import gradio as gr
def predict_image(img):
  img_2d=img.reshape(-1,180,180,3)
  prediction=model.predict(img_2d)[0]
  return {class_names[i]: float(prediction[i]) for i in range(5)}

image = gr.inputs.Image(shape=(180,180))
label = gr.outputs.Label(num_top_classes=5)

gr.Interface(fn=predict_image, inputs=image, outputs=label,interpretation='default').launch()