CAR-API: Cityscapes Attributes Recognition API

Related tags

Deep LearningCAR-API
Overview

CAR-API: Cityscapes Attributes Recognition API

This is the official api to download and fetch attributes annotations for Cityscapes Dataset.

Content

Installation

You first need to download Cityscapes dataset. You can do so by checking this repo.

I'm showing here a simple working example to download the data but for further issues please refer to the source repo. Or download from the official website

  1. Install Cityscapes scripts and other required packages.
$ pip install -r requirements.txt
  1. Run the following script to download Cityscapes dataset. If you don't have an account, you will need to create an account.
$ csDownload -d [DESTINATION_PATH] PACKAGE_NAME

Note: you can also use -l option to list all possible packages to download. i.e.

$ csDownload -l
  1. After downloading all required packages, set the environment variable CITYSCAPES_DATASET to the location of the dataset. For example, if the dataset is installed in the path /home/user/cityscapes/
$ export CITYSCAPES_DATASET="/home/user/cityscapes/"

Note: you can also export the previous command to your ~/.bashrc file for example.

~/.bashrc ">
$ echo 'export CITYSCAPES_DATASET="/home/user/cityscapes/"' > ~/.bashrc

Note2: we actually need the images only. We do not need the labels as it is stored with the attributes annotations as well.

  1. Run the following to download the json files of CAR compressed as a single zip file extract it and then remove the zip file.
$ python download_CAR.py --url_path "https://DOWNLOAD_LINK_HERE"

To obtain the download link, please email me at kmetwaly511 [at] gmail [dot] com.

At this point, you have 4 json files; namely all.json, train.json, val.json and test.json

PyTorch Example

We provide a pytorch example to read the dataset and retrieve a sample of the dataset in pytorch_dataset_CAR.py. Please, refer to main.It contains a code that goes through the entire dataset.

An output sample of the dataset class is of custom type ModelInputItem. Please refer to the definiton of the class for more details about defined methods and variables.

Citation

If you are planning to use this code or the dataset, please cite the work appropriately as follows.

@misc{car_api,
  title = {{CAR}-{API}: an {API} for {CAR} Dataset},
  key = {{CAR}-{API}},
  howpublished = {\url{http://github.com/kareem-metwaly/car-api}},
  note = {Accessed: 2021-11-16}
}

@misc{metwaly2022car,
  title={{CAR} -- Cityscapes Attributes Recognition A Multi-category Attributes Dataset for Autonomous Vehicles}, 
  author={Kareem Metwaly and Aerin Kim and Elliot Branson and Vishal Monga},
  year={2021},
  eprint={2111.08243},
  archivePrefix={arXiv},
  primaryClass={cs.CV},
  howpublished = {\url{https://arxiv.org/abs/2111.08243}},
  urldate = {2021-11-17},
}
Owner
Kareem Metwaly
Kareem Metwaly
Stitch it in Time: GAN-Based Facial Editing of Real Videos

STIT - Stitch it in Time [Project Page] Stitch it in Time: GAN-Based Facial Edit

1.1k Jan 04, 2023
Simple node deletion tool for onnx.

snd4onnx Simple node deletion tool for onnx. I only test very miscellaneous and limited patterns as a hobby. There are probably a large number of bugs

Katsuya Hyodo 6 May 15, 2022
TensorFlow implementation of Elastic Weight Consolidation

Elastic weight consolidation Introduction A TensorFlow implementation of elastic weight consolidation as presented in Overcoming catastrophic forgetti

James Stokes 67 Oct 11, 2022
Just Randoms Cats with python

Random-Cat Just Randoms Cats with python.

OriCode 2 Dec 21, 2021
Unofficial PyTorch implementation of Fastformer based on paper "Fastformer: Additive Attention Can Be All You Need"."

