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
Source code release of the paper: Knowledge-Guided Deep Fractal Neural Networks for Human Pose Estimation.

GNet-pose Project Page: http://guanghan.info/projects/guided-fractal/ UPDATE 9/27/2018: Prototxts and model that achieved 93.9Pck on LSP dataset. http

Guanghan Ning 83 Nov 21, 2022
RoBERTa Marathi Language model trained from scratch during huggingface 🤗 x flax community week

RoBERTa base model for Marathi Language (मराठी भाषा) Pretrained model on Marathi language using a masked language modeling (MLM) objective. RoBERTa wa

Nipun Sadvilkar 23 Oct 19, 2022
Fusion-DHL: WiFi, IMU, and Floorplan Fusion for Dense History of Locations in Indoor Environments

Fusion-DHL: WiFi, IMU, and Floorplan Fusion for Dense History of Locations in Indoor Environments Paper: arXiv (ICRA 2021) Video : https://youtu.be/CC

Sachini Herath 68 Jan 03, 2023
Encoding Causal Macrovariables

Encoding Causal Macrovariables Data Natural climate data ('El Nino') Self-generated data ('Simulated') Experiments Detecting macrovariables through th

Benedikt Höltgen 3 Jul 31, 2022
TCTrack: Temporal Contexts for Aerial Tracking (CVPR2022)

TCTrack: Temporal Contexts for Aerial Tracking (CVPR2022) Ziang Cao and Ziyuan Huang and Liang Pan and Shiwei Zhang and Ziwei Liu and Changhong Fu In

Intelligent Vision for Robotics in Complex Environment 100 Dec 19, 2022
Improving Factual Completeness and Consistency of Image-to-text Radiology Report Generation

Improving Factual Completeness and Consistency of Image-to-text Radiology Report Generation The reference code of Improving Factual Completeness and C

46 Dec 15, 2022
Semantic Segmentation for Real Point Cloud Scenes via Bilateral Augmentation and Adaptive Fusion (CVPR 2021)

Semantic Segmentation for Real Point Cloud Scenes via Bilateral Augmentation and Adaptive Fusion (CVPR 2021) This repository is for BAAF-Net introduce

90 Dec 29, 2022
[WACV 2022] Contextual Gradient Scaling for Few-Shot Learning

CxGrad - Official PyTorch Implementation Contextual Gradient Scaling for Few-Shot Learning Sanghyuk Lee, Seunghyun Lee, and Byung Cheol Song In WACV 2

Sanghyuk Lee 4 Dec 05, 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
Code + pre-trained models for the paper Keeping Your Eye on the Ball Trajectory Attention in Video Transformers

Motionformer This is an official pytorch implementation of paper Keeping Your Eye on the Ball: Trajectory Attention in Video Transformers. In this rep

Facebook Research 192 Dec 23, 2022
PyTorch implementation of Soft-DTW: a Differentiable Loss Function for Time-Series in CUDA

Soft DTW Loss Function for PyTorch in CUDA This is a Pytorch Implementation of Soft-DTW: a Differentiable Loss Function for Time-Series which is batch

Keon Lee 76 Dec 20, 2022
Pytorch implementation of the paper "Optimization as a Model for Few-Shot Learning"

Optimization as a Model for Few-Shot Learning This repo provides a Pytorch implementation for the Optimization as a Model for Few-Shot Learning paper.

Albert Berenguel Centeno 238 Jan 04, 2023
Dynamic Slimmable Network (CVPR 2021, Oral)

Dynamic Slimmable Network (DS-Net) This repository contains PyTorch code of our paper: Dynamic Slimmable Network (CVPR 2021 Oral). Architecture of DS-

Changlin Li 197 Dec 09, 2022
基于Paddle框架的fcanet复现

fcanet-Paddle 基于Paddle框架的fcanet复现 fcanet 本项目基于paddlepaddle框架复现fcanet,并参加百度第三届论文复现赛,将在2021年5月15日比赛完后提供AIStudio链接~敬请期待 参考项目: frazerlin-fcanet 数据准备 本项目已挂

QuanHao Guo 7 Mar 07, 2022
unofficial pytorch implement of "Squareplus: A Softplus-Like Algebraic Rectifier"

SquarePlus (Pytorch implement) unofficial pytorch implement of "Squareplus: A Softplus-Like Algebraic Rectifier" SquarePlus Squareplus is a Softplus-L

SeeFun 3 Dec 29, 2021
Official PyTorch implementation of "BlendGAN: Implicitly GAN Blending for Arbitrary Stylized Face Generation" (NeurIPS 2021)

BlendGAN: Implicitly GAN Blending for Arbitrary Stylized Face Generation Official PyTorch implementation of the NeurIPS 2021 paper Mingcong Liu, Qiang

onion 462 Dec 29, 2022
Sentiment analysis translations of the Bhagavad Gita

Sentiment and Semantic Analysis of Bhagavad Gita Translations It is well known that translations of songs and poems not only breaks rhythm and rhyming

Machine learning and Bayesian inference @ UNSW Sydney 3 Aug 01, 2022
Homepage of paper: Paint Transformer: Feed Forward Neural Painting with Stroke Prediction, ICCV 2021.

Paint Transformer: Feed Forward Neural Painting with Stroke Prediction [Paper] [Official Paddle Implementation] [Huggingface Gradio Demo] [Unofficial

442 Dec 16, 2022
[CVPR22] Official codebase of Semantic Segmentation by Early Region Proxy.

RegionProxy Figure 2. Performance vs. GFLOPs on ADE20K val split. Semantic Segmentation by Early Region Proxy Yifan Zhang, Bo Pang, Cewu Lu CVPR 2022

Yifan 54 Nov 29, 2022
Code of the paper "Performance-Efficiency Trade-offs in Unsupervised Pre-training for Speech Recognition"

SEW (Squeezed and Efficient Wav2vec) The repo contains the code of the paper "Performance-Efficiency Trade-offs in Unsupervised Pre-training for Speec

ASAPP Research 67 Dec 01, 2022