import streamlit as st
from helper import *
from deepface import DeepFace
import tf_keras


# Set the page title
st.title("Aging Deaging App")

# Create columns for input and output sections
col1, col2 = st.columns(2)

# Input Section
with col1:
    st.header("Input")
    uploaded_image = st.file_uploader("Upload an image", type=["jpg", "jpeg", "png"])
    
    if uploaded_image is not None:
        # Display the uploaded image
        st.image(uploaded_image, caption="Uploaded Image")

        # Display the selected option
        

# Output Section
with col2:
    st.header("Output")
    age_conversion_option = st.radio("Select age conversion option", ("Old to Young", "Young to Old"))
    st.write(f"Selected conversion: {age_conversion_option}")
    if st.button("Generate"):
        if uploaded_image is not None:
            image = Image.open(uploaded_image).convert("RGB")  # Convert to RGB
            image = np.array(image)  # Convert to numpy array for DeepFace and OpenCV

            detections = extract_faces_opencv(image)
            for face in detections:
                face_crop = cv2.resize(face, (256, 256))
                # face_crop = cv2.cvtColor(face_crop, cv2.COLOR_BGR2RGB)
                if age_conversion_option == "Young to Old":
                    processed_image = generate_Y2O(face_crop)
                    st.image(processed_image, caption="Old you", use_container_width=True)
                elif age_conversion_option == "Old to Young":
                    processed_image = generate_O2Y(face_crop)
                    st.image(processed_image, caption="Young you", use_container_width=True)
        else:
            st.warning("Please upload an image before clicking Generate")