#!/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')