The comma.ai Calibration Challenge!

Overview

Welcome to the comma.ai Calibration Challenge!

Your goal is to predict the direction of travel (in camera frame) from provided dashcam video.

  • This repo provides 10 videos. Every video is 1min long and 20 fps.
  • 5 videos are labeled with a 2D array describing the direction of travel at every frame of the video with a pitch and yaw angle in radians.
  • 5 videos are unlabeled. It is your task to generate the labels for them.
  • The example labels are generated using a Neural Network, and the labels were confirmed with a SLAM algorithm.
  • You can estimate the focal length to be 910 pixels.

Context

The devices that run openpilot are not mounted perfectly. The camera is not exactly aligned to the vehicle. There is some pitch and yaw angle between the camera of the device and the vehicle, which can vary between installations. Estimating these angles is essential for accurate control of the vehicle. The best way to start estimating these values is to predict the direction of motion in camera frame. More info can be found in this readme.

Deliverable

Your deliverable is the 5 labels called 5.txt to 9.txt. These labels should be a 2D array that contains the pitch and yaw angles of the direction of travel (in camera frame) of every frame of the respective videos. Zip them up and e-mail it to [email protected].

Evaluation

We will evaluate your mean squared error against our ground truth labels. Errors for frames where the car speed is less than 4m/s will be ignored. Those are also labeled as NaN in the example labels.

This repo includes an eval script that will give an error score (lower is better). You can use it to test your solutions against the labeled examples. We will use this script to evaluate your solution.

Hints

  • Keep the goal and evaluation script in mind, creative solutions are allowed.
  • Look at plots of your solutions before submitting.

$500 Prize CLAIMED

The first submission that scores an error under 25% on the unlabeled set, will receive a $500 prize.

Owner
comma.ai
Make driving chill
comma.ai
code for Grapadora research paper experimentation

Road feature embedding selection method Code for research paper experimentation Abstract Traffic forecasting models rely on data that needs to be sens

Eric López Manibardo 0 May 26, 2022
Official Repo of my work for SREC Nandyal Machine Learning Bootcamp

About the Bootcamp A 3-day Machine Learning Bootcamp organised by Department of Electronics and Communication Engineering, Santhiram Engineering Colle

MS 1 Nov 29, 2021
code associated with ACL 2021 DExperts paper

DExperts Hi! This repository contains code for the paper DExperts: Decoding-Time Controlled Text Generation with Experts and Anti-Experts to appear at

Alisa Liu 68 Dec 15, 2022
An implementation of paper `Real-time Convolutional Neural Networks for Emotion and Gender Classification` with PaddlePaddle.

简介 通过PaddlePaddle框架复现了论文 Real-time Convolutional Neural Networks for Emotion and Gender Classification 中提出的两个模型,分别是SimpleCNN和MiniXception。利用 imdb_crop

8 Mar 11, 2022
This is the official code of L2G, Unrolling and Recurrent Unrolling in Learning to Learn Graph Topologies.

Learning to Learn Graph Topologies This is the official code of L2G, Unrolling and Recurrent Unrolling in Learning to Learn Graph Topologies. Requirem

Stacy X PU 16 Dec 09, 2022
本步态识别系统主要基于GaitSet模型进行实现

本步态识别系统主要基于GaitSet模型进行实现。在尝试部署本系统之前,建立理解GaitSet模型的网络结构、训练和推理方法。 系统的实现效果如视频所示: 演示视频 由于模型较大,部分模型文件存储在百度云盘。 链接提取码:33mb 具体部署过程 1.下载代码 2.安装requirements.txt

16 Oct 22, 2022
Riemannian Geometry for Molecular Surface Approximation (RGMolSA)

Riemannian Geometry for Molecular Surface Approximation (RGMolSA) Introduction Ligand-based virtual screening aims to reduce the cost and duration of

11 Nov 15, 2022
Exploration & Research into cross-domain MEV. Initial focus on ETH/POLYGON.

xMEV, an apt exploration This is a small exploration on the xMEV opportunities between Polygon and Ethereum. It's a data analysis exercise on a few pa

odyslam.eth 7 Oct 18, 2022
This repository is an unoffical PyTorch implementation of Medical segmentation in 3D and 2D.

Pytorch Medical Segmentation Read Chinese Introduction:Here! Recent Updates 2021.1.8 The train and test codes are released. 2021.2.6 A bug in dice was

EasyCV-Ellis 618 Dec 27, 2022
Motion Reconstruction Code and Data for Skills from Videos (SFV)

Motion Reconstruction Code and Data for Skills from Videos (SFV) This repo contains the data and the code for motion reconstruction component of the S

268 Dec 01, 2022
Visualizing lattice vibration information from phonon dispersion to atoms (For GPUMD)

Phonon-Vibration-Viewer (For GPUMD) Visualizing lattice vibration information from phonon dispersion for primitive atoms. In this tutorial, we will in

Liangting 6 Dec 10, 2022
Implementation of the Transformer variant proposed in "Transformer Quality in Linear Time"

FLASH - Pytorch Implementation of the Transformer variant proposed in the paper Transformer Quality in Linear Time Install $ pip install FLASH-pytorch

Phil Wang 209 Dec 28, 2022
Using modified BiSeNet for face parsing in PyTorch

face-parsing.PyTorch Contents Training Demo References Training Prepare training data: -- download CelebAMask-HQ dataset -- change file path in the pr

zll 1.6k Jan 08, 2023
Python scripts for performing 3D human pose estimation using the Mobile Human Pose model in ONNX.

Python scripts for performing 3D human pose estimation using the Mobile Human Pose model in ONNX.

Ibai Gorordo 99 Dec 31, 2022
TensorFlow implementation of the algorithm in the paper "Decoupled Low-light Image Enhancement"

Decoupled Low-light Image Enhancement Shijie Hao1,2*, Xu Han1,2, Yanrong Guo1,2 & Meng Wang1,2 1Key Laboratory of Knowledge Engineering with Big Data

17 Apr 25, 2022
The (Official) PyTorch Implementation of the paper "Deep Extraction of Manga Structural Lines"

MangaLineExtraction_PyTorch The (Official) PyTorch Implementation of the paper "Deep Extraction of Manga Structural Lines" Usage model_torch.py [sourc

Miaomiao Li 82 Jan 02, 2023
buildseg is a building extraction plugin of QGIS based on PaddlePaddle.

buildseg buildseg is a building extraction plugin of QGIS based on PaddlePaddle. TODO Extract building on 512x512 remote sensing images. Extract build

Yizhou Chen 11 Sep 26, 2022
Convolutional neural network that analyzes self-generated images in a variety of languages to find etymological similarities

This project is a convolutional neural network (CNN) that analyzes self-generated images in a variety of languages to find etymological similarities. Specifically, the goal is to prove that computer

1 Feb 03, 2022
Demo code for ICCV 2021 paper "Sensor-Guided Optical Flow"

Sensor-Guided Optical Flow Demo code for "Sensor-Guided Optical Flow", ICCV 2021 This code is provided to replicate results with flow hints obtained f

10 Mar 16, 2022
Self-supervised Deep LiDAR Odometry for Robotic Applications

DeLORA: Self-supervised Deep LiDAR Odometry for Robotic Applications Overview Paper: link Video: link ICRA Presentation: link This is the correspondin

Robotic Systems Lab - Legged Robotics at ETH Zürich 181 Dec 29, 2022