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)