CyberDoggos

:warning: You are not allowed to use the provided images for your own collection: The images are intended for demonstration purposes only. Do not use them to create your own collection. Please replace them with your own art. If you want to make a CyberDoggo tribute collection (like PicassoPunks did for CryptoPunks) please contact me on Twitter before.

This is the original script that was used to create all CyberDoggos. Every single trait was drawn as a standalone image. The final image is then composed by stacking seven layers with different traits on top of each other. For each image and layer one trait is randomly chosen, and the uniqueness of each image is assured.

Setup and Run

This script was done with Python 3.8. All additional requirements can be found in the requiremtents.txt. To install them all at once just run pip install -r requirements.txt in the project folder.

Run python generate.py to start the generation of the images and properties. All generated files will end up in the build folder. The image is saved in the tiny original resolution as well as in an enlarged version. Besides the single images, the properties of each item are serialized into a yaml file. After all items are created, a collage of all images is stitched together.

Make it your own

To make your own collection of generated images you don't even need to touch the Python script. You only have to replace the images in the corresponding folder with your own ones and adapt the three config files.

The config.yaml is used to adjust some general parameters of the collection and generation. Each parameter is well documented in the file.

The config_normal.yaml contains a list of the layers which are stacked on top of each other to generate the image. The order of the layers in the config file corresponds to the stacking order. So make sure to put the background layer at the top of the config file. Each layer has a category value (which is used as the headline for the trait) and a list of multiple traits available at this very layer. Each trait, in turn, consists of ...

• the name of the trait
• a target probability which sums up to one over the complete layer
• the path to the image resource of that trait
• an optional category which can override the category defined in the layer

The config_legend.py is used to mix some manually created images into the collection. The normal image that will be replaced by the legendary one is given by the image id. If you want to create a collection of only randomly created images, you can simply empty that file.