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from random import choices
import numpy as np
import gradio as gr
from glob import glob
from huggingface_hub import from_pretrained_keras
model = from_pretrained_keras('Jorgvt/CycleGAN_GTA_REAL', compile=False)
def transform(img, direction):
img = (img / 127.5) - 1
if direction==0:
pred = model.generator_g.predict(img[None,:,:,:])[0]
else:
pred = model.generator_f.predict(img[None,:,:,:])[0]
pred = (pred-pred.min())/(pred.max()-pred.min())
pred = (pred * 255).astype(np.uint8)
return pred
examples_gta = [[path, 'GTA->REAL'] for path in glob('Examples/gta*')]
examples_real = [[path, 'REAL->GTA'] for path in glob('Examples/real*')]
examples = [*examples_gta, *examples_real]
demo = gr.Interface(fn=transform,
inputs=[gr.inputs.Image(shape=(256, 256), type='numpy'),
gr.inputs.Radio(choices=['GTA->REAL', 'REAL->GTA'],
type='index')],
outputs=gr.outputs.Image(type='numpy'),
examples=examples)
if __name__ == '__main__':
demo.launch() |