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import gradio as gr
from huggingface_hub import hf_hub_download
import torch
import matplotlib.pyplot as plt
import numpy as np
path = hf_hub_download('huggan/ArtGAN', 'ArtGAN.pt')
model = torch.load(path)
device = 'cuda' if torch.cuda.is_available() else 'cpu'
def generate(seed):
with torch.no_grad():
noise = torch.randn(seed, 100, 1, 1, device=device)
with torch.no_grad():
art = model(noise).detach().cpu()
gen = np.transpose(art[-1], (1, 2, 0))
fig = plt.figure(figsize=(5, 5))
plt.imshow(gen)
plt.axis('off')
return fig
gr.Interface(
fn=generate,
inputs=[
gr.inputs.Slider
(
label='noise',
minimum=10,
maximum=100,
step=1,
default=25
)
],
outputs=gr.outputs.Image(type='plot'),
title='ArtGAN',
description='Generate A Abract Art Using ArtGAN',
).launch()
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