dsh/dual_camera_system/main.py

"""
双摄像头联动抓拍系统 - 主程序

系统功能:
1. 全景摄像头实时监控和物体检测
2. 检测到人体后,球机自动变焦定位
3. 对人体进行分割并OCR识别衣服上的编号
"""

# 必须在import cv2之前设置，否则FFmpeg多线程解码会导致
# "Assertion fctx->async_lock failed at pthread_frame.c:167" 崩溃
import os
os.environ['OPENCV_FFMPEG_CAPTURE_OPTIONS'] = 'threads;1'

import sys
import time
import argparse
import logging
import threading
from typing import Optional

import cv2
import numpy as np

# 添加项目路径
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))

from config import (
    PANORAMA_CAMERA, PTZ_CAMERA, SDK_PATH,
    DETECTION_CONFIG, PTZ_CONFIG, OCR_CONFIG, COORDINATOR_CONFIG,
    CALIBRATION_CONFIG, LOG_CONFIG
)
from dahua_sdk import DahuaSDK
from panorama_camera import PanoramaCamera, ObjectDetector, PersonTracker, DetectedObject
from ptz_camera import PTZCamera, PTZController
from ocr_recognizer import NumberDetector, PersonInfo
from coordinator import Coordinator, EventDrivenCoordinator


# 配置日志 - 使用LOG_CONFIG
def setup_logging():
    """设置日志配置"""
    log_level = getattr(logging, LOG_CONFIG.get('level', 'INFO'), logging.INFO)
    log_format = LOG_CONFIG.get('format', '%(asctime)s - %(name)s - %(levelname)s - %(message)s')
    log_file = LOG_CONFIG.get('file')
    
    handlers = [logging.StreamHandler()]
    
    if log_file:
        from logging.handlers import RotatingFileHandler
        file_handler = RotatingFileHandler(
            log_file,
            maxBytes=LOG_CONFIG.get('max_bytes', 10*1024*1024),
            backupCount=LOG_CONFIG.get('backup_count', 5)
        )
        file_handler.setFormatter(logging.Formatter(log_format))
        handlers.append(file_handler)
    
    logging.basicConfig(
        level=log_level,
        format=log_format,
        handlers=handlers
    )

setup_logging()
logger = logging.getLogger(__name__)


class DualCameraSystem:
    """
    双摄像头联动抓拍系统
    """
    
    def __init__(self, config_override: dict = None):
        """
        初始化系统
        Args:
            config_override: 配置覆盖
        """
        self.config = config_override or {}
        
        # SDK
        self.sdk = None
        
        # 摄像头
        self.panorama_camera = None
        self.ptz_camera = None
        
        # 检测器和识别器
        self.detector = None
        self.number_detector = None
        
        # 联动控制器
        self.coordinator = None
        
        # 校准器
        self.calibrator = None
        self.calibration_manager = None
        
        # 定时校准
        self.calibration_interval = CALIBRATION_CONFIG.get('interval', 5 * 60)  # 默认5分钟
        self.calibration_thread = None
        self.calibration_running = False
        self.last_calibration_time = 0
        
        # 运行标志
        self.running = False
    
    def initialize(self, skip_calibration: bool = False) -> bool:
        """
        初始化系统组件
        Args:
            skip_calibration: 是否跳过校准
        Returns:
            是否成功
        """
        logger.info("初始化双摄像头联动系统...")
        
        # 先初始化检测器（YOLO/PyTorch），再加载大华SDK
        # 大华SDK与PyTorch共享进程空间时可能导致内存冲突，
        # 先加载PyTorch可避免SDK的内存映射覆盖PyTorch运行时
        
        # 初始化检测器 (YOLO11/RKNN/ONNX)
        try:
            from config import DETECTION_CONFIG
            self.detector = ObjectDetector(
                model_path=self.config.get('model_path', DETECTION_CONFIG.get('model_path')),
                use_gpu=self.config.get('use_gpu', DETECTION_CONFIG.get('use_gpu', True)),
                model_size=self.config.get('model_size', 'n'),
                model_type=self.config.get('model_type', DETECTION_CONFIG.get('model_type', 'auto'))
            )
            logger.info("检测器初始化成功")
        except Exception as e:
            logger.warning(f"检测器初始化失败: {e}")
        
