src/streamlit_app.py

import sys
import os
import tempfile

import streamlit as st

sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))

st.set_page_config(
    page_title="More Close To Whom?",
    page_icon="👨‍👩‍👧",
    layout="wide",
)

st.title("👨‍👩‍👧 More Close To Whom?")
st.caption("Upload photos of father, mother, and child to discover who the child resembles more")

# Backend selector
backend_choice = st.radio(
    "ML Backend",
    ["🧠 DeepFace", "⚡ InsightFace", "🤗 HF Model"],
    horizontal=True,
    help="Select the AI model to use for face analysis",
)

st.divider()

# Upload row: Father | Child (center, wider) | Mother
col_f, col_c, col_m = st.columns([1, 1.3, 1])

with col_f:
    st.markdown("#### 👨 Father")
    tab1, tab2 = st.tabs(["📁 Upload", "📷 Camera"])
    with tab1:
        upload = st.file_uploader(
            "Upload Father Image",
            type=["jpg", "jpeg", "png","webp"],
            key="father_upload",
            label_visibility="collapsed",
        )

    with tab2:
        camera = st.camera_input(
            "Capture Father Image",
            key="father_camera",
            label_visibility="collapsed",
        )

    father_file = camera if camera else upload
    if father_file:
        st.image(father_file, use_container_width=True)

with col_c:
    st.markdown("#### 🧒 Child")
    tab1, tab2 = st.tabs(["📁 Upload", "📷 Camera"])
    with tab1:
        upload = st.file_uploader(
            "Upload child photo",
            type=["jpg", "jpeg", "png","webp"],
            key="child_upload",
            label_visibility="collapsed",
        )

    with tab2:
        camera = st.camera_input(
            "Capture child photo",
            key="child_camera",
            label_visibility="collapsed",
        )

    child_file = camera if camera else upload
    if child_file:
        st.image(child_file, use_container_width=True)

with col_m:
    st.markdown("#### 👩 Mother")
    tab1, tab2 = st.tabs(["📁 Upload", "📷 Camera"])
    with tab1:
        upload = st.file_uploader(
            "Upload mother photo",
            type=["jpg", "jpeg", "png","webp"],
            key="mother_upload",
            label_visibility="collapsed",
        )

    with tab2:
        camera = st.camera_input(
            "Capture mother photo",
            key="mother_camera",
            label_visibility="collapsed",
        )

    mother_file = camera if camera else upload
    if mother_file:
        st.image(mother_file, use_container_width=True)

st.divider()

all_uploaded = all([father_file, child_file, mother_file])

if st.button("▶ Analyze Resemblance", type="primary", disabled=not all_uploaded):
    with st.spinner("Analyzing faces — this may take a moment on first run..."):
        with tempfile.TemporaryDirectory() as tmpdir:
            def save(uploaded, name):
                path = os.path.join(tmpdir, name)
                with open(path, "wb") as f:
                    f.write(uploaded.getvalue())
                return path

            father_path = save(father_file, "father.jpg")
            mother_path = save(mother_file, "mother.jpg")
            child_path  = save(child_file, "child.jpg")

            try:
                if "DeepFace" in backend_choice:
                    from backends.deepface_backend import analyze
                elif "InsightFace" in backend_choice:
                    from backends.insightface_backend import analyze
                else:
                    from backends.hf_backend import analyze

                result = analyze(father_path, mother_path, child_path)

                st.success("Analysis complete!")

                r1, r2, r3 = st.columns(3)
                with r1:
                    st.metric("👨 Father resemblance", f"{result['father_score']}%")
                    st.progress(result["father_score"] / 100)
                with r2:
                    st.metric("👩 Mother resemblance", f"{result['mother_score']}%")
                    st.progress(result["mother_score"] / 100)
                with r3:
                    st.metric("🧒 Estimated child age", f"{result['age']} yrs")

                st.divider()

                diff = abs(result["father_score"] - result["mother_score"])
                if diff < 2:
                    st.info("⚖️ Child resembles both parents almost equally!")
                elif result["father_score"] >= result["mother_score"]:
                    st.success(f"✅ Child looks more like **Father 👨** ({diff:.1f}% difference)")
                else:
                    st.success(f"✅ Child looks more like **Mother 👩** ({diff:.1f}% difference)")

            except ValueError as e:
                st.error(f"⚠️ {e}")
            except Exception as e:
                st.error(f"❌ Analysis failed: {e}")

elif not all_uploaded:
    st.info("👆 Please upload photos of all three family members to begin")