Upload app.py

app.py

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+#!/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'])
+class_names = ['Normal', 'Parazit']
+
+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)
+    st.write(class_names[predicted_class])