use iced::{
    Alignment, Element, Length, Settings, Task, Theme,
    widget::{
        Space, button, column, container, image, pick_list, progress_bar, row, scrollable, slider,
        text,
    },
};
use rfd::FileDialog;
use std::path::PathBuf;
use std::sync::Arc;

use crate::gui::bridge::FaceDetectionBridge;
use ::image::{DynamicImage, ImageFormat, RgbImage};

#[derive(Debug, Clone)]
pub enum Message {
    // File operations
    OpenImageDialog,
    ImageSelected(Option<PathBuf>),
    OpenSecondImageDialog,
    SecondImageSelected(Option<PathBuf>),
    SaveOutputDialog,
    OutputPathSelected(Option<PathBuf>),

    // Detection parameters
    ThresholdChanged(f32),
    NmsThresholdChanged(f32),
    ExecutorChanged(ExecutorType),

    // Actions
    DetectFaces,
    CompareFaces,
    ClearResults,

    // Results
    DetectionComplete(DetectionResult),
    ComparisonComplete(ComparisonResult),

    // UI state
    TabChanged(Tab),
    ProgressUpdate(f32),

    // Image loading
    ImageLoaded(Option<Arc<Vec<u8>>>),
    SecondImageLoaded(Option<Arc<Vec<u8>>>),
    ProcessedImageUpdated(Option<Vec<u8>>),
    FaceRoisLoaded(Vec<image::Handle>, Vec<image::Handle>),
}

#[derive(Debug, Clone, PartialEq)]
pub enum Tab {
    Detection,
    Comparison,
    Settings,
}

#[derive(Debug, Clone, PartialEq)]
pub enum ExecutorType {
    MnnCpu,
    #[cfg(feature = "mnn-metal")]
    MnnMetal,
    #[cfg(feature = "mnn-coreml")]
    MnnCoreML,
    OnnxCpu,
    #[cfg(feature = "ort-cuda")]
    OrtCuda,
}

#[derive(Debug, Clone)]
pub enum DetectionResult {
    Success {
        image_path: PathBuf,
        faces_count: usize,
        processed_image: Option<Vec<u8>>,
        processing_time: f64,
    },
    Error(String),
}

#[derive(Debug, Clone)]
pub enum ComparisonResult {
    Success {
        image1_faces: usize,
        image2_faces: usize,
        image1_face_rois: Vec<ndarray::Array3<u8>>,
        image2_face_rois: Vec<ndarray::Array3<u8>>,
        best_similarity: f32,
        processing_time: f64,
    },
    Error(String),
}

#[derive(Debug)]
pub struct FaceDetectorApp {
    // Current tab
    current_tab: Tab,

    // File paths
    input_image: Option<PathBuf>,
    second_image: Option<PathBuf>,
    output_path: Option<PathBuf>,

    // Detection parameters
    threshold: f32,
    nms_threshold: f32,
    executor_type: ExecutorType,

    // UI state
    is_processing: bool,
    progress: f32,
    status_message: String,

    // Results
    detection_result: Option<DetectionResult>,
    comparison_result: Option<ComparisonResult>,

    // Image data for display
    current_image_handle: Option<image::Handle>,
    processed_image_handle: Option<image::Handle>,
    second_image_handle: Option<image::Handle>,

    // Face ROI handles for comparison display
    image1_face_roi_handles: Vec<image::Handle>,
    image2_face_roi_handles: Vec<image::Handle>,
}

impl Default for FaceDetectorApp {
    fn default() -> Self {
        Self {
            current_tab: Tab::Detection,
            input_image: None,
            second_image: None,
            output_path: None,
            threshold: 0.8,
            nms_threshold: 0.3,
            #[cfg(not(any(feature = "mnn-metal", feature = "ort-cuda")))]
            executor_type: ExecutorType::MnnCpu,
            #[cfg(feature = "ort-cuda")]
            executor_type: ExecutorType::OrtCuda,
            is_processing: false,
            progress: 0.0,
            status_message: "Ready".to_string(),
            detection_result: None,
            comparison_result: None,
            current_image_handle: None,
            processed_image_handle: None,
            second_image_handle: None,
            image1_face_roi_handles: Vec::new(),
            image2_face_roi_handles: Vec::new(),
        }
    }
}

impl FaceDetectorApp {
    fn new() -> (Self, Task<Message>) {
        (Self::default(), Task::none())
    }

    fn title(&self) -> String {
        "Face Detector - Rust GUI".to_string()
    }

    fn update(&mut self, message: Message) -> Task<Message> {
        match message {
            Message::TabChanged(tab) => {
                self.current_tab = tab;
                Task::none()
            }

