import json
from keras.models import Model, load_model
import gradio as gr
import cv2
import numpy as np

model = load_model('final_vgg1920epochs.h5', compile=True)

# Opening JSON file
f = open('dat.json')
  
# returns JSON object as 
# a dictionary
data = json.load(f)

keys = list(data)


def Predict(image):
  img = cv2.resize(image, (32,32)) / 255.0
  prediction = model.predict(img.reshape(1,32,32,3))
  print(prediction)
  
  
  return keys[prediction.argmax()],data[keys[prediction.argmax()]]['description'],data[keys[prediction.argmax()]]['symptoms'],data[keys[prediction.argmax()]]['causes'],data[keys[prediction.argmax()]]['treatement-1']

demo=gr.Interface(fn=Predict,
                  inputs="image",
                  outputs=[gr.inputs.Textbox(label='Name Of Disease'),gr.inputs.Textbox(label='Description'),gr.inputs.Textbox(label='Symptoms'),gr.inputs.Textbox(label='Causes'),gr.inputs.Textbox(label='Treatement')],
                  title="Predict Skin Disease")
                 
demo.launch(debug=True)