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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) | |
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(label="image", type="pil", shape=(960, 640))], | |
outputs="image").launch(enable_queue=True) |