app.py

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

model = load_model('Bulut_CNN_model.keras')

def process_image(img):
    img = img.resize((64, 64))
    img = img.convert('RGB')
    img = np.array(img)
    img = img / 255.0
    img = np.expand_dims(img, axis=0)
    return img

df = pd.read_csv('train.csv') 
class_names = df['label'].unique()
st.write("Resim seç ve model ne olduğunu tahmin etsin")
file = st.file_uploader('Bir resim seç', type=['jpg', 'jpeg', 'png'])

if file is not None:
    img = Image.open(file)
    st.image(img, caption='Yüklenen resim', use_column_width=True)
    image = process_image(img)
    prediction = model.predict(image)
    predicted_class = np.argmax(prediction, axis=1)[0]
    st.write(f"Tahmin edilen sınıf: {class_names[predicted_class]}")