motion synthesis

GAN-motion-Prediction An LSTM based GAN for motion synthesis has a few issues reading H3.6M data from A.Jain et al , will fix soon. Prediction of the

Amogh Adishesha 9 Jun 17, 2022
TimeSHAP explains Recurrent Neural Network predictions.

TimeSHAP TimeSHAP is a model-agnostic, recurrent explainer that builds upon KernelSHAP and extends it to the sequential domain. TimeSHAP computes even

Feedzai 90 Dec 18, 2022
Code for NeurIPS 2021 paper 'Spatio-Temporal Variational Gaussian Processes'

Spatio-Temporal Variational GPs This repository is the official implementation of the methods in the publication: O. Hamelijnck, W.J. Wilkinson, N.A.

AaltoML 26 Sep 16, 2022
Simple-System-Convert--C--F - Simple System Convert With Python

Simple-System-Convert--C--F REQUIREMENTS Python version : 3 HOW TO USE Run the c

Jonathan Santos 2 Feb 16, 2022
Improving Object Detection by Estimating Bounding Box Quality Accurately

Improving Object Detection by Estimating Bounding Box Quality Accurately Abstrac

2 Apr 14, 2022
Code for the paper titled "Prabhupadavani: A Code-mixed Speech Translation Data for 25 languages"

Prabhupadavani: A Code-mixed Speech Translation Data for 25 languages Code for the paper titled "Prabhupadavani: A Code-mixed Speech Translation Data

Ayush Daksh 12 Dec 01, 2022
simple demo codes for Learning to Teach with Dynamic Loss Functions

Learning to Teach with Dynamic Loss Functions This repo contains the simple demo for the NeurIPS-18 paper: Learning to Teach with Dynamic Loss Functio

Lijun Wu 15 Dec 30, 2021
NeuralDiff: Segmenting 3D objects that move in egocentric videos

NeuralDiff: Segmenting 3D objects that move in egocentric videos Project Page | Paper + Supplementary | Video About This repository contains the offic

Vadim Tschernezki 14 Dec 05, 2022
Illuminated3D This project participates in the Nasa Space Apps Challenge 2021.

Illuminated3D This project participates in the Nasa Space Apps Challenge 2021.

Eleftheriadis Emmanouil 1 Oct 09, 2021
LinkNet - This repository contains our Torch7 implementation of the network developed by us at e-Lab.

LinkNet This repository contains our Torch7 implementation of the network developed by us at e-Lab. You can go to our blogpost or read the article Lin

e-Lab 158 Nov 11, 2022
Deconfounding Temporal Autoencoder: Estimating Treatment Effects over Time Using Noisy Proxies

Deconfounding Temporal Autoencoder (DTA) This is a repository for the paper "Deconfounding Temporal Autoencoder: Estimating Treatment Effects over Tim

Milan Kuzmanovic 3 Feb 04, 2022
An image processing project uses Viola-jones technique to detect faces and then use SIFT algorithm for recognition.

Attendance_System An image processing project uses Viola-jones technique to detect faces and then use LPB algorithm for recognition. Face Detection Us

8 Jan 11, 2022
Code for our ACL 2021 paper - ConSERT: A Contrastive Framework for Self-Supervised Sentence Representation Transfer

ConSERT Code for our ACL 2021 paper - ConSERT: A Contrastive Framework for Self-Supervised Sentence Representation Transfer Requirements torch==1.6.0

Yan Yuanmeng 478 Dec 25, 2022
This GitHub repository contains code used for plots in NeurIPS 2021 paper 'Stochastic Multi-Armed Bandits with Control Variates.'

About Repository This repository contains code used for plots in NeurIPS 2021 paper 'Stochastic Multi-Armed Bandits with Control Variates.' About Code

Arun Verma 1 Nov 09, 2021
LocUNet is a deep learning method to localize a UE based solely on the reported signal strengths from a set of BSs.

LocUNet LocUNet is a deep learning method to localize a UE based solely on the reported signal strengths from a set of BSs. The method utilizes accura

4 Oct 05, 2022
DeepVoxels is an object-specific, persistent 3D feature embedding.

DeepVoxels is an object-specific, persistent 3D feature embedding. It is found by globally optimizing over all available 2D observations of

Vincent Sitzmann 196 Dec 25, 2022
A PyTorch library and evaluation platform for end-to-end compression research

CompressAI CompressAI (compress-ay) is a PyTorch library and evaluation platform for end-to-end compression research. CompressAI currently provides: c

InterDigital 680 Jan 06, 2023
Neural network pruning for finding a sparse computational model for controlling a biological motor task.

MothPruning Scientific Overview Originally inspired by biological nervous systems, deep neural networks (DNNs) are powerful computational tools for mo

Olivia Thomas 0 Dec 14, 2022
Implementation of ConvMixer in TensorFlow and Keras

ConvMixer ConvMixer, an extremely simple model that is similar in spirit to the ViT and the even-more-basic MLP-Mixer in that it operates directly on

Sayan Nath 8 Oct 03, 2022
Back to the Feature: Learning Robust Camera Localization from Pixels to Pose (CVPR 2021)

Back to the Feature with PixLoc We introduce PixLoc, a neural network for end-to-end learning of camera localization from an image and a 3D model via

Computer Vision and Geometry Lab 610 Jan 05, 2023