import gradio as gr
from huggingface_hub import from_pretrained_keras

model = from_pretrained_keras("NikiTricky/resnet50-food101")

def classify_image(inp):
  inp = inp.reshape((-1, 224, 224, 3))
  inp /= 255.0
  prediction = model.predict(inp)
  confidences = {model.config['id2label'][str(i)]: float(prediction[i]) for i in range(101)}
  return confidences

gr.Interface(fn=classify_image, 
             inputs=gr.Image(shape=(224, 224)),
             outputs=gr.Label(num_top_classes=3)).launch()