Downloads · 30 days
34
3% of all-time downloads
huggan/crypto-gan
crypto-gan is a unconditional image generation model from huggan. Use it for the unconditional image generation task on the model card, and read the license before you ship it in a product. It is set up for tf-keras.
Simple DCGAN implementation in TensorFlow to generate CryptoPunks.
Downloads · 30 days
34
3% of all-time downloads
All-time downloads
1.2K
Public
Repo size
87.9 MB
Likes
18
Public
Click a slice to open those files.
.data-00000-of-000015.3 MB · 95%
From the Hugging Face model README
Simple DCGAN implementation in TensorFlow to generate CryptoPunks.
Project repository: CryptoGANs.
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)
For training, I used the 10000 CryptoPunks images.
