Model description

Simple DCGAN implementation in TensorFlow to generate CryptoPunks.

Generated samples

Project repository: CryptoGANs.

Usage

You can play with the HuggingFace space demo.

Or try it yourself

import tensorflow as tf
import matplotlib.pyplot as plt
from huggingface_hub import from_pretrained_keras

seed = 42
n_images = 36
codings_size = 100
generator = from_pretrained_keras("huggan/crypto-gan")

def generate(generator, seed):
    noise = tf.random.normal(shape=[n_images, codings_size], seed=seed)
    generated_images = generator(noise, training=False)

    fig = plt.figure(figsize=(10, 10))
    for i in range(generated_images.shape[0]):
        plt.subplot(6, 6, i+1)
        plt.imshow(generated_images[i, :, :, :])
        plt.axis('off')
    plt.savefig("samples.png")
    
generate(generator, seed)

Training data

For training, I used the 10000 CryptoPunks images.

Model Plot

View Model Plot

Model Image

Downloads last month
17
Inference Providers NEW
This model is not currently available via any of the supported third-party Inference Providers, and the HF Inference API does not support tf-keras models with pipeline type unconditional-image-generation

Spaces using huggan/crypto-gan 2