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camera-calibration

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GnnrMrkr
GnnrMrkr commented Apr 30, 2020

I'm working with Open3D with data from different devices. One of them does not provide the point cloud as a file, so I am creating the file by myself with a little Python script.

However, I am confused by the supported formats:
The pts format contains lines of [x, y, z, i, r, g, b]. xyz and rgb are intuitive and explained, but what exactly is the i for? And in what format is it exp

hrehfeld
hrehfeld commented Apr 11, 2019

My Archlinux doesn't seem to have "trash" (moves to trash?):

$ git clone https://github.com/stuffmatic/fSpy
$ cd fSpy
$ yarn dist
yarn run v1.15.2
$ yarn run build-dist
$ trash build
/bin/sh: trash: command not found
error Command failed with exit code 127.
info Visit https://yarnpkg.com/en/docs/cli/run for documentation about this command.
error Command failed with exit code 127.
changbaishan
changbaishan commented Jan 11, 2019

The example for "Remove Distortion" is quite beautiful. The reverse is to place an image into a specified area of an image, most likely distorted. I wonder if it can be done by specifying the four corners. If not, please add other points. I guess the underlying code already exist in BoofCV. Just an example to show us how to bring up the functionality.

Thanks very much.

herrdeh
herrdeh commented Oct 15, 2019

Great app - my congrats!
But: How can I make blender to render the background image? - is there a simple trick? Or do I have to import the background image again? - If so, how do I find correct position and size, as I cannot get hold really of an image in blender, just of a camera.
I couldnt find useful info in blender tutorials as well, so I'd be very grateful for some hints.

This is a package for extrinsic calibration between a 3D LiDAR and a camera, described in paper: Improvements to Target-Based 3D LiDAR to Camera Calibration. This package is used for Cassie Blue's 3D LiDAR semantic mapping and automation.

  • Updated Apr 14, 2020
  • MATLAB

This repository contains works on a computer vision software pipeline built on top of Python to identify Lanes and vehicles in a video. This project is not part of Udacity SDCND but is based on other free courses and challanges provided by Udacity. It uses Computer vision and Deep Learrning Techniques. Few pipelines have been tried on SeDriCa, IIT Bombay.

  • Updated Nov 2, 2018
  • Jupyter Notebook

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