import numpy as np

def image_classifier(inp):
  confidence_scores = np.random.rand(2)
  confidence_scores /= np.sum(confidence_scores)
  classes = ['cats', 'dogs']
  result = {classes[i] : confidence_scores[i] for i in range(2)}
  return result
    
import gradio as gr

demo = gr.Interface(fn = image_classifier, inputs="image", outputs="label")
demo.launch()