app.py

import gradio as gr
from huggingface_hub import from_pretrained_keras

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

def classify_image(inp):
  print("Classifying image...")
    
  inp = inp.reshape((-1, 224, 224, 3))
  inp = inp/255
  prediction = model.predict(inp)[0]

  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=5),
             examples=["./examples/chocolate cake.jpg", "./examples/cup cakes.jpg", "./examples/mac and cheese.jpg", "./examples/sashimi.jpg"]).launch()