        # 初始化编号检测器 (使用llama-server API)
        try:
            ocr_config = {
                'api_host': self.config.get('ocr_host', OCR_CONFIG['api_host']),
                'api_port': self.config.get('ocr_port', OCR_CONFIG['api_port']),
                'model': self.config.get('ocr_model', OCR_CONFIG['model']),
            }
            self.number_detector = NumberDetector(use_api=True, ocr_config=ocr_config)
            logger.info("编号检测器初始化成功 (使用llama-server API)")
        except Exception as e:
            logger.warning(f"编号检测器初始化失败: {e}")
        
        # 初始化SDK（在检测器之后，避免SDK内存映射与PyTorch冲突）
        sdk_path = os.path.join(
            self.config.get('sdk_path', SDK_PATH['lib_path']),
            self.config.get('netsdk', SDK_PATH['netsdk'])
        )
        
        try:
            self.sdk = DahuaSDK(sdk_path)
            if not self.sdk.init():
                logger.error("SDK初始化失败")
                return False
            logger.info("SDK初始化成功")
        except Exception as e:
            logger.error(f"SDK加载失败: {e}")
            return False
        
        # 初始化摄像头
        panorama_config = self.config.get('panorama_camera', PANORAMA_CAMERA)
        self.panorama_camera = PanoramaCamera(self.sdk, panorama_config)
        
        ptz_config = self.config.get('ptz_camera', PTZ_CAMERA)
        self.ptz_camera = PTZCamera(self.sdk, ptz_config)
        
        # 初始化联动控制器
        self.coordinator = Coordinator(
            self.panorama_camera,
            self.ptz_camera,
            self.detector,
            self.number_detector
        )
        
        # 设置回调
        self._setup_callbacks()
        
        logger.info("系统初始化完成")
        
        # 执行自动校准
        if not skip_calibration:
            if not self._auto_calibrate():
                logger.error("自动校准失败!")
                return False
        
        return True
    
    def _auto_calibrate(self) -> bool:
        """
        执行自动校准
        Returns:
            是否成功
        """
        from calibration import CameraCalibrator, CalibrationManager
        
        logger.info("=" * 50)
        logger.info("开始自动校准...")
        logger.info("=" * 50)
        
        # 连接摄像头
        if not self.panorama_camera.connect():
            logger.error("连接全景摄像头失败，无法进行校准")
            return False
        
        if not self.ptz_camera.connect():
            logger.error("连接球机失败，无法进行校准")
            self.panorama_camera.disconnect()
            return False
        
        # 启动视频流获取帧数据
        if not self.panorama_camera.start_stream_rtsp():
            logger.warning("RTSP视频流启动失败，尝试SDK方式...")
            if not self.panorama_camera.start_stream():
                logger.error("无法启动视频流，校准可能无法获取画面")
        
        # 启动球机视频流（校准需要球机画面做特征匹配）
        if not self.ptz_camera.start_stream_rtsp():
            logger.warning("球机RTSP视频流启动失败，校准将无法进行特征匹配")
            if not self.ptz_camera.start_stream():
                logger.error("无法启动球机视频流，校准将仅依赖运动检测")
        
        # 创建校准器 - 支持视野重叠发现
        self.calibrator = CameraCalibrator(
            ptz_camera=self.ptz_camera,
            get_frame_func=self.panorama_camera.get_frame,
            detect_marker_func=None,
            ptz_capture_func=self._capture_ptz_frame
        )
        
        # 配置重叠发现参数
        overlap_cfg = CALIBRATION_CONFIG.get('overlap_discovery', {})
        self.calibrator.overlap_pan_range = overlap_cfg.get('pan_range', (0, 360))
        self.calibrator.overlap_tilt_range = overlap_cfg.get('tilt_range', (-30, 30))
        self.calibrator.overlap_pan_step = overlap_cfg.get('pan_step', 20)
        self.calibrator.overlap_tilt_step = overlap_cfg.get('tilt_step', 15)
        self.calibrator.stabilize_time = overlap_cfg.get('stabilize_time', 2.0)
        self.calibrator.max_overlap_ranges = overlap_cfg.get('max_overlap_ranges', 3)
        self.calibrator.min_positions_per_range = overlap_cfg.get('min_positions_per_range', 3)
        
        # 校准进度回调
        def on_progress(current: int, total: int, message: str):
            logger.info(f"校准进度: {current}/{total} - {message}")
        
        # 校准完成回调
        def on_complete(result):
            if result.success:
                logger.info(f"校准完成! RMS误差: {result.rms_error:.4f}")
            else:
                logger.error(f"校准失败: {result.error_message}")
        
        self.calibrator.on_progress = on_progress
        self.calibrator.on_complete = on_complete
        
