metadata
library_name: tf-keras
tags:
- gan
- dcgan
- huggan
- tensorflow
- unconditional-image-generation
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
