import streamlit as st
from tensorflow.keras.models import load_model
from PIL import Image
import numpy as np

model=load_model('my_cnn_datafruit_model.h5')

def process_image(img):
    img=img.resize((64, 64)) 
    img=np.array(img)
    img=img/255.0  
    img=np.expand_dims(img,axis=0)
    return img

st.title("Hurma Tür Sınıflandırılması") 
st.write('Resim seç')

file=st.file_uploader('Bir Resim Seç',type=['jpg','jpeg', 'png'])

if file is not None:
    img=Image.open(file)
    st.image(img,caption='yüklenen resim')
    image= process_image(img)
    prediction=model.predict(image)
    predicted_class=np.argmax(prediction)

    class_names=['Ajwa','Galaxy','Medjool','Meneifi','Nabtat Ali','Rutab','Shaishe','Sokari','Sugaey']
    st.write(class_names[predicted_class])