engine/src/renderer/depth.rs

use crate::error::{GeneratorError, Result};
use std::path::Path;

/// Générer une depth map avec Depth Anything V2
/// TODO: Intégrer avec ONNX ou PyO3 pour l'inférence réelle
pub async fn generate_depth_anything(image_path: &Path, output_path: &Path) -> Result<()> {
    eprintln!("⚠️  Depth Anything V2 integration in progress");

    // Pour l'instant, créer une depth map placeholder
    // En production, ce serait un appel à un modèle ONNX ou Python
    create_placeholder_depth_map(image_path, output_path)
}

/// Créer une depth map placeholder basée sur les contenus de l'image
fn create_placeholder_depth_map(image_path: &Path, output_path: &Path) -> Result<()> {
    use image::{DynamicImage, GenericImageView, ImageBuffer, Luma};

    // Charger l'image source
    let source = image::open(image_path).map_err(|e| {
        GeneratorError::DepthGenerationFailed(format!("Failed to load source: {}", e))
    })?;

    let (width, height) = source.dimensions();
    let rgba = source.to_rgba8();

    // Créer une depth map simple basée sur la luminosité
    let mut depth = ImageBuffer::new(width, height);

    for (x, y, pixel) in rgba.enumerate_pixels() {
        // Calculer la luminosité du pixel
        let [r, g, b, _a] = pixel.0;
        let luminance = (0.299 * r as f32 + 0.587 * g as f32 + 0.114 * b as f32) as u8;

        // La profondeur est inverse de la luminosité (les pixels clairs = loin, sombres = près)
        let depth_value = 255 - luminance;
        depth.put_pixel(x, y, Luma([depth_value]));
    }

    // Sauvegarder
    DynamicImage::ImageLuma8(depth)
        .save(output_path)
        .map_err(|e| GeneratorError::DepthGenerationFailed(format!("Failed to save depth: {}", e)))
}

/// Utiliser un modèle ONNX pour la depth estimation
/// Cette fonction sera activée avec la feature "onnx"
#[cfg(feature = "onnx")]
pub async fn generate_depth_onnx(image_path: &Path, output_path: &Path) -> Result<()> {
    eprintln!("⚠️  ONNX depth estimation not yet implemented");
    // TODO: Implémenter avec ort crate (ONNX Runtime)
    create_placeholder_depth_map(image_path, output_path)
}

/// Interface pour différents backends de depth estimation
pub enum DepthBackend {
    PlaceHolder,
    #[cfg(feature = "onnx")]
    Onnx,
    #[cfg(feature = "python")]
    Python,
}

impl DepthBackend {
    pub async fn estimate(&self, image_path: &Path, output_path: &Path) -> Result<()> {
        match self {
            DepthBackend::PlaceHolder => create_placeholder_depth_map(image_path, output_path),
            #[cfg(feature = "onnx")]
            DepthBackend::Onnx => generate_depth_onnx(image_path, output_path).await,
            #[cfg(feature = "python")]
            DepthBackend::Python => generate_depth_python(image_path, output_path).await,
        }
    }
}

#[cfg(feature = "python")]
pub async fn generate_depth_python(image_path: &Path, output_path: &Path) -> Result<()> {
    eprintln!("⚠️  Python depth estimation not yet implemented");
    // TODO: Intégrer PyO3 pour Python
    create_placeholder_depth_map(image_path, output_path)
}