from keras.models import load_model
import cv2
import json
import gradio as gr

model_data=load_model("SkinCancerModel.h5",compile=True)
f=open("data.json")

data=json.load(f)


cancer_class_list=list(data)


def Canccer_Prediction(image):
  image=cv2.resize(image,(180,180))/255.0
  result=model_data.predict(image.reshape(1,180,180,3)).argmax()

  return cancer_class_list[result],data[cancer_class_list[result]]['description'],data[cancer_class_list[result]]['symptoms'],data[cancer_class_list[result]]['causes'],data[cancer_class_list[result]]['treatement-1'],data[cancer_class_list[result]]['treatement-2']


interface=gr.Interface(fn=Canccer_Prediction,
                       inputs="image",
                       outputs=[gr.components.Textbox(label="Cancer Name"),gr.components.Textbox(label="Description"),gr.components.Textbox(label="Symptoms"),gr.components.Textbox(label="Causes"),gr.components.Textbox(label="Treatment 1"),gr.components.Textbox(label="Treatment 2")],
                       enablue_queu=True)
interface.launch(debug=True)