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import gradio as gr | |
import tensorflow as tf | |
import matplotlib.pyplot as plt | |
from huggingface_hub import from_pretrained_keras | |
n_images = 36 | |
codings_size = 100 | |
generator = from_pretrained_keras("huggan/crypto-gan") | |
def generate(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('foo.png') | |
return "foo.png" | |
gr.Interface(fn=generate, | |
inputs=[gr.inputs.Slider(label='Seed', minimum=0, maximum=1000, default=42)], | |
outputs=gr.Image(), | |
title="CryptoGAN", | |
description="These CryptoPunks do not exist.").launch() |