Update app.py

app.py

@@ -1,44 +0,0 @@
-import numpy as np
-import gradio as gr
-from PIL import Image
-import tensorflow as tf
-from tensorflow 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 = model.predict(image)
-    print(len(output))
-    print([len(a) for a in output])
-    '''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)'''
-    
-    output_image = tf.cast((output[0, :, :, :] * 255), dtype=np.uint8)
-    
-    
-    #output_image = Image.fromarray(output_image.numpy())
-    output_image = output_image.numpy()
-    print(output_image.shape())
-    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=[gr.outputs.Image(label="image", type="numpy")],
-    #examples=examples,
-    article = "Author: <a href=\"https://huggingface.co/vumichien\">Vu Minh Chien</a>. Based on the keras example from <a href=\"https://keras.io/examples/vision/mirnet/\">Soumik Rakshit</a>",
-    ).launch(debug=True)