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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="",
description="description",
examples=examples,
enable_queue=True)
iface.launch(debug=True) |