            Message::OpenImageDialog => {
                self.status_message = "Opening file dialog...".to_string();
                Task::perform(
                    async {
                        FileDialog::new()
                            .add_filter("Images", &["jpg", "jpeg", "png", "bmp", "tiff", "webp"])
                            .pick_file()
                    },
                    Message::ImageSelected,
                )
            }

            Message::ImageSelected(path) => {
                if let Some(path) = path {
                    self.input_image = Some(path.clone());
                    self.status_message = format!("Selected: {}", path.display());

                    // Load image data for display
                    Task::perform(
                        async move {
                            match std::fs::read(&path) {
                                Ok(data) => Some(Arc::new(data)),
                                Err(_) => None,
                            }
                        },
                        Message::ImageLoaded,
                    )
                } else {
                    self.status_message = "No file selected".to_string();
                    Task::none()
                }
            }

            Message::OpenSecondImageDialog => Task::perform(
                async {
                    FileDialog::new()
                        .add_filter("Images", &["jpg", "jpeg", "png", "bmp", "tiff", "webp"])
                        .pick_file()
                },
                Message::SecondImageSelected,
            ),

            Message::SecondImageSelected(path) => {
                if let Some(path) = path {
                    self.second_image = Some(path.clone());
                    self.status_message = format!("Second image selected: {}", path.display());

                    // Load second image data for display
                    Task::perform(
                        async move {
                            match std::fs::read(&path) {
                                Ok(data) => Some(Arc::new(data)),
                                Err(_) => None,
                            }
                        },
                        Message::SecondImageLoaded,
                    )
                } else {
                    self.status_message = "No second image selected".to_string();
                    Task::none()
                }
            }

            Message::SaveOutputDialog => Task::perform(
                async {
                    FileDialog::new()
                        .add_filter("Images", &["jpg", "jpeg", "png"])
                        .save_file()
                },
                Message::OutputPathSelected,
            ),

            Message::OutputPathSelected(path) => {
                if let Some(path) = path {
                    self.output_path = Some(path.clone());
                    self.status_message = format!("Output will be saved to: {}", path.display());
                } else {
                    self.status_message = "No output path selected".to_string();
                }
                Task::none()
            }

            Message::ThresholdChanged(value) => {
                self.threshold = value;
                Task::none()
            }

            Message::NmsThresholdChanged(value) => {
                self.nms_threshold = value;
                Task::none()
            }

            Message::ExecutorChanged(executor_type) => {
                self.executor_type = executor_type;
                Task::none()
            }

            Message::DetectFaces => {
                if let Some(input_path) = &self.input_image {
                    self.is_processing = true;
                    self.progress = 0.0;
                    self.status_message = "Detecting faces...".to_string();

                    let input_path = input_path.clone();
                    let output_path = self.output_path.clone();
                    let threshold = self.threshold;
                    let nms_threshold = self.nms_threshold;
                    let executor_type = self.executor_type.clone();

                    Task::perform(
                        async move {
                            FaceDetectionBridge::detect_faces(
                                input_path,
                                output_path,
                                threshold,
                                nms_threshold,
                                executor_type,
                            )
                            .await
                        },
                        Message::DetectionComplete,
                    )
                } else {
                    self.status_message = "Please select an image first".to_string();
                    Task::none()
                }
            }

            Message::CompareFaces => {
                if let (Some(image1), Some(image2)) = (&self.input_image, &self.second_image) {
                    self.is_processing = true;
                    self.progress = 0.0;
                    self.status_message = "Comparing faces...".to_string();

                    let image1 = image1.clone();
                    let image2 = image2.clone();
                    let threshold = self.threshold;
                    let nms_threshold = self.nms_threshold;
                    let executor_type = self.executor_type.clone();

