app.py

from PIL import Image
import cv2
import numpy as np

import tensorflow as tf
from keras.models import load_model

import gradio as gr

model =load_model('BrainTumor10Epochs.h5')

def getResult(inp):
    
    inp=np.array(inp)
    input_img = np.expand_dims(inp, axis=0)
    result=np.max(model.predict(input_img))

    if result==0:
        return "No Brain Tumor"
    elif result==1:
        
        return "Yes Brain Tumor"
    

iface=gr.Interface(fn=getResult, 
             inputs=gr.Image(shape=(64, 64)),
             outputs=gr.Label(num_top_classes=2),
             )
if __name__ == "__main__":
    iface.launch()