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("Harveenchadha/low-light-image-enhancement", compile=False)
examples = ['examples/179.png', 'examples/493.png', 'examples/780.png']
def infer(original_image):
image = keras.preprocessing.image.img_to_array(original_image)
image = image.astype("float32") / 255.0
image = np.expand_dims(image, axis=0)
output_image = model.predict(image)
output_image = tf.cast((output_image[0, :, :, :] * 255), dtype=np.uint8)
output_image = Image.fromarray(output_image.numpy())
return output_image
iface = gr.Interface(
fn=infer,
title="Low Light Image Enhancement",
description = "Keras Implementation of MIRNet model for light up the dark image 🌆🎆",
inputs=[gr.inputs.Image(label="image", type="pil")],
outputs="image",
examples=examples,
article = "Author: Vu Minh Chien. Based on the keras example from Soumik Rakshit",
).launch(debug=True)