                    Task::perform(
                        async move {
                            FaceDetectionBridge::compare_faces(
                                image1,
                                image2,
                                threshold,
                                nms_threshold,
                                executor_type,
                            )
                            .await
                        },
                        Message::ComparisonComplete,
                    )
                } else {
                    self.status_message = "Please select both images for comparison".to_string();
                    Task::none()
                }
            }

            Message::ClearResults => {
                self.detection_result = None;
                self.comparison_result = None;
                self.processed_image_handle = None;
                self.image1_face_roi_handles.clear();
                self.image2_face_roi_handles.clear();
                self.status_message = "Results cleared".to_string();
                Task::none()
            }

            Message::DetectionComplete(result) => {
                self.is_processing = false;
                self.progress = 100.0;

                match &result {
                    DetectionResult::Success {
                        faces_count,
                        processing_time,
                        processed_image,
                        ..
                    } => {
                        self.status_message = format!(
                            "Detection complete! Found {} faces in {:.2}s",
                            faces_count, processing_time
                        );

                        // Update processed image if available
                        if let Some(image_data) = processed_image {
                            self.processed_image_handle =
                                Some(image::Handle::from_bytes(image_data.clone()));
                        }
                    }
                    DetectionResult::Error(error) => {
                        self.status_message = format!("Detection failed: {}", error);
                    }
                }

                self.detection_result = Some(result);
                Task::none()
            }

            Message::ComparisonComplete(result) => {
                self.is_processing = false;
                self.progress = 100.0;

                match &result {
                    ComparisonResult::Success {
                        best_similarity,
                        processing_time,
                        image1_face_rois,
                        image2_face_rois,
                        ..
                    } => {
                        let interpretation = if *best_similarity > 0.8 {
                            "Very likely the same person"
                        } else if *best_similarity > 0.6 {
                            "Possibly the same person"
                        } else if *best_similarity > 0.4 {
                            "Unlikely to be the same person"
                        } else {
                            "Very unlikely to be the same person"
                        };

                        self.status_message = format!(
                            "Comparison complete! Similarity: {:.3} - {} (Processing time: {:.2}s)",
                            best_similarity, interpretation, processing_time
                        );

                        // Convert face ROIs to image handles
                        let image1_handles = convert_face_rois_to_handles(image1_face_rois.clone());
                        let image2_handles = convert_face_rois_to_handles(image2_face_rois.clone());

                        self.comparison_result = Some(result);
                        return Task::perform(
                            async move { (image1_handles, image2_handles) },
                            |(h1, h2)| Message::FaceRoisLoaded(h1, h2),
                        );
                    }
                    ComparisonResult::Error(error) => {
                        self.status_message = format!("Comparison failed: {}", error);
                    }
                }

                self.comparison_result = Some(result);
                Task::none()
            }

            Message::FaceRoisLoaded(image1_handles, image2_handles) => {
                self.image1_face_roi_handles = image1_handles;
                self.image2_face_roi_handles = image2_handles;
                Task::none()
            }

            Message::ProgressUpdate(progress) => {
                self.progress = progress;
                Task::none()
            }

            Message::ImageLoaded(data) => {
                if let Some(image_data) = data {
                    self.current_image_handle =
                        Some(image::Handle::from_bytes(image_data.as_ref().clone()));
                    self.status_message = "Image loaded successfully".to_string();
                } else {
                    self.status_message = "Failed to load image".to_string();
                }
                Task::none()
            }

            Message::SecondImageLoaded(data) => {
                if let Some(image_data) = data {
                    self.second_image_handle =
                        Some(image::Handle::from_bytes(image_data.as_ref().clone()));
                    self.status_message = "Second image loaded successfully".to_string();
                } else {
                    self.status_message = "Failed to load second image".to_string();
                }
                Task::none()
            }

