Traffic4D: Single View Reconstruction of Repetitious Activity Using Longitudinal Self-Supervision

Related tags

Deep LearningTraffic4D-Release
Overview

Traffic4D: Single View Reconstruction of Repetitious Activity Using Longitudinal Self-Supervision

Project | PDF | Poster
Fangyu Li, N. Dinesh Reddy, Xudong Chen and Srinivasa G. Narasimhan
Proceedings of IEEE Intelligent Vehicles Symposium (IV'21)
Best Paper Award

Following instructions below, the user will get keypoints, trajectory reconstruction and vehicular activity clustering results like

Set up

The set up process can be skipped if using docker. Please check "Docker" section.

Python

Python version 3.6.9 is used. Python packages are in requirements.txt .

git clone https://github.com/Emrys-Lee/Traffic4D-Release.git
sudo apt-get install python3.6
sudo apt-get install python3-pip
cd Traffic4D-Release
pip3 install -r requirements.txt

C++

Traffic4D uses C++ libraries ceres and pybind for efficient optimization. pybind needs clang compiler, so Traffic4D uses clang compiler.

Install clang compiler

sudo apt-get install clang++-6.0

Install prerequisites for ceres

# CMake
sudo apt-get install cmake
# google-glog + gflags
sudo apt-get install libgoogle-glog-dev libgflags-dev
# BLAS & LAPACK
sudo apt-get install libatlas-base-dev
# Eigen3
sudo apt-get install libeigen3-dev
# SuiteSparse and CXSparse (optional)
sudo apt-get install libsuitesparse-dev

Download and install ceres

wget https://github.com/ceres-solver/ceres-solver/archive/1.12.0.zip
unzip 1.12.0.zip
cd ceres-solver-1.12.0/
mkdir build
cd build
cmake ..
make
sudo make install

Download and install pybind

git clone https://github.com/pybind/pybind11
cd pybind11
cmake .
make
sudo make install

Build Traffic4D optimization library

cd Traffic4D-Release/src/ceres
make

ceres_reconstruct.so and ceres_spline.so are generated under path Traffic4D-Release/src/ceres/.

Dataset

Download dataset and pre-generated results from here, and put it under Traffic4D-Release/.

cd Traffic4D-Release
mv Data-Traffic4D.zip ./
unzip Data-Traffic4D.zip

The directory should be like

Traffic4D-Release/
    Data-Traffic4D/
    └───fifth_morewood/
        └───fifth_morewood_init.vd
        └───top_view.png
        └───images/
                00001.jpg
                00002.jpg
                ...
                06288.jpg
    └───arterial_kennedy/
        └───arterial_kennedy_init.vd
        └───top_view.png
        └───images/
                <put AI City Challenge frames here>
        ...

The input and output paths can be modified in config/*.yml.

Explanation

1. Input videos

Sample videos in Traffic4D are provided. Note arterial_kennedy and dodge_century are from Nvidia AI City Challenge City-Scale Multi-Camera Vehicle Tracking Challenge Track. Please request the access to the dataset here. Once get the data, run

ffmpeg -i <mtmc-dir>/train/S01/c001/vdo.avi Traffic4D-Release/Data-Traffic4D/arterial_kennedy/images/%05d.jpg
ffmpeg -i <mtmc-dir>/test/S02/c007/vdo.avi Traffic4D-Release/Data-Traffic4D/dodge_century/images/%05d.jpg

to extract frames into images/.

2. Pre-Generated 2D results

Detected 2D bounding boxes, keypoints and tracking IDs are stored in *_init.vd. Check Occlusionnet implementation for detecting keypoints; V-IOU for multi-object tracking.

3. Output folder

Folder Traffic4D-Release/Result/ will be created by default.

Experiments

Run python exp/traffic4d.py config/<intersection_name>.yml <action>. Here YML configuration files for multiple intersections are provided under config/ folder. <action> shoulbe be reconstruction or clustering to perform longitudinal reconstruction and activity clustering sequentially. For example, below runs Fifth and Morewood intersection.

cd Traffic4D-Release
python3 exp/traffic4d.py config/fifth_morewood.yml reconstruction
python3 exp/traffic4d.py config/fifth_morewood.yml clustering

Results

Find these results in the output folder:

  1. 2D keypoints: If 3D reconstruction is done, 2D reprojected keypoints will be plotted in Traffic4D-Release/Result/<intersection_name>_keypoints/.
  2. 3D reconstructed trajectories and clusters: The clustered 3D trajectories are plotted on the top view map as Traffic4D-Release/Result/<intersection_name>_top_view.jpg.

