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https://github.com/Enigma-li/Free2CAD


https://github.com/Enigma-li/Free2CAD

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README

        

# Free2CAD: Parsing Freehand Drawings into CAD Commands
![](doc/teaser.png)

## Introduction
This repository contains the implementation of [Free2CAD](http://geometry.cs.ucl.ac.uk/projects/2022/free2cad/) proposed in our SIGGRAPH 2022 paper.
* **Free2CAD: Parsing Freehand Drawings into CAD Commands**

By [Changjian Li](https://enigma-li.github.io/), [Hao Pan](http://haopan.github.io/), [Adrien Bousseau](http://www-sop.inria.fr/members/Adrien.Bousseau/), [Niloy Mitra](http://www0.cs.ucl.ac.uk/staff/n.mitra/),

*ACM Transaction on Graphics (TOG), 41(4), 2022.*

It contains two parts: 1) **network training**, 2) **training dataset** and **trained network deployment** (e.g., for interactive modeling).

The code is released under the **MIT license**.

### Network training
This part contains the **Python** code for building, training and testing the nueral network using [TensorFlow](https://www.tensorflow.org/).

đź’ˇ Great news: we have released the **docker image** used for training to ease the burden for configuration, please read README file within the *networkTraining* folder for more details.

### Training dataset and network deployment
This part contains the code for deploying the trained network in a C++ project that can be an interactive 3D modeling application. It also provides instructions to download the training dataset we generated, and our trained networks.

Please read the README file in *dataAndModel* folder for more details.

### đź”´ IMPORTANT about data downloadingâť—đź”´
The current data hosting is broken, we are working on it to find more permanent alternative places. Hopefull, we can make it alive soon.

## Citation
If you use our code or model, please cite our paper:

@Article{Li:2022:Free2CAD,
Title = {Free2CAD: Parsing Freehand Drawings into CAD Commands},
Author = {Changjian Li and Hao Pan and Adrien Bousseau and Niloy J. Mitra},
Journal = {ACM Trans. Graph. (Proceedings of SIGGRAPH 2022)},
Year = {2022},
Number = {4},
Volume = {41},
Pages={93:1--93:16},
numpages = {16},
DOI={https://doi.org/10.1145/3528223.3530133},
Publisher = {ACM}
}



## Contact
Any questions you could contact Changjian Li ([email protected]) or Hao Pan ([email protected]) for help.