Create app.py

app.py

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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
+examples=['1o.png','2o.png','3o.png']
+iface = gr.Interface(
+    fn=infer,
+    title="Low Light Image Enhancement",
+    description = "Keras Implementation of MIRNet model for lighting up a dark image 🌆🎆",
+    inputs=[gr.inputs.Image(label="image", type="pil")],
+    outputs="image",
+    examples=examples,
+    cache_examples=True,
+    article = "Authors: <a href=\"https://github.com/Uviveknarayan\">Vivek Narayan</a>, <a href=\"https://github.com/chiranjan-7\">Chiranjan</a>,<a href=\"https://github.com/GangaSrujan\">Srujan</a>,<a href=\"https://github.com/RohanPawar3399\">Rohan Pawar</a>,<a href=\"https://github.com/pavankarthik77\">Pavan Karthik</a>").launch(enable_queue=True)