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import gradio as gr | |
import matplotlib.pyplot as plt | |
from huggingface_hub import from_pretrained_keras | |
seed = gr.inputs.Slider(step = 1) | |
number_of_examples = gr.inputs.Slider(minimum = 1, maximum = 4, step = 1) | |
image = gr.outputs.Image(type = "plot") | |
model = from_pretrained_keras("merve/anime-faces-generator") | |
def generate_and_save_images(seed, number_of_examples): | |
seed = tf.random.normal([number_of_examples, seed]) | |
predictions = model(seed, training=False) | |
fig = plt.figure(figsize=(16, 64)) | |
for i in range(predictions.shape[0]): | |
plt.subplot(1, 4, i+1) | |
plt.imshow(predictions[i, :, :, :]) | |
plt.axis('off') | |
return plt | |
gr.Interface(generate_and_save_images, inputs = [seed, number_of_examples], outputs = image).launch(debug=True) |