Docker

We provide docker image with dependencies already set up. The steps in "Set up" can be skipped if you use docker image. You still need to clone the repo and download the dataset and put it in under Traffic4D-Release/.

git clone https://github.com/Emrys-Lee/Traffic4D-Release.git

Pull Traffic4D docker image.

docker pull emrysli/traffic4d-release:latest

Then create a container and map the git repo into docker container to access the dataset. For example, if the cloned repo locates at host directory /home/xxx/Traffic4D-Release, <path_to_repo> should be /home/xxx. If <path_in_container> is /home/yyy, then /home/xxx/Traffic4D-Release will be mapped as /home/yyy/Traffic4D-Release inside the container.

docker run -it -v <path_to_repo>/Traffic4D-Release:<path_in_container>/Traffic4D-Release emrysli/traffic4d-release:latest /bin/bash

Inside container compile Traffic4D again.

# inside container
cd <path_in_container>/Traffic4D-Release/src/ceres
make

Run experiments.

cd <path_in_container>/Traffic4D-Release
python3 exp/traffic4d.py config/fifth_morewood.yml reconstruction
python3 exp/traffic4d.py config/fifth_morewood.yml clustering

Trouble Shooting

  1. tkinter module is missing
File "/usr/local/lib/python3.6/dist-packages/matplotlib/backends/_backend_tk.py", line 5, in <module>
    import tkinter as Tk
ModuleNotFoundError: No module named 'tkinter'

Solution: install tkinter.

sudo apt-get install python3-tk
  1. opencv import error such as
File "/usr/local/lib/python3.6/dist-packages/cv2/__init__.py", line 3, in <module>
    from .cv2 import *
ImportError: libSM.so.6: cannot open shared object file: No such file or directory

Solution: install the missing libraries.

sudo apt-get install libsm6 libxrender1 libfontconfig1 libxext6

Citation

Traffic4D

@conference{Li-2021-127410,
author = {Fangyu Li and N. Dinesh Reddy and Xudong Chen and Srinivasa G. Narasimhan},
title = {Traffic4D: Single View Reconstruction of Repetitious Activity Using Longitudinal Self-Supervision},
booktitle = {Proceedings of IEEE Intelligent Vehicles Symposium (IV '21)},
year = {2021},
month = {July},
publisher = {IEEE},
keywords = {Self-Supervision, vehicle Detection, 4D Reconstruction, 3D reconstuction, Pose Estimation.},
}

Occlusion-Net

@inproceedings{onet_cvpr19,
author = {Reddy, N. Dinesh and Vo, Minh and Narasimhan, Srinivasa G.},
title = {Occlusion-Net: 2D/3D Occluded Keypoint Localization Using Graph Networks},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
pages = {7326--7335},
year = {2019}
}
Owner
GitHub Repository
Code for paper "Do Language Models Have Beliefs? Methods for Detecting, Updating, and Visualizing Model Beliefs"

This is the codebase for the paper: Do Language Models Have Beliefs? Methods for Detecting, Updating, and Visualizing Model Beliefs Directory Structur

Peter Hase 19 Aug 21, 2022
Mixed Transformer UNet for Medical Image Segmentation

MT-UNet Update 2021/11/19 Thank you for your interest in our work. We have uploaded the code of our MTUNet to help peers conduct further research on i

dotman 92 Dec 25, 2022
Repo for "Event-Stream Representation for Human Gaits Identification Using Deep Neural Networks"

Summary This is the code for the paper Event-Stream Representation for Human Gaits Identification Using Deep Neural Networks by Yanxiang Wang, Xian Zh

zhangxian 54 Jan 03, 2023
GenGNN: A Generic FPGA Framework for Graph Neural Network Acceleration

GenGNN: A Generic FPGA Framework for Graph Neural Network Acceleration Stefan Abi-Karam*, Yuqi He*, Rishov Sarkar*, Lakshmi Sathidevi, Zihang Qiao, Co

Sharc-Lab 19 Dec 15, 2022
Uses Open AI Gym environment to create autonomous cryptocurrency bot to trade cryptocurrencies.

