CycleGAN_DL / app.py
Rietta's picture
Gradio2
4165dfd
from random import choices
import numpy as np
import gradio as gr
from glob import glob
from huggingface_hub import from_pretrained_keras
import cv2
model = from_pretrained_keras('Rietta/CycleGAN_DL', compile=False)
imagen = cv2.imread('Kirby.png')
RGB_img = cv2.cvtColor(imagen, cv2.COLOR_BGR2RGB)
def transform(img, direction):
img = (img / 127.5) - 1
if direction==0:
pred = model.generator_wow.predict(img[None,:,:,:])[0]
elif direction == 1:
pred = model.generator_sims.predict(img[None,:,:,:])[0]
else:
pred = RGB_img
pred = (pred-pred.min())/(pred.max()-pred.min())
pred = (pred * 255).astype(np.uint8)
return pred
demo = gr.Interface(fn=transform,
inputs=[gr.inputs.Image(shape=(256, 256), type='numpy'),
gr.inputs.Radio(choices=['Sims', 'Warcraft', "Kirby"],
type='index')],
outputs=gr.outputs.Image(type='numpy'))
if __name__ == '__main__':
demo.launch()