        # 创建校准管理器
        self.calibration_manager = CalibrationManager(self.calibrator)
        
        # 执行视觉校准
        result = self.calibration_manager.auto_calibrate(force=True)
        
        if not result.success:
            logger.error("=" * 50)
            logger.error("校准失败!")
            logger.error(f"原因: {result.error_message}")
            logger.error("=" * 50)
            logger.error("")
            logger.error("请检查以下问题:")
            logger.error("1. 全景摄像头和球机是否正确连接")
            logger.error("2. 球机PTZ控制是否正常")
            logger.error("3. 两台摄像头的视野是否有重叠区域")
            logger.error("4. 场景是否有足够的纹理/特征用于匹配")
            logger.error("5. 球机RTSP视频流是否正常（特征匹配需要球机画面）")
            logger.error("")
            logger.error("您可以尝试:")
            logger.error("- 检查摄像头连接和网络")
            logger.error("- 手动移动球机确认PTZ控制正常")
            logger.error("- 确保场景有足够的纹理/特征")
            logger.error("- 使用 --skip-calibration 跳过校准")
            logger.error("=" * 50)
            
            # 释放资源
            self.panorama_camera.disconnect()
            self.ptz_camera.stop_stream()
            self.ptz_camera.disconnect()
            
            return False
        
        logger.info("=" * 50)
        logger.info("校准成功!")
        logger.info(f"有效校准点: {len(result.points)}")
        logger.info(f"RMS误差: {result.rms_error:.4f} 度")
        logger.info("=" * 50)
        
        return True
    
    def _capture_ptz_frame(self) -> Optional[np.ndarray]:
        """
        从球机抓拍一帧图像
        用于校准时特征匹配
        """
        if self.ptz_camera is None:
            return None
        try:
            return self.ptz_camera.get_frame()
        except Exception as e:
            logger.error(f"球机抓拍失败: {e}")
            return None
    
    def _setup_callbacks(self):
        """设置回调函数"""
        
        def on_person_detected(person: DetectedObject, frame: np.ndarray):
            """人体检测回调"""
            logger.info(f"检测到人体: 位置={person.center}, 置信度={person.confidence:.2f}")
        
        def on_number_recognized(person_info: PersonInfo):
            """编号识别回调"""
            logger.info(
                f"识别到编号: ID={person_info.person_id}, "
                f"编号={person_info.number_text}, "
                f"置信度={person_info.number_confidence:.2f}, "
                f"位置={person_info.number_location}"
            )
        
        self.coordinator.on_person_detected = on_person_detected
        self.coordinator.on_number_recognized = on_number_recognized
    
    def start(self) -> bool:
        """
        启动系统
        Returns:
            是否成功
        """
        if self.running:
            logger.warning("系统已在运行")
            return True
        
        logger.info("启动联动系统...")
        
        if not self.coordinator.start():
            logger.error("联动系统启动失败")
            return False
        
        self.running = True
        logger.info("联动系统启动成功")
        
        # 启动定时校准
        self._start_periodic_calibration()
        
        return True
    
    def stop(self):
        """停止系统"""
        if not self.running:
            return
        
        logger.info("停止联动系统...")
        
        # 停止定时校准
        self._stop_periodic_calibration()
        
        self.coordinator.stop()
        self.running = False
        logger.info("联动系统已停止")
    
    def get_results(self):
        """获取识别结果"""
        if self.coordinator:
            return self.coordinator.get_results()
        return []
    
    def _start_periodic_calibration(self):
        """启动定时校准"""
        if self.calibration_running:
            return
        
        self.calibration_running = True
        self.calibration_thread = threading.Thread(
            target=self._periodic_calibration_worker, 
            daemon=True
        )
        self.calibration_thread.start()
        # 格式化显示间隔
        interval_hours = self.calibration_interval // 3600
        if interval_hours >= 24:
            interval_str = f"{interval_hours // 24}天"
        elif interval_hours >= 1:
            interval_str = f"{interval_hours}小时"
        else:
            interval_str = f"{self.calibration_interval // 60}分钟"
        logger.info(f"定时校准已启动 (间隔: {interval_str})")
    
    def _stop_periodic_calibration(self):
        """停止定时校准"""
        self.calibration_running = False
        if self.calibration_thread:
            self.calibration_thread.join(timeout=2)
            self.calibration_thread = None
        logger.info("定时校准已停止")
    
