import streamlit as st
import cv2
import numpy as np
from PIL import Image

# Modeli yükle (gender_model.yml dosyan var mı kontrol et)
model = cv2.face.LBPHFaceRecognizer_create()
model.read('gender_model.yml')

st.title('Gender Prediction / Cinsiyet Tahmini')

uploaded_file = st.file_uploader("Upload a face image / Yüz resmi yükleyin", type=["jpg", "jpeg", "png"])

if uploaded_file is not None:
    image = Image.open(uploaded_file).convert('RGB')
    st.image(image, caption='Uploaded Image / Yüklenen Resim', width=400)

    # Görüntüyü OpenCV formatına çevir
    img_np = np.array(image)
    img_gray = cv2.cvtColor(img_np, cv2.COLOR_RGB2GRAY)
    img_resized = cv2.resize(img_gray, (200, 200))

    label, confidence = model.predict(img_resized)
    gender = "Male / Erkek" if label == 0 else "Female / Kadın"

    st.write(f"Prediction / Tahmin: **{gender}**")
    st.write(f"Confidence / Güven: %{round(100 - confidence, 2)}")