This is a repository for high performance real time camera calibration and performing inverse perspective mapping at the same time.
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Table of Contents
I've had problems with finding a performant algorithm which calibrates the camera and performs inverse perspective mapping to get the bird eye view variant of an image to use in my self driving car project so I made this repository to help other people that want a high performance camera calibration and/or ipm algorithm.
The IPM code is heavily inspired from IPM-master by JamesLiao so huge thanks for his work!
The code was built primarily to run on jetson nano although it should work on any cuda capable device.
First you should get started by trying out the demo
Here are all the dependencies you will need:
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cuda 10.1 or 10.2
Follow the official documentation from NVIDIA CUDA
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gcc 8
sudo apt-get install gcc-8 g++-8
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cmake
sudo apt-get install cmake
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eigen
sudo apt install libeigen3-dev
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opencv (needed only for demo)
Follow the official documentation OpenCV
- Clone the repo
git clone https://github.com/butnaruteodor/IPMandCamCalib.git
- Build the project
chmod +x build.sh && ./build.sh - Run the demo
./IPM
- Add documentation
- Add usage examples
- Broader compatibility
See the open issues for a full list of proposed features (and known issues).
Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.
If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature) - Commit your Changes (
git commit -m 'Add some AmazingFeature') - Push to the Branch (
git push origin feature/AmazingFeature) - Open a Pull Request
Butnaru Teodor - butnaruteodor@gmail.com
Project Link: https://github.com/butnaruteodor/IPMandCamCalib