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https://github.com/siddeshsambasivam/artest
https://github.com/siddeshsambasivam/artest
Last synced: 22 days ago
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- Host: GitHub
- URL: https://github.com/siddeshsambasivam/artest
- Owner: SiddeshSambasivam
- Created: 2019-01-16T08:36:53.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2019-01-20T04:38:19.000Z (almost 6 years ago)
- Last Synced: 2024-10-23T03:25:43.864Z (23 days ago)
- Language: CSS
- Size: 10.2 MB
- Stars: 0
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# connect to NUS_Guest and VISIT 172.17.212.68:5000
## Getting Started
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.
## Prerequisites
What things you need to install the software and how to install them
```
numpy
flask
cpickle
tensorflow
scipy
tqdm
```
## Installing
A step by step series of examples that tell you how to get a development env running
If the required dependencies (prerequisites) are already installed, please skip this part.
To install these prerequisites, Open the respective command line interface (powershell, terminal) and paste the following:
```
pip install numpy
pip install scipy
pip install tqdm
pip install tensorflow
pip install flask
py -m pip install --user virtualenv
```
To create a virtual environment, open the directory of the project through the command line and enter ther following command,
'''
python -m virtualenv env
'''
Now, there will be a (env) on the side of the terminal line.
# Datasets :
Download the dataset (36GB) and extract it in the misc/fullimages
https://drive.google.com/file/d/1yHqS2zXgCiI9LO4gN-X5W18QYXC5bbQS/view
# Decription :
Artest is a program used to generate a completly new painting by using Generative adverserial model.
# Usage :
To use our tool, connect to NUS-Guest wifi network and type in the following IP Address : http://172.17.212.68:5000/
Please follow the steps listed there to try out the our tool. Do take some time to check out our Facebook, Instagram
and G+ pages and feel free to contact us via email as given on the website.
# Prize Categories :
Categories we would like to enroll for :
1. Top 8
2. Most Beautiful Hack
3. Most Annoying Hack
4. Most Entertainig Hack
5. Most Awesomely Useless Hack
6. Coreteam's Best Roll
# Team member Contribution :
1. Siddesh - Backened Developer
2. Joe - Server Setup
3. Vijai - Social Media setup and Server setup
4. Rohan - Supervising and assissting Server Setup
Finally,Pull requests/changes/stars would be really helpful.
________________________________________________________________________________________________________________________
Inspired by : Generative Adversarial Networks
Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, Yoshua Bengio
https://arxiv.org/abs/1406.2661v1