Fastformer-PyTorch Unofficial PyTorch implementation of Fastformer based on paper Fastformer: Additive Attention Can Be All You Need. Usage : import t

Hong-Jia Chen 126 Dec 06, 2022
Crossover Learning for Fast Online Video Instance Segmentation (ICCV 2021)

TL;DR: CrossVIS (Crossover Learning for Fast Online Video Instance Segmentation) proposes a novel crossover learning paradigm to fully leverage rich c

Hust Visual Learning Team 79 Nov 25, 2022
Avalanche RL: an End-to-End Library for Continual Reinforcement Learning

Avalanche RL: an End-to-End Library for Continual Reinforcement Learning Avalanche Website | Getting Started | Examples | Tutorial | API Doc | Paper |

ContinualAI 43 Dec 24, 2022
A large dataset of 100k Google Satellite and matching Map images, resembling pix2pix's Google Maps dataset.

Larger Google Sat2Map dataset This dataset extends the aerial ⟷ Maps dataset used in pix2pix (Isola et al., CVPR17). The provide script download_sat2m

34 Dec 28, 2022
PyTorch implementation of TSception V2 using DEAP dataset

TSception This is the PyTorch implementation of TSception V2 using DEAP dataset in our paper: Yi Ding, Neethu Robinson, Su Zhang, Qiuhao Zeng, Cuntai

Yi Ding 27 Dec 15, 2022
RANZCR-CLiP 7th Place Solution

RANZCR-CLiP 7th Place Solution This repository is WIP. (18 Mar 2021) Installation git clone https://github.com/analokmaus/kaggle-ranzcr-clip-public.gi

Hiroshechka Y 21 Oct 22, 2022
Parametric Contrastive Learning (ICCV2021)

Parametric-Contrastive-Learning This repository contains the implementation code for ICCV2021 paper: Parametric Contrastive Learning (https://arxiv.or

DV Lab 156 Dec 21, 2022
Official implementation of "Motif-based Graph Self-Supervised Learning forMolecular Property Prediction"

Motif-based Graph Self-Supervised Learning for Molecular Property Prediction Official Pytorch implementation of NeurIPS'21 paper "Motif-based Graph Se

zaixi 71 Dec 20, 2022
[AAAI22] Reliable Propagation-Correction Modulation for Video Object Segmentation

Reliable Propagation-Correction Modulation for Video Object Segmentation (AAAI22) Preview version paper of this work is available at: https://arxiv.or

Xiaohao Xu 70 Dec 04, 2022
Combinatorial model of ligand-receptor binding

Combinatorial model of ligand-receptor binding The binding of ligands to receptors is the starting point for many import signal pathways within a cell

Mobolaji Williams 0 Jan 09, 2022
This is a Machine Learning Based Hand Detector Project, It Uses Machine Learning Models and Modules Like Mediapipe, Developed By Google!

Machine Learning Hand Detector This is a Machine Learning Based Hand Detector Project, It Uses Machine Learning Models and Modules Like Mediapipe, Dev

Popstar Idhant 3 Feb 25, 2022
House_prices_kaggle - Predict sales prices and practice feature engineering, RFs, and gradient boosting

House Prices - Advanced Regression Techniques Predicting House Prices with Machine Learning This project is build to enhance my knowledge about machin

Gurpreet Singh 1 Jan 01, 2022
A Physics-based Noise Formation Model for Extreme Low-light Raw Denoising (CVPR 2020 Oral & TPAMI 2021)

ELD The implementation of CVPR 2020 (Oral) paper "A Physics-based Noise Formation Model for Extreme Low-light Raw Denoising" and its journal (TPAMI) v

Kaixuan Wei 359 Jan 01, 2023
Random Walk Graph Neural Networks

Random Walk Graph Neural Networks This repository is the official implementation of Random Walk Graph Neural Networks. Requirements Code is written in

Giannis Nikolentzos 38 Jan 02, 2023
[Official] Exploring Temporal Coherence for More General Video Face Forgery Detection(ICCV 2021)

Exploring Temporal Coherence for More General Video Face Forgery Detection(FTCN) Yinglin Zheng, Jianmin Bao, Dong Chen, Ming Zeng, Fang Wen Accepted b

57 Dec 28, 2022