    def _periodic_calibration_worker(self):
        """定时校准工作线程"""
        import time
        
        while self.calibration_running:
            try:
                # 等待校准间隔
                for _ in range(self.calibration_interval):
                    if not self.calibration_running:
                        return
                    time.sleep(1)
                
                if not self.calibration_running:
                    return
                
                # 执行校准
                logger.info("=" * 50)
                logger.info("执行定时校准...")
                logger.info("=" * 50)
                
                result = self._auto_calibrate()
                
                if result:
                    logger.info("定时校准成功!")
                else:
                    logger.warning("定时校准失败, 将在下次间隔重试")
                
            except Exception as e:
                logger.error(f"定时校准错误: {e}")
                time.sleep(10)
    
    def manual_calibrate(self) -> bool:
        """
        手动触发校准
        Returns:
            是否成功
        """
        logger.info("手动触发校准...")
        return self._auto_calibrate()
    
    def cleanup(self):
        """清理资源"""
        self.stop()
        
        # 确保定时校准停止
        self._stop_periodic_calibration()
        
        if self.sdk:
            self.sdk.cleanup()
        
        logger.info("系统资源已清理")


def run_interactive(system: DualCameraSystem):
    """
    交互模式运行
    Args:
        system: 系统实例
    """
    print("\n双摄像头联动系统 - 交互模式")
    print("=" * 50)
    print("命令:")
    print("  s - 开始/停止联动")
    print("  r - 获取识别结果")
    print("  t - 手动跟踪 (输入 x y)")
    print("  c - 抓拍快照")
    print("  b - 手动校准")
    print("  q - 退出")
    print("=" * 50)
    
    running = False
    
    while True:
        try:
            cmd = input("\n> ").strip().lower()
            
            if cmd == 'q':
                break
            
            elif cmd == 's':
                if running:
                    system.stop()
                    running = False
                    print("联动已停止")
                else:
                    if system.start():
                        running = True
                        print("联动已启动")
            
            elif cmd == 'r':
                results = system.get_results()
                if results:
                    print(f"获取到 {len(results)} 个识别结果:")
                    for r in results:
                        print(f"  ID={r.person_id}, 编号={r.number_text}, 置信度={r.number_confidence:.2f}")
                else:
                    print("暂无识别结果")
            
            elif cmd == 't':
                try:
                    coords = input("输入坐标 (x y, 范围0-1): ").strip().split()
                    x, y = float(coords[0]), float(coords[1])
                    system.coordinator.force_track_position(x, y)
                    print(f"已移动到位置 ({x:.2f}, {y:.2f})")
                except Exception as e:
                    print(f"输入错误: {e}")
            
            elif cmd == 'c':
                frame = system.coordinator.capture_snapshot()
                if frame is not None:
                    filename = f"snapshot_{int(time.time())}.jpg"
                    cv2.imwrite(filename, frame)
                    print(f"快照已保存: {filename}")
                else:
                    print("抓拍失败")
            
            elif cmd == 'b':
                print("开始手动校准...")
                if system.manual_calibrate():
                    print("校准成功!")
                else:
                    print("校准失败!")
            
            else:
                print("未知命令")
                
        except KeyboardInterrupt:
            break
        except Exception as e:
            print(f"错误: {e}")
    
    print("退出交互模式")


def main():
    """主函数"""
    parser = argparse.ArgumentParser(description='双摄像头联动抓拍系统')
    
    parser.add_argument('--panorama-ip', type=str, help='全景摄像头IP')
    parser.add_argument('--ptz-ip', type=str, help='球机IP')
    parser.add_argument('--username', type=str, default='admin', help='用户名')
    parser.add_argument('--password', type=str, default='admin123', help='密码')
    parser.add_argument('--model', type=str, help='检测模型路径 (默认使用YOLO11n)')
    parser.add_argument('--model-size', type=str, default='n', 
                        choices=['n', 's', 'm', 'l', 'x'],
                        help='YOLO11模型尺寸 (n/s/m/l/x)')
    parser.add_argument('--no-gpu', action='store_true', help='不使用GPU')
    parser.add_argument('--ocr-host', type=str, default='localhost', help='OCR API服务器地址')
    parser.add_argument('--ocr-port', type=int, default=8111, help='OCR API端口')
    parser.add_argument('--ocr-model', type=str, default='PaddleOCR-VL-1.5-GGUF.gguf', help='OCR模型名称')
    parser.add_argument('--interactive', action='store_true', help='交互模式')
    parser.add_argument('--demo', action='store_true', help='演示模式(不连接实际摄像头)')
    parser.add_argument('--skip-calibration', action='store_true', help='跳过自动校准')
    parser.add_argument('--force-calibration', action='store_true', help='强制重新校准')
    
    args = parser.parse_args()
    
