I recently purchased an NFT from the Cryptopunks Reload collection. These animations re-create a Cryptopunk by filling in each of the features of a punk one pixel at a time. I was excited to get a hold of one of these and equally excited to try to figure out how they made them. Go check them out!

When working with images in deep learning for generative art, you will almost always use the convolution operator to build networks. Convolution is a function that takes an input image and creates a scaled down, convoluted, representation of the image by passing a kernel over the image in steps called “strides”, multiplying each cell and adding the results to create a value in the output matrix.

My 15 year old son bears a striking resemblance to Crypto Punk #2101. For his birthday, I’d like to get him a high quality, framed print of #2101 that he can showcase proudly in his room. Unfortunately, the original punk images are only available at a very low resolution and aren’t printshop ready. In this post, I’ll show how to upscale a low-rez image using Python, Tensorflow and Keras so the images will be ready for printing at 300 Dots per Inch (DPI).

The CryptoPunks are 32x32x4 images where the 4 element array at each point in the 2D image represents a pixel encoded in the Red, Green, Blue, Transparent (RGBT) encoding scheme. Simplifying the source material is a common method for building and intuition for a dataset. Let's imagine the punks were created with black and white pixels exclusively. By building a set of black and white punks, and then training our model on those punks, we can learn something about the classifier’s performance.

CPUNKS-10K are subsets of the 10,000 labeled images in the CryptoPunks collection by Larva Labs. They have been collected, organized & modified for use in Machine Learning research by tnn1t1s.eth. The source images files and meta-data were designed and created by John Watkinson & Matt Hall.

CPUNKS-10K are subsets of the 10,000 labeled images in the CryptoPunks collection by Larva Labs. They have been collected, organized & modified for use in Machine Learning research by tnn1t1s.eth. The source images files and meta-data were designed and created by John Watkinson & Matt Hall.

The CryptoPunks are a collection of 24x24 pixel art images stored on the Ethereum blockchain as NFTs. There are 10,000 unique Cryptopunks containing a mix of types and attributes.