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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 | |
| import cv2 | |
| model = from_pretrained_keras('Rietta/CycleGAN_DL', compile=False) | |
| imagen = cv2.imread('Kirby.png', 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 = imagen | |
| 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=['Sims', 'Warcraft', "Kirby"], | |
| type='index')], | |
| outputs=gr.outputs.Image(type='numpy')) | |
| #examples=examples) | |
| if __name__ == '__main__': | |
| demo.launch() |