import streamlit as st
from PIL import Image, ImageEnhance
import pandas as pd
import numpy as np
import io
import os
from pathlib import Path

def zoom_at(img, x, y, zoom):
    # ...existing code...

# App title and description
st.set_page_config(page_title="Cell Explorer", layout="wide")
st.title("CLL Explorer: Annotation Tool")

st.markdown("""
### About this Application
This tool helps researchers analyze microscope images of blood cells for malaria detection:
- Upload microscope images
- Adjust image view with zoom and enhancement controls
- Detect and measure cells automatically
- Save analysis results and annotations

**Note**: Cell measurements are in micrometers (µm)
""")

# Create tabs for different functions
tab1, tab2, tab3 = st.tabs(["Image Analysis", "Detection Results", "Settings"])

with tab1:
    col1, col2 = st.columns([2,1])

    with col1:
        uploaded_files = st.file_uploader("Upload Images", accept_multiple_files=True, type=["jpg", "png"])

        if uploaded_files:
            img_index = st.selectbox("Select Image", range(len(uploaded_files)))
            img_data = uploaded_files[img_index].read()
            img = Image.open(io.BytesIO(img_data)).resize((800, 800))

            st.image(img, caption="Original Image", use_column_width=True)

    with col2:
        if uploaded_files:
            st.subheader("Image Controls")
            x = st.slider("X Position", 0, 800, 400)
            y = st.slider("Y Position", 0, 800, 400)
            zoom = st.slider("Zoom Level", 1, 10, 5)

            with st.expander("Enhancement Settings"):
                contrast = st.slider("Contrast", 0.0, 5.0, 1.0)
                brightness = st.slider("Brightness", 0.0, 5.0, 1.0)
                sharpness = st.slider("Sharpness", 0.0, 2.0, 1.0)

            img_zoomed = zoom_at(img, x, y, zoom)
            img_processed = ImageEnhance.Contrast(img_zoomed).enhance(contrast)
            img_processed = ImageEnhance.Brightness(img_processed).enhance(brightness)
            img_processed = ImageEnhance.Sharpness(img_processed).enhance(sharpness)

            st.image(img_processed, caption="Processed View", use_column_width=True)

with tab2:
    if uploaded_files:
        st.subheader("Cell Detection Results")
        # Add your existing cell detection code here

        col1, col2 = st.columns(2)
        with col1:
            description = st.text_area("Analysis Notes", "")
        with col2:
            if st.button("Save Analysis"):
                timestamp = pd.Timestamp.now().strftime("%Y%m%d_%H%M%S")
                save_dir = Path("analysis_results") / timestamp
                save_dir.mkdir(parents=True, exist_ok=True)

                img_processed.save(save_dir / "processed_image.jpg")
                with open(save_dir / "analysis_notes.txt", "w") as f:
                    f.write(description)
                st.success(f"Analysis saved to {save_dir}")

with tab3:
    st.subheader("Application Settings")
    st.checkbox("Enable Auto-Detection", value=True)
    st.selectbox("Measurement Unit", ["Micrometers", "Pixels"])
    st.number_input("Detection Confidence Threshold", 0.0, 1.0, 0.5)