https://github.com/robertmaxwilliams/optical-illusion-dataset

JSON files with image links and metadata for optical illusions. Stay tuned as it grows and the images are released in gzip format from University host
https://github.com/robertmaxwilliams/optical-illusion-dataset

Last synced: about 2 months ago
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JSON files with image links and metadata for optical illusions. Stay tuned as it grows and the images are released in gzip format from University host

• Host: GitHub
• URL: https://github.com/robertmaxwilliams/optical-illusion-dataset
• Owner: robertmaxwilliams
• Created: 2018-02-04T20:35:30.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2018-04-16T01:11:05.000Z (over 6 years ago)
• Last Synced: 2024-04-24T18:26:23.331Z (5 months ago)
• Language: Python
• Size: 253 KB
• Stars: 31
• Watchers: 2
• Forks: 4
• Open Issues: 2
• Metadata Files:
  • Readme: README.md

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README

        
# optical-illusion-dataset

JSON files with image links and metadata for optical illusions. Stay tuned as it grows and the images are released in gzip format from University host

## Files:

* mo-scraper.py:  final version of web scraping script for moillusions

* moillusions_data.json:  json of image URLs and metadata for moillusions

* mo-downloader.py: downloades images linked in JSON above into data/

* viper-scraper.py: viperlib scraper script

* viperlib_data.json: viperlib image URLs and metadata

* viper-downloader.py: downloades images linked in JSON above into data/

## Sources:

6436 image links and metadata from https://www.moillusions.com/

1454 image links and metadata from http://viperlib.york.ac.uk/

## Download JPEGs:

The full image download can be found here (**6725** images) :

A greatly reduced dataset of only images that have eye-bending patterns is here (**569** images, hand picked):

## My dataset build procese: 

If you want to replicate it, for more latest images, or if some weird bug appears and documentation becomes important:

- run a scraper to make the JSON file of all images

- run a downloader to download images to data/

- make sure `rename`, `mogrify`, and `file` are installed on your system

- run `bash cleanconvert.sh` to convert everything to jpg, and verify all images using `file`

- Investigate lines printed out, but I doubt you'll get anything unless you're unlucky

- look in data/ if it has lots of #####.jpg and nothing else

- rename data/ to something like viper-data/ etc

## Next steps

- come up with a scheme to combine website provided categories (some effort towards this in `combiner.py`)

- train a GAN on the filtered images

- learn a latent space for the images and do dimensionality reduction of some sort on it