NFTs are the current rage. I have realized that most NFT projects are not about selling “art”. The image is just a representation of a token. But most projects come with a promise of some reward in the form of a cryptocurrency. Most buyers buy them with the hope of selling them for a higher price. This is not to say that they don’t have a practical role in metaverse or as store of wealth. I am still learning more about NFTs and working on this project certainly helped me a lot with that.
Making Illustrations, 100 USD:
Probably the most popular form of NFT is images, though they can be audio or video, so the first part is to make those images. This step could be free for you if you are good at illustrations. Since you will need thousands of images, the most convenient way is to make them in layers. So each layer represents a certain part/component of the image. Then you combine these layers in various combinations to generate images. I had an idea for what my images would be, characters representing healthcare workers, so my layers had to have items like scrubs, the character, hair, eyes, mask, cap and so on. I am not good at drawing so I went on to fiverr to hire someone to draw those layers for me. I have to say it was tricky picking the right person for the right price. One tip is to look for sellers who specifically mention NFT images by layers. Because all the layers have to be same sized images with transparent background and the content has to be in line to fit in the right location in the entire image, a lot of the sellers, specially the cheaper ones, were not able to understand that. However, with a little searching, I was able to find one with my budget. She took a week but delivered perfect illustrations.
Generating 1000s of Images and Metadata, 0 USD:
Now that you have your layers, you can stake them in different combinations to generate unique images. You can find many ways of doing that, even some paid services that would do it. Luckily, I know some python so I wrote my own code. Thoroughly enjoyed the process! Now each image has to be associated with a .json file that contains the metadata of the image. Here is how I did it:
