SmokingGAN

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An experimental framework for running ML Models inside the Grasshopper / Rhino environment

SmokingGAN 최신버젼 다운로드

최종 버전 다운로드 (.zip)

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# SmokingGAN
An experimental framework for running ML Models inside the Grasshopper / Rhino environment

## Attributions
SmokingGAN is a Hackathon project for the 2020 AEC Tech Symposium organized by [CORE Studio](https://www.thorntontomasetti.com/core-studio) at [Thornton Tomasetti](https://www.thorntontomasetti.com)

This project has been a collaborative effort between [Mayur Mistry](https://github.com/Mistrymm7), [Sergey Pigach](https://github.com/enmerk4r), [Charlie Portelli](https://github.com/Crashnorun) and [Sergio Guindon](https://github.com/sguindon)

**SmokingGAN borrows heavily from the following open-source projects:**

**Fast Style Transfer**: https://github.com/lengstrom/fast-style-transfer

**TF Monodepth 2**: https://github.com/FangGet/tf-monodepth2

## Description
SmokingGAN is an attempt at incorporating GANs into a Rhino / Grasshopper design workflow. The two major parts of the SmokingGAN are the Flask server exposing pre-trained checkpoints (This hackathon version currently serves [A Style GAN](https://github.com/lengstrom/fast-style-transfer) and a [Depth Map generator](https://github.com/FangGet/tf-monodepth2), but can be extended to work with any other pretrained checkpoints) and a Grasshopper plugin that accesses the Flask API and also provides functionality for converting images to meshes based on the depth information.

![2x2](https://github.com/enmerk4r/SmokingGAN/blob/main/Assets/2x2.gif)
![Rhino](https://github.com/enmerk4r/SmokingGAN/blob/main/Assets/Rhino.gif)

This is the basic architectural diagram showing the main components of the API:

![Diagram](https://github.com/enmerk4r/SmokingGAN/blob/main/Images/Image%20GAN%20Flow%20Chart.png)
 
 ## Server Setup
 We recommend creating an Anaconda environment with **Python 3.7** (IMPORTANT: we've ran into serious issues with Tensorflow and Python 3.8)
 ```
 conda create --name your-env-name python=3.7
 conda activate your-env-name
 ```
 Install the necessary dependencies:
 ```
 conda install flask numpy imageio marshmallow matplotlib scipy pillow pandas
 pip install tensorflow==2.3.1
 pip install keras==2.4.3
 pip install tf_slim
 pip install flask
pip install marshmallow
pip install imageio
pip install matplotlib
 ```
Download the following checkpoint files:

***Style Transfer*** - https://drive.google.com/drive/folders/0B9jhaT37ydSyRk9UX0wwX3BpMzQ
 
 ***Depth Map*** - https://drive.google.com/drive/folders/0B9jhaT37ydSyRk9UX0wwX3BpMzQ
 
 Place them into `Flask/Checkpoints/StyleTransfer` and `Flask/Checkpoints/DepthMap` respectively.
 
 Run the server:
 ```
 cd GenerativeModeling/Flask
 python MainFrame.py
 ```
## Grasshopper Setup
Open and build the **GenerativeModeling** solution from the `.NET` folder

In [Rhino's](https://www.rhino3d.com/) command line type in `GrasshopperDeveloperSettings`. In the dialog paste the path to the bin folder for the Visual Studio solution. Click ok and launch [Grasshopper](https://www.grasshopper3d.com/). You should see the SmokingGAN tab appear in the panel.

Have fun:

![Grasshopper](https://github.com/enmerk4r/SmokingGAN/blob/main/Assets/Grasshopper.PNG)
![Flythrough](https://github.com/enmerk4r/SmokingGAN/blob/main/Assets/FlyThrough.gif)
![Rhino Screenshot](https://github.com/enmerk4r/SmokingGAN/blob/main/Assets/RhinoScreenshot.png)

SmokingGAN

SmokingGAN 최신버젼 다운로드

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