Crypto_Bot Uses Open AI Gym environment to create autonomous cryptocurrency bot to trade cryptocurrencies. Steps to get started using the bot: Sign up

21 Oct 03, 2022
SelfRemaster: SSL Speech Restoration

SelfRemaster: Self-Supervised Speech Restoration Official implementation of SelfRemaster: Self-Supervised Speech Restoration with Analysis-by-Synthesi

Takaaki Saeki 46 Jan 07, 2023
a curated list of docker-compose files prepared for testing data engineering tools, databases and open source libraries.

data-services A repository for storing various Data Engineering docker-compose files in one place. How to use it ? Set the required settings in .env f

BigData.IR 525 Dec 03, 2022
Solutions of Reinforcement Learning 2nd Edition

Solutions of Reinforcement Learning, An Introduction

YIFAN WANG 1.4k Dec 30, 2022
Partial implementation of ODE-GAN technique from the paper Training Generative Adversarial Networks by Solving Ordinary Differential Equations

ODE GAN (Prototype) in PyTorch Partial implementation of ODE-GAN technique from the paper Training Generative Adversarial Networks by Solving Ordinary

Somshubra Majumdar 15 Feb 10, 2022
A Keras implementation of YOLOv4 (Tensorflow backend)

keras-yolo4 请使用更完善的版本: https://github.com/miemie2013/Keras-YOLOv4 Please visit here for more complete model: https://github.com/miemie2013/Keras-YOLOv

384 Nov 29, 2022
This project intends to use SVM supervised learning to determine whether or not an individual is diabetic given certain attributes.

Diabetes Prediction Using SVM I explore a diabetes prediction algorithm using a Diabetes dataset. Using a Support Vector Machine for my prediction alg

Jeff Shen 1 Jan 14, 2022
Learning Dynamic Network Using a Reuse Gate Function in Semi-supervised Video Object Segmentation.

Training Script for Reuse-VOS This code implementation of CVPR 2021 paper : Learning Dynamic Network Using a Reuse Gate Function in Semi-supervised Vi

HYOJINPARK 22 Jan 01, 2023
An open software package to develop BCI based brain and cognitive computing technology for recognizing user's intention using deep learning

An open software package to develop BCI based brain and cognitive computing technology for recognizing user's intention using deep learning

deepbci 272 Jan 08, 2023
Tacotron 2 - PyTorch implementation with faster-than-realtime inference

Tacotron 2 (without wavenet) PyTorch implementation of Natural TTS Synthesis By Conditioning Wavenet On Mel Spectrogram Predictions. This implementati

NVIDIA Corporation 4.1k Jan 03, 2023
DockStream: A Docking Wrapper to Enhance De Novo Molecular Design

DockStream Description DockStream is a docking wrapper providing access to a collection of ligand embedders and docking backends. Docking execution an

AstraZeneca - Molecular AI 72 Jan 02, 2023
Implementation of CVPR'21: RfD-Net: Point Scene Understanding by Semantic Instance Reconstruction

RfD-Net [Project Page] [Paper] [Video] RfD-Net: Point Scene Understanding by Semantic Instance Reconstruction Yinyu Nie, Ji Hou, Xiaoguang Han, Matthi

Yinyu Nie 162 Jan 06, 2023
EASY - Ensemble Augmented-Shot Y-shaped Learning: State-Of-The-Art Few-Shot Classification with Simple Ingredients.

EASY - Ensemble Augmented-Shot Y-shaped Learning: State-Of-The-Art Few-Shot Classification with Simple Ingredients. This repository is the official im

Yassir BENDOU 57 Dec 26, 2022
Python and C++ implementation of "MarkerPose: Robust real-time planar target tracking for accurate stereo pose estimation". Accepted at LXCV @ CVPR 2021.

MarkerPose: Robust real-time planar target tracking for accurate stereo pose estimation This is a PyTorch and LibTorch implementation of MarkerPose: a

Jhacson Meza 47 Nov 18, 2022
PixelPyramids: Exact Inference Models from Lossless Image Pyramids (ICCV 2021)

PixelPyramids: Exact Inference Models from Lossless Image Pyramids This repository contains the PyTorch implementation of the paper PixelPyramids: Exa

Visual Inference Lab @TU Darmstadt 8 Dec 11, 2022
PyTorch implementation of our method for adversarial attacks and defenses in hyperspectral image classification.

Self-Attention Context Network for Hyperspectral Image Classification PyTorch implementation of our method for adversarial attacks and defenses in hyp

22 Dec 02, 2022