            Message::ProcessedImageUpdated(data) => {
                if let Some(image_data) = data {
                    self.processed_image_handle = Some(image::Handle::from_bytes(image_data));
                }
                Task::none()
            }
        }
    }

    fn view(&self) -> Element<'_, Message> {
        let tabs = row![
            button("Detection")
                .on_press(Message::TabChanged(Tab::Detection))
                .style(if self.current_tab == Tab::Detection {
                    button::primary
                } else {
                    button::secondary
                }),
            button("Comparison")
                .on_press(Message::TabChanged(Tab::Comparison))
                .style(if self.current_tab == Tab::Comparison {
                    button::primary
                } else {
                    button::secondary
                }),
            button("Settings")
                .on_press(Message::TabChanged(Tab::Settings))
                .style(if self.current_tab == Tab::Settings {
                    button::primary
                } else {
                    button::secondary
                }),
        ]
        .spacing(10)
        .padding(10);

        let content = match self.current_tab {
            Tab::Detection => self.detection_view(),
            Tab::Comparison => self.comparison_view(),
            Tab::Settings => self.settings_view(),
        };

        let status_bar = container(
            row![
                text(&self.status_message),
                Space::with_width(Length::Fill),
                if self.is_processing {
                    Element::from(progress_bar(0.0..=100.0, self.progress))
                } else {
                    Space::with_width(Length::Shrink).into()
                }
            ]
            .align_y(Alignment::Center)
            .spacing(10),
        )
        .padding(10)
        .style(container::bordered_box);

        column![tabs, content, status_bar].into()
    }
}

impl FaceDetectorApp {
    fn detection_view(&self) -> Element<'_, Message> {
        let file_section = column![
            text("Input Image").size(18),
            row![
                button("Select Image").on_press(Message::OpenImageDialog),
                text(
                    self.input_image
                        .as_ref()
                        .map(|p| p
                            .file_name()
                            .unwrap_or_default()
                            .to_string_lossy()
                            .to_string())
                        .unwrap_or_else(|| "No image selected".to_string())
                ),
            ]
            .spacing(10)
            .align_y(Alignment::Center),
            row![
                button("Output Path").on_press(Message::SaveOutputDialog),
                text(
                    self.output_path
                        .as_ref()
                        .map(|p| p
                            .file_name()
                            .unwrap_or_default()
                            .to_string_lossy()
                            .to_string())
                        .unwrap_or_else(|| "Auto-generate".to_string())
                ),
            ]
            .spacing(10)
            .align_y(Alignment::Center),
        ]
        .spacing(10);

        // Image display section
        let image_section = if let Some(ref handle) = self.current_image_handle {
            let original_image = column![
                text("Original Image").size(16),
                container(
                    image(handle.clone())
                        .width(400)
                        .height(300)
                        .content_fit(iced::ContentFit::ScaleDown)
                )
                .style(container::bordered_box)
                .padding(5),
            ]
            .spacing(5)
            .align_x(Alignment::Center);

            let processed_section = if let Some(ref processed_handle) = self.processed_image_handle
            {
                column![
                    text("Detected Faces").size(16),
                    container(
                        image(processed_handle.clone())
                            .width(400)
                            .height(300)
                            .content_fit(iced::ContentFit::ScaleDown)
                    )
                    .style(container::bordered_box)
                    .padding(5),
                ]
                .spacing(5)
                .align_x(Alignment::Center)
            } else {
                column![
                    text("Detected Faces").size(16),
                    container(
                        text("Process image to see results").style(|_theme| text::Style {
                            color: Some(iced::Color::from_rgb(0.6, 0.6, 0.6)),
                        })
                    )
                    .width(400)
                    .height(300)
                    .style(container::bordered_box)
                    .padding(5)
                    .center_x(Length::Fill)
                    .center_y(Length::Fill),
                ]
                .spacing(5)
                .align_x(Alignment::Center)
            };

            row![original_image, processed_section]
                .spacing(20)
                .align_y(Alignment::Start)
        } else {
            row![
                container(
                    text("Select an image to display").style(|_theme| text::Style {
                        color: Some(iced::Color::from_rgb(0.6, 0.6, 0.6)),
                    })
                )
                .width(400)
                .height(300)
                .style(container::bordered_box)
                .padding(5)
                .center_x(Length::Fill)
                .center_y(Length::Fill)
            ]
        };

        let controls = column![
            text("Detection Parameters").size(18),
            row![
                text("Threshold:"),
                slider(0.1..=1.0, self.threshold, Message::ThresholdChanged).step(0.01),
                text(format!("{:.2}", self.threshold)),
            ]
            .spacing(10)
            .align_y(Alignment::Center),
            row![
                text("NMS Threshold:"),
                slider(0.1..=1.0, self.nms_threshold, Message::NmsThresholdChanged).step(0.01),
                text(format!("{:.2}", self.nms_threshold)),
            ]
            .spacing(10)
            .align_y(Alignment::Center),
            row![
                button("Detect Faces")
                    .on_press(Message::DetectFaces)
                    .style(button::primary),
                button("Clear Results").on_press(Message::ClearResults),
            ]
            .spacing(10),
        ]
        .spacing(10);

