app.py

import gradio as gr
import tensorflow as tf
import numpy as np
import keras
import tensorflow_hub as hub

model = tf.keras.models.load_model('20220815-14421660574557-full-image-set-mobilenetv2-Adam.h5', custom_objects = {"KerasLayer":hub.KerasLayer})

class_name = {0:"Other",1:"monkeypox"}
def predict_image(img):
  img_3d=img.reshape(-1,224,224,3)
  prediction=model.predict(img_3d)[0]
  return {class_name[i]: float(prediction[i]) for i in range(2)}
                               
image = gr.inputs.Image(shape=(224,224))
label = gr.outputs.Label(num_top_classes=2)

gr.Interface(fn=predict_image, inputs=image, outputs=label, capture_session=True, examples=["is_monkeypox.jpg", "not_monkeypox.jpg"]).launch(debug='True')