app.py

import gradio as gr
import matplotlib.pyplot as plt
import tensorflow as tf

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, label = "Number of Examples to Generate")
image = gr.outputs.Image(type = "plot")

model = from_pretrained_keras("merve/anime-faces-generator")
def generate_and_save_images(number_of_examples):
  
  seed = tf.random.normal([number_of_examples, 100])
  predictions = model(seed, training=False)

  fig = plt.figure(figsize=(80, 80))

  for i in range(predictions.shape[0]):
      plt.subplot(2, 2, i+1)
      plt.imshow(predictions[i, :, :, :])
      plt.axis('off')
  return fig


description = "Anime face generator made with DCGAN"
gr.Interface(generate_and_save_images, inputs = [number_of_examples], outputs = image, 
title = "Anime Face Generator", description = description).launch()