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

try:
    model = load_model("my_model.keras")
    st.write("Model loaded successfully!")
except Exception as e:
    st.write("Error loading model:", str(e))

def process_image(img):
    img = img.resize((170,170)) # boyutunu 170 x 170 pixel yaptık
    img = np.array(img)
    img = img/255.0 #normalize ettik
    img = np.expand_dims(img, axis= 0)
    return img

st.title("Kanser Resmi Sınıflandırma :cancer:")
st.write("Resim seç ve model kanser olup olmadığını tahmin etsin")

file = st.file_uploader("Bir reaim 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 = ["Kanser Değil", "Kanser"]
    st.write(class_names[predicted_class])
    st.write("Model prediction (raw):", prediction)