video/rtc/rtc.py

import asyncio
import aiohttp
import cv2  # 导入OpenCV库
import numpy as np
from aiortc import RTCPeerConnection, RTCSessionDescription, RTCConfiguration
from aiortc.mediastreams import MediaStreamTrack
from ocr.ocr_violation_detector import OCRViolationDetector


class VideoTrack(MediaStreamTrack):
    kind = "video"

    def __init__(self, max_frames=1):
        super().__init__()
        self.frames = asyncio.Queue(maxsize=max_frames)

    async def recv(self):
        return await super().recv()


async def rtc_frame_receiver(url, frame_queue):
    """
    对每帧进行检查、只要接收到 RTC 帧且队列为空、就往队列放入cv2格式的帧数据
    """
    pc = RTCPeerConnection(RTCConfiguration(iceServers=[]))
    video_track = VideoTrack()
    pc.addTrack(video_track)

    # 累计帧计数器
    total_frames = 0

    @pc.on("track")
    async def on_track(track):
        nonlocal total_frames
        if track.kind == "video":
            print("接收到视频轨道、开始接收视频帧")
            while True:
                # 接收当前帧并累计计数
                frame = await track.recv()
                # 转换为cv2兼容的BGR格式numpy数组
                frame_cv2 = frame.to_ndarray(format='bgr24')

                # 验证是否为cv2兼容格式
                if isinstance(frame_cv2, np.ndarray) and frame_cv2.ndim == 3 and frame_cv2.shape[2] == 3:
                    total_frames += 1

                    # 对每帧都检查队列状态、队列为空则放入
                    if frame_queue.empty():
                        # 队列为空、放入当前cv2帧
                        await frame_queue.put(frame_cv2)
                        # print(f"第{total_frames}帧：队列为空、已放入新的cv2帧，尺寸: {frame_cv2.shape}")
                    else:
                        # 队列非空、说明上一帧还未处理、跳过当前帧
                        print(f"第{total_frames}帧：队列非空、跳过该帧")
                else:
                    print("帧格式转换失败，不是有效的cv2格式")

    # 创建并设置本地offer
    offer = await pc.createOffer()
    print("已创建本地 SDP Offer")
    await pc.setLocalDescription(offer)

    # 发送offer到服务器
    async with aiohttp.ClientSession() as session:
        print("开始向服务器发送 SDP Offer")
        async with session.post(
                url,
                data=offer.sdp.encode(),
                headers={
                    "Content-Type": "application/sdp",
                    "Content-Length": str(len(offer.sdp))
                },
                ssl=False
        ) as response:
            print("已接收到服务器的响应、开始处理 SDP Answer")
            answer_sdp = await response.text()
            await pc.setRemoteDescription(RTCSessionDescription(sdp=answer_sdp, type='answer'))

    try:
        # 保持连接
        while True:
            await asyncio.sleep(1)
    except KeyboardInterrupt:
        print("用户中断")
    finally:
        print("开始关闭 RTCPeerConnection")
        await pc.close()
        print("已关闭 RTCPeerConnection")


async def frame_consumer(frame_queue):
    """
    从队列中读取cv2帧并处理（队列空时会阻塞等待）

    Args: frame_queue: 帧队列
    """
    # 创建OCR检测器实例（请替换为实际的违禁词文件路径）
    ocr_detector = OCRViolationDetector(
        forbidden_words_path=r"D:\Git\bin\video\ocr\forbidden_words.txt",  # 替换为实际路径
        ocr_confidence_threshold=0.5,)

    while True:
        # 从队列中获取cv2帧（队列为空时会阻塞等待新帧）
        current_frame = await frame_queue.get()

        ocr_detector.detect(current_frame)






        # 验证这是cv2可以处理的帧
        # print(f"从队列获取到cv2帧、尺寸: {current_frame.shape}、数据类型: {current_frame.dtype}")

        # 这里可以添加cv2的处理代码，例如显示帧
        # cv2.imshow('Received Frame', current_frame)
        # if cv2.waitKey(1) & 0xFF == ord('q'):
        #     break

        # print("cv2帧处理完成")

        # 标记任务完成
        frame_queue.task_done()
        # print("帧处理完成、队列已清空")


async def main():
    # WebRTC服务器地址
    url = "http://192.168.110.25:1985/rtc/v1/whep/?app=live&stream=677a4845aa48cb8526c811ad56fc5e60"

    # 创建队列
    frame_queue = asyncio.Queue(maxsize=1)

    # 创建任务
    receiver_task = asyncio.create_task(rtc_frame_receiver(url, frame_queue))
    consumer_task = asyncio.create_task(frame_consumer(frame_queue))

    # 等待任务完成
    await asyncio.gather(receiver_task, consumer_task)


if __name__ == "__main__":
    try:
        asyncio.run(main())
    finally:
        # 确保关闭所有cv2窗口
        cv2.destroyAllWindows()