Omnidirectional camera calibration in python

Overview

Omnidirectional Camera Calibration

Key features

Undistort example (undistort example)

Usage

  1. Corner detection (see python -m omnicalib.detect --help for detailed argument description)
python -m omnical.detect --chessboard <rows> <columns> <square-size> --max-dim <max-dim> --threads <threads> <image-folder>

The file detections.pickle is written, which contains a pickled dictionary with the following format

{
    'detections': {
        <image_path_0>: {'image_points': <image_points>, 'object_points': <object_points>},
        ...
}
  • Image paths (pathlib.Path) are absolute
  • image_points are torch.Tensor with shape N x 2 and dtype torch.float64
  • object_points are torch.Tensor with shape N x 3 and dtype torch.float64 and third colum, the z coordinate, all zeros

If an external corner detection method is used, this file can simply be written manually.

  1. Calibration (see python -m omnicalib --help for detailed argument description)
python -m omnical --degree <degree> detections.pickle

Result

A calibration.yml file (see example_calibration.yml) containing

  • extrinsics as list of 3 x 4 matrices
  • poly_incident_angle_to_radius, a polynom that converts incident angle to image radius
  • poly_radius_to_z, a polynom that converts radius to z component of view vector
  • principal_point in pixel

Method

For a detailed description see method.md.

Simulation

Play with the calibration on simulated data with the provided jupyter lab notebook. It generates randomized data for the following ideal projection models

  • equidistant
  • stereographic
  • orthographic
  • equisolid

, see Large Area 3D Human Pose Detection Via Stereo Reconstruction in Panoramic Cameras for a detailed description.

Example

Jupyter lab notebook, example results

Example calibration

Example r-z curve

Example calibration

You might also like...
Improving Calibration for Long-Tailed Recognition (CVPR2021)
Improving Calibration for Long-Tailed Recognition (CVPR2021)

Improving Calibration for Long-Tailed Recognition (CVPR2021)

Pytorch Implementation of Spiking Neural Networks Calibration, ICML 2021

SNN_Calibration Pytorch Implementation of Spiking Neural Networks Calibration, ICML 2021 Feature Comparison of SNN calibration: Features SNN Direct Tr

S2-BNN: Bridging the Gap Between Self-Supervised Real and 1-bit Neural Networks via Guided Distribution Calibration (CVPR 2021)
S2-BNN: Bridging the Gap Between Self-Supervised Real and 1-bit Neural Networks via Guided Distribution Calibration (CVPR 2021)

S2-BNN (Self-supervised Binary Neural Networks Using Distillation Loss) This is the official pytorch implementation of our paper: "S2-BNN: Bridging th

the code for paper "Energy-Based Open-World Uncertainty Modeling for Confidence Calibration"

EOW-Softmax This code is for the paper "Energy-Based Open-World Uncertainty Modeling for Confidence Calibration". Accepted by ICCV21. Usage Commnd exa

We utilize deep reinforcement learning to obtain favorable trajectories for visual-inertial system calibration.
We utilize deep reinforcement learning to obtain favorable trajectories for visual-inertial system calibration.

Unified Data Collection for Visual-Inertial Calibration via Deep Reinforcement Learning Update: The lastest code will be updated in this branch. Pleas

Improving Calibration for Long-Tailed Recognition (CVPR2021)
Improving Calibration for Long-Tailed Recognition (CVPR2021)

MiSLAS Improving Calibration for Long-Tailed Recognition Authors: Zhisheng Zhong, Jiequan Cui, Shu Liu, Jiaya Jia [arXiv] [slide] [BibTeX] Introductio

Source code of NeurIPS 2021 Paper ''Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration''

CaGCN This repo is for source code of NeurIPS 2021 paper "Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration". Paper L

CSAC - Collaborative Semantic Aggregation and Calibration for Separated Domain Generalization
CSAC - Collaborative Semantic Aggregation and Calibration for Separated Domain Generalization

CSAC Introduction This repository contains the implementation code for paper: Co

[CVPR 2022] Official code for the paper:
[CVPR 2022] Official code for the paper: "A Stitch in Time Saves Nine: A Train-Time Regularizing Loss for Improved Neural Network Calibration"

MDCA Calibration This is the official PyTorch implementation for the paper: "A Stitch in Time Saves Nine: A Train-Time Regularizing Loss for Improved

Owner
Thomas Pönitz
Thomas Pönitz
Safe Control for Black-box Dynamical Systems via Neural Barrier Certificates

Safe Control for Black-box Dynamical Systems via Neural Barrier Certificates Installation Clone the repository: git clone https://github.com/Zengyi-Qi

Zengyi Qin 3 Oct 18, 2022
VOS: Learning What You Don’t Know by Virtual Outlier Synthesis

VOS This is the source code accompanying the paper VOS: Learning What You Don’t

248 Dec 25, 2022
ICCV2021 Oral SA-ConvONet: Sign-Agnostic Optimization of Convolutional Occupancy Networks

Sign-Agnostic Convolutional Occupancy Networks Paper | Supplementary | Video | Teaser Video | Project Page This repository contains the implementation