        let results = if let Some(result) = &self.detection_result {
            match result {
                DetectionResult::Success {
                    faces_count,
                    processing_time,
                    ..
                } => column![
                    text("Detection Results").size(18),
                    text(format!("Faces detected: {}", faces_count)),
                    text(format!("Processing time: {:.2}s", processing_time)),
                ]
                .spacing(5),
                DetectionResult::Error(error) => column![
                    text("Detection Results").size(18),
                    text(format!("Error: {}", error)).style(text::danger),
                ]
                .spacing(5),
            }
        } else {
            column![text("No results yet").style(|_theme| text::Style {
                color: Some(iced::Color::from_rgb(0.6, 0.6, 0.6)),
            })]
        };

        column![file_section, image_section, controls, results]
            .spacing(20)
            .padding(20)
            .into()
    }

    fn comparison_view(&self) -> Element<'_, Message> {
        let file_section = column![
            text("Image Comparison").size(18),
            row![
                button("Select First Image").on_press(Message::OpenImageDialog),
                text(
                    self.input_image
                        .as_ref()
                        .map(|p| p
                            .file_name()
                            .unwrap_or_default()
                            .to_string_lossy()
                            .to_string())
                        .unwrap_or_else(|| "No image selected".to_string())
                ),
            ]
            .spacing(10)
            .align_y(Alignment::Center),
            row![
                button("Select Second Image").on_press(Message::OpenSecondImageDialog),
                text(
                    self.second_image
                        .as_ref()
                        .map(|p| p
                            .file_name()
                            .unwrap_or_default()
                            .to_string_lossy()
                            .to_string())
                        .unwrap_or_else(|| "No image selected".to_string())
                ),
            ]
            .spacing(10)
            .align_y(Alignment::Center),
        ]
        .spacing(10);

        // Image comparison display section
        let comparison_image_section = {
            let first_image = if let Some(ref handle) = self.current_image_handle {
                column![
                    text("First Image").size(16),
                    container(
                        image(handle.clone())
                            .width(350)
                            .height(250)
                            .content_fit(iced::ContentFit::ScaleDown)
                    )
                    .style(container::bordered_box)
                    .padding(5),
                ]
                .spacing(5)
                .align_x(Alignment::Center)
            } else {
                column![
                    text("First Image").size(16),
                    container(text("Select first image").style(|_theme| text::Style {
                        color: Some(iced::Color::from_rgb(0.6, 0.6, 0.6)),
                    }))
                    .width(350)
                    .height(250)
                    .style(container::bordered_box)
                    .padding(5)
                    .center_x(Length::Fill)
                    .center_y(Length::Fill),
                ]
                .spacing(5)
                .align_x(Alignment::Center)
            };

            let second_image = if let Some(ref handle) = self.second_image_handle {
                column![
                    text("Second Image").size(16),
                    container(
                        image(handle.clone())
                            .width(350)
                            .height(250)
                            .content_fit(iced::ContentFit::ScaleDown)
                    )
                    .style(container::bordered_box)
                    .padding(5),
                ]
                .spacing(5)
                .align_x(Alignment::Center)
            } else {
                column![
                    text("Second Image").size(16),
                    container(text("Select second image").style(|_theme| text::Style {
                        color: Some(iced::Color::from_rgb(0.6, 0.6, 0.6)),
                    }))
                    .width(350)
                    .height(250)
                    .style(container::bordered_box)
                    .padding(5)
                    .center_x(Length::Fill)
                    .center_y(Length::Fill),
                ]
                .spacing(5)
                .align_x(Alignment::Center)
            };

            row![first_image, second_image]
                .spacing(20)
                .align_y(Alignment::Start)
        };

        let controls = column![
            text("Comparison Parameters").size(18),
            row![
                text("Threshold:"),
                slider(0.1..=1.0, self.threshold, Message::ThresholdChanged).step(0.01),
                text(format!("{:.2}", self.threshold)),
            ]
            .spacing(10)
            .align_y(Alignment::Center),
            row![
                text("NMS Threshold:"),
                slider(0.1..=1.0, self.nms_threshold, Message::NmsThresholdChanged).step(0.01),
                text(format!("{:.2}", self.nms_threshold)),
            ]
            .spacing(10)
            .align_y(Alignment::Center),
            button("Compare Faces")
                .on_press(Message::CompareFaces)
                .style(button::primary),
        ]
        .spacing(10);

        let results = if let Some(result) = &self.comparison_result {
            match result {
                ComparisonResult::Success {
                    image1_faces,
                    image2_faces,
                    image1_face_rois: _,
                    image2_face_rois: _,
                    best_similarity,
                    processing_time,
                } => {
                    let interpretation = if *best_similarity > 0.8 {
                        (
                            "Very likely the same person",
                            iced::Color::from_rgb(0.2, 0.8, 0.2),
                        )
                    } else if *best_similarity > 0.6 {
                        (
                            "Possibly the same person",
                            iced::Color::from_rgb(0.8, 0.8, 0.2),
                        )
                    } else if *best_similarity > 0.4 {
                        (
                            "Unlikely to be the same person",
                            iced::Color::from_rgb(0.8, 0.6, 0.2),
                        )
                    } else {
                        (
                            "Very unlikely to be the same person",
                            iced::Color::from_rgb(0.8, 0.2, 0.2),
                        )
                    };

                    let mut result_column = column![
                        text("Comparison Results").size(18),
                        text(format!("First image faces: {}", image1_faces)),
                        text(format!("Second image faces: {}", image2_faces)),
                        text(format!("Best similarity: {:.3}", best_similarity)),
                        text(interpretation.0).style(move |_theme| text::Style {
                            color: Some(interpretation.1),
                        }),
                        text(format!("Processing time: {:.2}s", processing_time)),
                    ]
                    .spacing(5);

                    // Add face ROI displays if available
                    if !self.image1_face_roi_handles.is_empty()
                        || !self.image2_face_roi_handles.is_empty()
                    {
                        result_column = result_column.push(text("Detected Faces").size(16));

                        // Create face ROI rows
                        let image1_faces_row = if !self.image1_face_roi_handles.is_empty() {
                            let faces: Element<'_, Message> = self
                                .image1_face_roi_handles
                                .iter()
                                .enumerate()
                                .fold(row![].spacing(5), |row, (i, handle)| {
                                    row.push(
                                        column![
                                            text(format!("Face {}", i + 1)).size(12),
                                            container(
                                                image(handle.clone())
                                                    .width(80)
                                                    .height(80)
                                                    .content_fit(iced::ContentFit::Cover)
                                            )
                                            .style(container::bordered_box)
                                            .padding(2),
                                        ]
                                        .spacing(2)
                                        .align_x(Alignment::Center),
                                    )
                                })
                                .into();

                            column![
                                text("First Image Faces:").size(14),
                                scrollable(faces).direction(scrollable::Direction::Horizontal(
                                    scrollable::Scrollbar::new()
                                )),
                            ]
                            .spacing(5)
                        } else {
                            column![text("First Image Faces: None detected").size(14)]
                        };

                        let image2_faces_row = if !self.image2_face_roi_handles.is_empty() {
                            let faces: Element<'_, Message> = self
                                .image2_face_roi_handles
                                .iter()
                                .enumerate()
                                .fold(row![].spacing(5), |row, (i, handle)| {
                                    row.push(
                                        column![
                                            text(format!("Face {}", i + 1)).size(12),
                                            container(
                                                image(handle.clone())
                                                    .width(80)
                                                    .height(80)
                                                    .content_fit(iced::ContentFit::Cover)
                                            )
                                            .style(container::bordered_box)
                                            .padding(2),
                                        ]
                                        .spacing(2)
                                        .align_x(Alignment::Center),
                                    )
                                })
                                .into();

                            column![
                                text("Second Image Faces:").size(14),
                                scrollable(faces).direction(scrollable::Direction::Horizontal(
                                    scrollable::Scrollbar::new()
                                )),
                            ]
                            .spacing(5)
                        } else {
                            column![text("Second Image Faces: None detected").size(14)]
                        };

