import numpy as np
import gradio as gr
from PIL import Image
import keras
from huggingface_hub import from_pretrained_keras


model = from_pretrained_keras("keras-io/lowlight-enhance-mirnet", compile=False)
examples = ['examples/179.png', 'examples/493.png', 'examples/780.png']


def infer(original_image):
    image = keras.utils.img_to_array(original_image)
    image = image.astype("float32") / 255.0
    image = np.expand_dims(image, axis=0)
    output = model.predict(image)
    output_image = output[0] * 255.0
    output_image = output_image.clip(0, 255)
    output_image = output_image.reshape(
        (np.shape(output_image)[0], np.shape(output_image)[1], 3)
    )
    output_image = np.uint32(output_image)
    return output_image

iface = gr.Interface(
    fn=infer,
    inputs=gr.inputs.Image(type="pil"), 
                     outputs=gr.outputs.Image(type="pil", label="predicted"),
                     title=title,
                     description=description,
                     examples=examples,
                     enable_queue=True)
iface.launch(debug=True)