'''
This is the originall CLL Explorer application that allows users to upload, process, and save images.

The application provides the following functionalities:
- Upload microscope images.
- Adjust image view with zoom and enhancement controls.
- Detect and measure cells automatically.
- Save analysis results and annotations.

The application is divided into the following sections:
1. **Upload Images**: Users can upload microscope images in JPG or PNG format.
2. **Select Image**: Users can select an image from the uploaded files.
3. **Processed Image**: Displays the processed image with zoom and enhancement controls.
4. **Image Controls**: Allows users to adjust the image view with sliders for X and Y coordinates, zoom, contrast, brightness, and sharpness.
5. **Save Options**: Provides options to save the processed image, image description, and image parameters.

To run the application:
1. Save the script in a Python file (e.g., app.py).
2. Run the script using the Streamlit command:
```bash
streamlit run app.py

'''

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

def zoom_at(img, x, y, zoom):
    '''
    Zoom into an image at a specific location.

    Parameters:
    ----------
    img : PIL.Image
        Input image.

    x : int
        X-coordinate of the zoom center.

    y : int
        Y-coordinate of the zoom center.

    zoom : float
        Zoom factor.

    Returns:
    -------
    PIL.Image
        Zoomed image.

    Examples:
    --------
    >>> img = Image.open('image.jpg')
    >>> zoomed_img = zoom_at(img, x=100, y=100, zoom=2.0)
    '''
    w, h = img.size
    zoom2 = zoom * 2
    img = img.crop((x - w / zoom2, y - h / zoom2,
                    x + w / zoom2, y + h / zoom2))
    return img.resize((w, h), Image.LANCZOS)

def apply_enhancements(img, x, y, zoom, contrast, brightness, sharpness):
    '''
    Apply zoom and image enhancements to the input image.

    Parameters:
    ----------
    img : PIL.Image
        Input image.
    x : int
        X-coordinate of the zoom center.
    y : int
        Y-coordinate of the zoom center.
    zoom : float
        Zoom factor.
    contrast : float
        Contrast adjustment factor.
    brightness : float
        Brightness adjustment factor.
    sharpness : float
        Sharpness adjustment factor.

    Returns:
    -------
    PIL.Image
        Enhanced image.
    '''
    zoomed = zoom_at(img, x, y, zoom)
    enhanced_contrast = ImageEnhance.Contrast(zoomed).enhance(contrast)
    enhanced_brightness = ImageEnhance.Brightness(enhanced_contrast).enhance(brightness)
    enhanced_sharpness = ImageEnhance.Sharpness(enhanced_brightness).enhance(sharpness)
    return enhanced_sharpness

st.set_page_config(page_title="CLL Explorer", layout="wide")
st.title("CLL Explorer - Malaria Cell Detection")

st.markdown("""
### About This Application
This tool assists researchers in analyzing microscope images of any cell type. Or something else entirely.
- **Upload** microscope images.
- **Adjust** image view with zoom and enhancement controls.
- **Detect** and measure cells automatically.
- **Save** analysis results and annotations.
""")

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)),
        format_func=lambda x: uploaded_files[x].name
    )
    img_data = uploaded_files[img_index].read()
    img = Image.open(io.BytesIO(img_data)).resize((500, 500))

    # Sidebar for Image Controls
    with st.sidebar:
        st.header("Image Controls")
        x = st.slider("X Coordinate", 0, 500, 250)
        y = st.slider("Y Coordinate", 0, 500, 250)
        zoom = st.slider("Zoom", 1, 10, 5)

        with st.expander("Enhancement Settings", expanded=True):
            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)

        if st.button("Apply Adjustments"):
            processed_img = apply_enhancements(img, x, y, zoom, contrast, brightness, sharpness)
            st.session_state.processed_img = processed_img
        else:
            processed_img = apply_enhancements(img, x, y, zoom, contrast, brightness, sharpness)
            st.session_state.processed_img = processed_img

    # Display Processed Image
    st.subheader("Processed Image")
    if 'processed_img' in st.session_state:
        st.image(st.session_state.processed_img, use_column_width=True, caption="Processed Image")
    else:
        st.image(processed_img, use_column_width=True, caption="Processed Image")

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

    # Save Options
    save_image = st.checkbox("Save Processed Image")
    if save_image:
        st.session_state.processed_img.save("image-processed.jpg")
        st.success("Image saved as `image-processed.jpg`")

    with st.expander("Save Options"):
        description = st.text_area("Describe the image", "")
        if st.button("Save Description"):
            with open("saved_image_description.txt", "w") as f:
                f.write(description)
            st.success("Description saved as `saved_image_description.txt`")

        if st.button("Save Image Parameters"):
            params = {
                "coordinates_x": x,
                "coordinates_y": y,
                "zoom": zoom,
                "contrast": contrast,
                "brightness": brightness,
                "sharpness": sharpness
            }
            with open("saved_image_parameters.json", "w") as f:
                f.write(pd.DataFrame([params]).to_json(orient="records"))
            st.success("Image parameters saved as `saved_image_parameters.json`")

        if st.button("Rename Files"):
            file_ext = str(np.random.randint(100))
            os.rename("image-processed.jpg", f"img_processed{file_ext}.jpg")
            os.rename("saved_image_parameters.json", f"saved_image_parameters{file_ext}.json")
            os.rename("saved_image_description.txt", f"saved_image_description{file_ext}.txt")
            st.success("Files renamed successfully")