                        result_column = result_column.push(image1_faces_row).push(image2_faces_row);
                    }

                    result_column
                }
                ComparisonResult::Error(error) => column![
                    text("Comparison Results").size(18),
                    text(format!("Error: {}", error)).style(text::danger),
                ]
                .spacing(5),
            }
        } else {
            column![
                text("No comparison results yet").style(|_theme| text::Style {
                    color: Some(iced::Color::from_rgb(0.6, 0.6, 0.6)),
                })
            ]
        };

        scrollable(
            column![file_section, comparison_image_section, controls, results]
                .spacing(20)
                .padding(20),
        )
        .into()
    }

    fn settings_view(&self) -> Element<'_, Message> {
        #[allow(unused_mut)]
        let mut executor_options = vec![ExecutorType::MnnCpu, ExecutorType::OnnxCpu];

        #[cfg(feature = "mnn-metal")]
        executor_options.push(ExecutorType::MnnMetal);

        #[cfg(feature = "mnn-coreml")]
        executor_options.push(ExecutorType::MnnCoreML);

        #[cfg(feature = "ort-cuda")]
        executor_options.push(ExecutorType::OrtCuda);

        container(
            column![
                text("Model Settings").size(18),
                row![
                    text("Execution Backend:"),
                    pick_list(
                        executor_options,
                        Some(self.executor_type.clone()),
                        Message::ExecutorChanged,
                    ),
                ]
                .spacing(10)
                .align_y(Alignment::Center),
                text("Detection Thresholds").size(18),
                row![
                    text("Detection Threshold:"),
                    slider(0.1..=1.0, self.threshold, Message::ThresholdChanged).step(0.01),
                    text(format!("{:.2}", self.threshold)),
                ]
                .spacing(10)
                .align_y(Alignment::Center),
                row![
                    text("NMS Threshold:"),
                    slider(0.1..=1.0, self.nms_threshold, Message::NmsThresholdChanged).step(0.01),
                    text(format!("{:.2}", self.nms_threshold)),
                ]
                .spacing(10)
                .align_y(Alignment::Center),
                text("About").size(18),
                text("Face Detection and Embedding - Rust GUI"),
                text("Built with iced.rs and your face detection engine"),
            ]
            .spacing(15)
            .padding(20),
        )
        .height(Length::Shrink)
        .into()
    }
}

impl std::fmt::Display for ExecutorType {
    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
        match self {
            ExecutorType::MnnCpu => write!(f, "MNN (CPU)"),
            #[cfg(feature = "mnn-metal")]
            ExecutorType::MnnMetal => write!(f, "MNN (Metal)"),
            #[cfg(feature = "mnn-coreml")]
            ExecutorType::MnnCoreML => write!(f, "MNN (CoreML)"),
            ExecutorType::OnnxCpu => write!(f, "ONNX (CPU)"),
            #[cfg(feature = "ort-cuda")]
            ExecutorType::OrtCuda => write!(f, "ONNX (CUDA)"),
        }
    }
}

// Helper function to convert face ROIs to image handles
fn convert_face_rois_to_handles(face_rois: Vec<ndarray::Array3<u8>>) -> Vec<image::Handle> {
    face_rois
        .into_iter()
        .filter_map(|roi| {
            // Convert ndarray to image::RgbImage
            let (height, width, _) = roi.dim();
            let (raw_data, _offset) = roi.into_raw_vec_and_offset();

            if let Some(img) = RgbImage::from_raw(width as u32, height as u32, raw_data) {
                // Convert to PNG bytes
                let mut buffer = Vec::new();
                let mut cursor = std::io::Cursor::new(&mut buffer);
                if DynamicImage::ImageRgb8(img)
                    .write_to(&mut cursor, ImageFormat::Png)
                    .is_ok()
                {
                    return Some(image::Handle::from_bytes(buffer));
                }
            }
            None
        })
        .collect()
}

pub fn run() -> iced::Result {
    let settings = Settings {
        antialiasing: true,
        ..Default::default()
    };
    iced::application(
        "Face Detector",
        FaceDetectorApp::update,
        FaceDetectorApp::view,
    )
    .settings(settings)
    .run_with(FaceDetectorApp::new)
}