app.py

#import libraries
import streamlit as st
from tensorflow.keras.models import load_model
from PIL import Image
import numpy as np
import cv2
model=load_model('src/date_fruit_colab.keras')
def process_image(img):
    img=img.resize((150,150))
    img=np.array(img)
    img=img/255.0
    img=np.expand_dims(img,axis=0)
    return img
st.title("Date Fruit Classification:date_tree:")
st.write("Pick a picture and let the model predict the type of date")
file=st.file_uploader('Pick a picture',type=['jpg','jpeg','png','JPG'])
if file is not None:
    img=Image.open(file)
    st.image(img,caption='loaded picture')
    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])