64 Jan 05, 2023
Code for the paper: Sketch Your Own GAN

Sketch Your Own GAN Project | Paper | Youtube | Slides Our method takes in one or a few hand-drawn sketches and customizes an off-the-shelf GAN to mat

677 Dec 28, 2022
[CVPR 2021] "The Lottery Tickets Hypothesis for Supervised and Self-supervised Pre-training in Computer Vision Models" Tianlong Chen, Jonathan Frankle, Shiyu Chang, Sijia Liu, Yang Zhang, Michael Carbin, Zhangyang Wang

The Lottery Tickets Hypothesis for Supervised and Self-supervised Pre-training in Computer Vision Models Codes for this paper The Lottery Tickets Hypo

VITA 59 Dec 28, 2022
You Only Hypothesize Once: Point Cloud Registration with Rotation-equivariant Descriptors

You Only Hypothesize Once: Point Cloud Registration with Rotation-equivariant Descriptors In this paper, we propose a novel local descriptor-based fra

Haiping Wang 80 Dec 15, 2022
Code repository accompanying the paper "On Adversarial Robustness: A Neural Architecture Search perspective"

On Adversarial Robustness: A Neural Architecture Search perspective Preparation: Clone the repository: https://github.com/tdchaitanya/nas-robustness.g

Chaitanya Devaguptapu 4 Nov 10, 2022
Official implementation of VQ-Diffusion

Vector Quantized Diffusion Model for Text-to-Image Synthesis Overview This is the official repo for the paper: [Vector Quantized Diffusion Model for T

Microsoft 592 Jan 03, 2023
The official repository for BaMBNet

BaMBNet-Pytorch Paper

Junjun Jiang 18 Dec 04, 2022
The code for 'Deep Residual Fourier Transformation for Single Image Deblurring'

Deep Residual Fourier Transformation for Single Image Deblurring Xintian Mao, Yiming Liu, Wei Shen, Qingli Li and Yan Wang code will be released soon

145 Dec 13, 2022
Repo for "Benchmarking Robustness of 3D Point Cloud Recognition against Common Corruptions" https://arxiv.org/abs/2201.12296

Benchmarking Robustness of 3D Point Cloud Recognition against Common Corruptions This repo contains the dataset and code for the paper Benchmarking Ro

Jiachen Sun 168 Dec 29, 2022
Jiminy Cricket Environment (NeurIPS 2021)

Jiminy Cricket This is the repository for "What Would Jiminy Cricket Do? Towards Agents That Behave Morally" by Dan Hendrycks*, Mantas Mazeika*, Andy

Dan Hendrycks 15 Aug 29, 2022
Malware Env for OpenAI Gym

Malware Env for OpenAI Gym Citing If you use this code in a publication please cite the following paper: Hyrum S. Anderson, Anant Kharkar, Bobby Fila

ENDGAME 563 Dec 29, 2022
This is the official implementation of our proposed SwinMR

SwinMR This is the official implementation of our proposed SwinMR: Swin Transformer for Fast MRI Please cite: @article{huang2022swin, title={Swi

A Yang Lab (led by Dr Guang Yang) 27 Nov 17, 2022
This is the repository of shape matching algorithm Iterative Rotations and Assignments (IRA)

Description This is the repository of shape matching algorithm Iterative Rotations and Assignments (IRA), described in the publication [1]. Directory

MAMMASMIAS Consortium 6 Nov 14, 2022
A PyTorch implementation of the paper "Semantic Image Synthesis via Adversarial Learning" in ICCV 2017

Semantic Image Synthesis via Adversarial Learning This is a PyTorch implementation of the paper Semantic Image Synthesis via Adversarial Learning. Req

Seonghyeon Nam 146 Nov 25, 2022
[ICCV 2021] Our work presents a novel neural rendering approach that can efficiently reconstruct geometric and neural radiance fields for view synthesis.

MVSNeRF Project page | Paper This repository contains a pytorch lightning implementation for the ICCV 2021 paper: MVSNeRF: Fast Generalizable Radiance

Anpei Chen 529 Dec 30, 2022
Official code for "On the Frequency Bias of Generative Models", NeurIPS 2021

Frequency Bias of Generative Models Generator Testbed Discriminator Testbed This repository contains official code for the paper On the Frequency Bias

35 Nov 01, 2022
Learning Modified Indicator Functions for Surface Reconstruction

Learning Modified Indicator Functions for Surface Reconstruction In this work, we propose a learning-based approach for implicit surface reconstructio

4 Apr 18, 2022
Exploit ILP to learn symmetry breaking constraints of ASP programs.

ILP Symmetry Breaking Overview This project aims to exploit inductive logic programming to lift symmetry breaking constraints of ASP programs. Given a

Research Group Production Systems 1 Apr 13, 2022