    # 构建配置
    config = {}
    
    if args.panorama_ip:
        config['panorama_camera'] = {
            **PANORAMA_CAMERA,
            'ip': args.panorama_ip,
            'username': args.username,
            'password': args.password,
        }
    
    if args.ptz_ip:
        config['ptz_camera'] = {
            **PTZ_CAMERA,
            'ip': args.ptz_ip,
            'username': args.username,
            'password': args.password,
        }
    
    if args.model:
        config['model_path'] = args.model
    
    config['model_size'] = args.model_size
    config['use_gpu'] = not args.no_gpu
    config['ocr_host'] = args.ocr_host
    config['ocr_port'] = args.ocr_port
    config['ocr_model'] = args.ocr_model
    
    # 演示模式
    if args.demo:
        print("演示模式: 使用模拟数据")
        run_demo()
        return
    
    # 创建系统实例
    system = DualCameraSystem(config)
    
    try:
        # 初始化 (包含自动校准)
        if not system.initialize(skip_calibration=args.skip_calibration):
            print("\n系统初始化失败!")
            if not args.skip_calibration:
                print("提示: 可使用 --skip-calibration 跳过校准")
            return 1
        
        # 运行
        if args.interactive:
            run_interactive(system)
        else:
            # 自动模式
            print("启动联动系统...")
            if not system.start():
                print("启动失败")
                return 1
            
            print("系统运行中,按Ctrl+C停止")
            while True:
                time.sleep(1)
                results = system.get_results()
                if results:
                    for r in results:
                        if r.number_text:
                            print(f"[识别] ID={r.person_id}, 编号={r.number_text}")
    
    except KeyboardInterrupt:
        print("\n接收到停止信号")
    
    finally:
        system.cleanup()
    
    return 0


def run_demo():
    """演示模式"""
    print("\n演示模式 - 双摄像头联动系统")
    print("=" * 60)
    print("""
系统架构:
┌─────────────────────────────────────────────────────────────┐
│                    全景摄像头 (Panorama)                     │
│  ┌─────────┐    ┌─────────┐    ┌─────────┐                 │
│  │ 视频流  │ -> │ 人体检测 │ -> │ 位置计算 │                 │
│  └─────────┘    └─────────┘    └─────────┘                 │
└─────────────────────────────────────────────────────────────┘
                          │
                          ▼ 检测到人体位置 (x_ratio, y_ratio)
┌─────────────────────────────────────────────────────────────┐
│                      球机 (PTZ Camera)                       │
│  ┌─────────┐    ┌─────────┐    ┌─────────┐                 │
│  │ PTZ控制 │ -> │ 精确定位 │ -> │ 变焦放大 │                 │
│  └─────────┘    └─────────┘    └─────────┘                 │
└─────────────────────────────────────────────────────────────┘
                          │
                          ▼ 变焦后的人体图像
┌─────────────────────────────────────────────────────────────┐
│                     识别模块 (OCR)                           │
│  ┌─────────┐    ┌─────────┐    ┌─────────┐                 │
│  │人体分割 │ -> │ 区域检测 │ -> │ OCR识别 │ -> 编号结果    │
│  └─────────┘    └─────────┘    └─────────┘                 │
└─────────────────────────────────────────────────────────────┘

工作流程:
1. 全景摄像头实时获取视频流
2. 使用YOLO11检测画面中的人体
3. 计算人体在画面中的相对位置
4. 控制球机PTZ移动到对应位置
5. 球机变焦放大人体区域
6. 对人体进行分割,提取服装区域
7. 使用OCR识别服装上的编号
8. 输出识别结果

主要组件:
- dahua_sdk.py: 大华SDK封装
- panorama_camera.py: 全景摄像头和人体检测
- ptz_camera.py: 球机PTZ控制
- ocr_recognizer.py: 人体分割和OCR识别
- coordinator.py: 联动控制逻辑
""")
    
    print("=" * 60)
    print("\n使用方法:")
    print("  python main.py --panorama-ip 192.168.1.100 --ptz-ip 192.168.1.101")
    print("  python main.py --interactive  # 交互模式")
    print("  python main.py --demo         # 演示说明")


if __name__ == '__main__':
    sys.exit(main() or 0)