Difference between revisions of "DCGAN"
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[[File:Dcgan_1.png|600px]] | [[File:Dcgan_1.png|600px]] | ||
| − | 3: Navigate to the folder where the DCGAN script is stored (/home/interactionstation/dcgan.epoch) by | + | 3: Navigate to the folder where the DCGAN script is stored (/home/interactionstation/dcgan.epoch) |
| + | |||
| + | $ cd dcgan.epoch | ||
| + | |||
| + | [[File:Dcgan_2.png|600px]] | ||
| + | |||
| + | 4: '''If you have your own dataset ready, you can skip part 4 till part ...''' | ||
| + | |||
| + | This script also includes a dataset downloader. This allows you to download from Wikiart based on their genres. The usage is quite simple, but requires a bit of attention. In the script 'genre-scraper.py' there is a variable called 'genre_to_scrape' - simply change that to any of the genres listen on the Wikiart [https://www.wikiart.org/en/paintings-by-genre/] website. After changing the variable to the desired genre, run the script with python3. This will create a folder named after the genre inside '/home/interactionstation/dcgan.epoch/', containing all the download images. Note: the script takes a while to finish! | ||
| + | |||
| + | [[File:Dcgan_3.png|600px]] | ||
| + | |||
| + | $ sudo nano genre-scraper.py | ||
| + | |||
| + | [[File:Dcgan_4.png|600px]] | ||
| + | |||
| + | use the arrow keys to move the variable 'genre_to_scrape' and change it to the desired genre from Wikiart. Example: | ||
| + | |||
| + | genre_to_scrape = "nude-painting-nu" | ||
| + | |||
| + | [[File:Dcgan_5.png|600px]] | ||
| + | |||
| + | [[File:Dcgan_6.png|600px]] | ||
| + | |||
| + | save the changes you've made by pressing the following keys in the same order | ||
| + | ctrl+X | ||
| + | Y | ||
| + | enter | ||
| + | |||
| + | [[File:Dcgan_7.png|600px]] | ||
| + | |||
| + | Run the script! Note: this is going to take a while, grab a coffee. | ||
| + | python3 genre-scraper.py | ||
Revision as of 13:54, 16 January 2018
Generating images using A "Deep Convolutional Generative Adversarial Network"
In this tutorial we will be using a modified version of Soumith Chintala's torch implementation (https://github.com/soumith/dcgan.torch) of DCGAN - Deep Convolutional Generative Adversarial Network (https://arxiv.org/pdf/1511.06434.pdf) with a focus on generating images.
Getting started
Because training a DCGAN requires a lot of computing power, head over to the interaction station and sit behind the computer with the 'ml machineq' sticker. This computer runs a Ubuntu installation with (almost) every dependencies required to run some machine learning scripts/programs.
DCGAN
1: Log in to the computer by using the 'interactionstation' account.
username: interactionstation password: interactionstation
2: Start a new 'terminal' window by pressing the windows key (⊞) and typing 'term', followed by pressing 'enter'
⊞ term enter
3: Navigate to the folder where the DCGAN script is stored (/home/interactionstation/dcgan.epoch)
$ cd dcgan.epoch
4: If you have your own dataset ready, you can skip part 4 till part ...
This script also includes a dataset downloader. This allows you to download from Wikiart based on their genres. The usage is quite simple, but requires a bit of attention. In the script 'genre-scraper.py' there is a variable called 'genre_to_scrape' - simply change that to any of the genres listen on the Wikiart [1] website. After changing the variable to the desired genre, run the script with python3. This will create a folder named after the genre inside '/home/interactionstation/dcgan.epoch/', containing all the download images. Note: the script takes a while to finish!
$ sudo nano genre-scraper.py
use the arrow keys to move the variable 'genre_to_scrape' and change it to the desired genre from Wikiart. Example:
genre_to_scrape = "nude-painting-nu"
save the changes you've made by pressing the following keys in the same order
ctrl+X Y enter
Run the script! Note: this is going to take a while, grab a coffee.
python3 genre-scraper.py