use avx_image::ocr::*;

// Inicializar OCR
let mut ocr = OcrEngine::new()?;
ocr.load_model("pt-BR")?;

// Processar imagem
let img = NativeImageBuffer::from_file("document.jpg")?;
let result = ocr.recognize(&img)?;

// Extrair texto
for block in result.blocks() {
    println!("{}: {}", block.confidence(), block.text());
}

use avx_image::face::*;

// Detector de rostos
let detector = FaceDetector::new()?;
detector.load_model(FaceModel::RetinaFace)?;

let img = NativeImageBuffer::from_file("photo.jpg")?;
let faces = detector.detect(&img)?;

for face in faces {
    println!("Face: {:?}", face.bounding_box());
    println!("Confiança: {:.2}%", face.confidence() * 100.0);

    // Landmarks faciais (68 pontos)
    let landmarks = face.landmarks();

    // Reconhecimento de emoção
    let emotion = face.emotion()?;
    println!("Emoção: {:?}", emotion);
}

use avx_image::synthesis::*;

// Inicializar Stable Diffusion
let mut sd = StableDiffusion::new()?;
sd.load_model("sd-v2.1")?;

// Configuração
let config = GenerationConfig {
    width: 768,
    height: 512,
    steps: 30,
    cfg_scale: 7.5,
    seed: Some(42),
};

// Gerar imagem
let prompt = "paisagem brasileira ao pôr do sol, detalhada";
let negative = "baixa qualidade, desfocado";

let generated = sd.generate(prompt, negative, &config)?;
generated.save("output.png")?;

use avx_image::nerf::*;

// Carregar imagens de diferentes ângulos
let images = vec![
    NativeImageBuffer::from_file("view_1.jpg")?,
    NativeImageBuffer::from_file("view_2.jpg")?,
    // ... mais imagens
];

let camera_poses = load_camera_poses("poses.json")?;

// Treinar NeRF
let mut nerf = NeRFScene::new()?;
nerf.train(&images, &camera_poses, 10000)?;

// Sintetizar nova visão
let new_pose = CameraPose::from_position_target(
    [0.0, 0.0, 5.0],
    [0.0, 0.0, 0.0],
    [0.0, 1.0, 0.0],
);

let synthesized = nerf.render(&new_pose, 512, 512)?;

use avx_image::medical::*;

// Carregar DICOM
let dicom = DicomImage::from_file("scan.dcm")?;

println!("Paciente: {}", dicom.patient_name());
println!("Modalidade: {}", dicom.modality());

// Segmentação de órgãos
let segmenter = OrganSegmenter::new()?;
let segmented = segmenter.segment(&dicom, OrganType::Lung)?;

// Medições
let volume = segmented.calculate_volume()?;
println!("Volume: {:.2} cm³", volume);

// Renderização 3D
let renderer = VolumeRenderer::new();
let render_3d = renderer.render(&segmented)?;