Loading repository data…
Loading repository data…
Jarviss77 / repository
CurveTopia tackles shape detection and completion, featuring regularization and occlusion tasks. The Regularisation folder contains the regularization task, and the master_folder holds Jupyter notebooks (.ipynb) for Algorithms 1 to 4 on occlusion. The Streamlit app integrates all solutions for interactive use.
A transparent discovery signal based on current public GitHub metadata.
This score does not audit code, security, maintainers, documentation quality, or suitability. Verify the repository and its current documentation before adoption.
Find deployed link here: Deployed website
We have developed one algorithm for Regularization Task and four different algorithm for shape completion (Shape detection and Completion.Generalized Hough Transform with Multi-Scaling and Multi-Shifting.Generalized Hough Transform with Template Shapes README.Symmetry-Based B-Spline Algorithm README)
Motivation behind developing four different algos for curve completion was during our research we found that there is no proper algo to complete this task and each task has its own pros and cons.
You can find .ipynb files, testcases and generated images and csv for each algorith in master_folder.
To see eda of input csv you can see eda.ipynb
To see deploment code of our website go to deployment
Curvetopia is a project focused on identifying, regularizing, and beautifying various types of curves in 2D Euclidean space. The project involves converting line art from a PNG image into a set of connected cubic Bezier curves.
We have completed the regularization of curves. For detailed information on this process, please refer to the Regularization Task README.
For the occlusion handling task, we have proposed and implemented the following algorithms:
Process:
Details: For a detailed explanation and implementation of this algorithm, please refer to the Symmetry-Based B-Spline Algorithm README.
Process:
Details: For a detailed explanation and implementation of this algorithm, please refer to the Generalized Hough Transform with Template Shapes README.
Process:
Details: For a detailed explanation and implementation of this algorithm, please refer to the Generalized Hough Transform with Multi-Scaling and Multi-Shifting README.
If you would like to contribute to the Curvetopia project, please refer to the Contributing Guidelines.
This project is licensed under the MIT License. See the LICENSE file for more details.