import gradio as gr
import tensorflow as tf
import os

def create_path_name(file_path, folder_path):
    return folder_path + file_path

path_monkeyPox = "./data/Original Images/Original Images/Monkey Pox/"
path_other = "./data/Original Images/Original Images/Others/"
monkeyPox_data = list(map(lambda x : create_path_name(x,path_monkeyPox), os.listdir(path_monkeyPox)))
other_data = list(map(lambda x : create_path_name(x,path_other), os.listdir(path_other)))

model = tf.keras.models.load_model('./monkey pox_82.75.h5')

def classify_image(img):
    img = img.reshape((-1,224,224,3))
    prediction = model.predict(img).flatten()
    confidences = {'monkeypox': float(prediction[0]), 'other':float(prediction[1])}
    return confidences

gr.Interface(fn=classify_image,
             inputs=gr.Image(shape=(224,224)),
             outputs=gr.Label(),
             examples=[monkeyPox_data[0], monkeyPox_data[1], other_data[0], other_data[1]]
             ).launch()