app.py

#!/usr/bin/env python
# coding: utf-8

import streamlit as st
from tensorflow.keras.models import load_model
from PIL import Image
import numpy as np
import cv2

model = load_model('Malaria_cnn.h5')

def process_image(img):
    img = img.resize((30, 30)) 
    img = np.array(img)
    img = img / 255.0
    img = np.expand_dims(img, axis=0)
    return img

st.title('Malaria Parazit Tarama')
st.write('Resim seçin ve model tahmin etsin')

file = st.file_uploader('Bir resim seçin', 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)
    st.write(prediction[0])
    if prediction[0]<=.5:
        st.write('Normal')
    else: st.write('Parazit')