"""
NVIDIA Omniverse NuRec 在座舱数据合成中的应用
基于Omniverse + Isaac Sim + OpenUSD

适用场景:
1. 疲劳检测训练数据生成（不同光照/姿态/种族）
2. 分心检测（手机/交谈/操作中控）
3. CPD儿童检测（不同年龄/姿态/遮挡）
4. OOP异常姿态（脚在仪表板/前倾/躺平）
"""

# Omniverse座舱场景生成伪代码
CABIN_SYNTHESIS_CONFIG = {
    'environment': {
        'vehicle_model': 'SUV_interior.usd',  # OpenUSD座舱模型
        'lighting': [
            {'condition': 'day', 'lux': 5000, 'angle': 45},
            {'condition': 'dusk', 'lux': 500, 'angle': 10},
            {'condition': 'night', 'lux': 5, 'source': 'IR'},
            {'condition': 'tunnel', 'lux': 50, 'flicker': True},
        ],
    },
    'driver': {
        'metahuman_models': ['asian_male_30', 'caucasian_female_45', 
                           'asian_female_25', 'african_male_50'],
        'poses': {
            'normal_driving': {'torso_angle': 90, 'head_pitch': 0},
            'fatigue_mild': {'torso_angle': 85, 'head_pitch': 15, 'eye_closure': 0.3},
            'fatigue_severe': {'torso_angle': 75, 'head_pitch': 30, 'eye_closure': 0.7},
            'distraction_phone': {'head_yaw': -30, 'right_hand': 'lap'},
            'distraction_reach': {'torso_angle': 60, 'right_hand': 'rear'},
        },
    },
    'passenger': {
        'child_models': ['infant_6mo', 'toddler_2yr', 'child_5yr', 'child_8yr'],
        'positions': ['safety_seat_rear', 'footwell', 'under_blanket', 'leaning'],
    },
    'sensors': {
        'dms_camera': {'resolution': '1920x1200', 'fps': 30, 'fov': 50},
        'ir_camera': {'resolution': '640x480', 'fps': 30, 'wavelength': '940nm'},
        'mmwave_radar': {'frequency': '60GHz', 'tx_rx': '4x4'},
    },
    'generation_rate': '1000 fps',  # 合成速度
    'auto_label': True,  # 自动标注
}

def generate_cabin_dataset(scenario, num_samples=10000):
    """
    生成座舱训练数据集
    
    返回: 图像 + 完美标注
    """
    samples = []
    for i in range(num_samples):
        # 1. 随机选择环境
        lighting = random.choice(CABIN_SYNTHESIS_CONFIG['environment']['lighting'])
        
        # 2. 随机选择驾驶员/乘员
        driver_model = random.choice(CABIN_SYNTHESIS_CONFIG['driver']['metahuman_models'])
        pose = random.choice(list(CABIN_SYNTHESIS_CONFIG['driver']['poses'].keys()))
        
        # 3. Omniverse渲染
        # image = omniverse_render(scene_config)
        
        # 4. 自动获取标注
        # labels = get_ground_truth_from_scene()  # 完美标注
        
        samples.append({
            'image_id': f'synth_{scenario}_{i:06d}',
            'lighting': lighting['condition'],
            'driver_model': driver_model,
            'pose': pose,
            'auto_labeled': True,
        })
    
    return samples