读取帧优化

rtc/rtc.py

@@ -1,64 +1,71 @@
+import queue
 import asyncio
-from datetime import datetime
-
 import aiohttp
-import cv2
+import threading
-import numpy as np
+import time
 from aiortc import RTCPeerConnection, RTCSessionDescription, RTCConfiguration
-from ocr.ocr_violation_detector import OCRViolationDetector
+from aiortc.mediastreams import MediaStreamTrack
-from ws.ws import send_message_to_client
+
+# 创建一个长度为1的队列，用于生产者和消费者之间的通信
+frame_queue = queue.Queue(maxsize=1)
 
 
-async def rtc_frame_receiver(url, frame_queue, stop_event):
+class VideoTrack(MediaStreamTrack):
+    """自定义视频轨道类，继承自MediaStreamTrack"""
+    kind = "video"
+
+    def __init__(self, max_frames=100):
+        super().__init__()
+        self.frames = queue.Queue(maxsize=max_frames)
+
+    async def recv(self):
+        return await super().recv()
+
+
+def webrtc_producer(webrtc_url):
     """
-    接收RTC帧并往队列放入cv2格式的帧数据
+    生产者方法：从WEBRTC读取视频帧并放入队列
-    当队列已满时直接丢弃新帧，不阻塞等待
+    仅当队列空时才放入新帧，否则丢弃
-    当stop_event被设置时停止接收
     """
+    loop = asyncio.new_event_loop()
+    asyncio.set_event_loop(loop)
+
+    # 创建RTCPeerConnection对象，不使用ICE服务器
     pc = RTCPeerConnection(RTCConfiguration(iceServers=[]))
-
+    video_track = VideoTrack()
-    # 累计帧计数器和丢弃帧计数器
+    pc.addTrack(video_track)
-    total_frames = 0
-    dropped_frames = 0
 
     @pc.on("track")
     async def on_track(track):
-        nonlocal total_frames, dropped_frames
         if track.kind == "video":
-            print("接收到视频轨道、开始接收视频帧")
+            print("接收到视频轨道，开始接收视频帧")
-            while not stop_event.is_set():  # 检查是否需要停止
+            while True:
-                # 接收当前帧并累计计数
+                # 从轨道接收视频帧
                 frame = await track.recv()
-                total_frames += 1
+                # 转换为BGR24格式的NumPy数组
+                frame_bgr24 = frame.to_ndarray(format='bgr24')
 
-                # 转换为cv2兼容的BGR格式numpy数组
+                # 检查队列是否为空，为空则加入，否则丢弃
-                frame_cv2 = frame.to_ndarray(format='bgr24')
+                if frame_queue.empty():
-
+                    try:
-                # 验证是否为cv2兼容格式
+                        frame_queue.put_nowait(frame_bgr24)
-                if isinstance(frame_cv2, np.ndarray) and frame_cv2.ndim == 3 and frame_cv2.shape[2] == 3:
+                        print("帧已放入队列")
-                    # 检查队列是否已满
+                    except queue.Full:
-                    if frame_queue.full():
+                        print("队列已满，丢弃帧")
-                        # 队列已满，丢弃当前帧
-                        dropped_frames += 1
-                        print(f"第{total_frames}帧：队列已满，丢弃该帧（累计丢弃: {dropped_frames}）")
-                    else:
-                        # 队列未满，放入当前帧
-                        await frame_queue.put(frame_cv2)
-                        print(f"第{total_frames}帧：已放入队列")
                 else:
-                    print("帧格式转换失败，不是有效的cv2格式")
+                    print("队列非空，丢弃帧")
 
-    # 创建并设置本地offer
+    async def main():
-    offer = await pc.createOffer()
+        # 创建并发送SDP Offer
-    print("已创建本地 SDP Offer")
+        offer = await pc.createOffer()
-    await pc.setLocalDescription(offer)
+        print("已创建本地SDP Offer")
+        await pc.setLocalDescription(offer)
 
-    # 发送offer到服务器
+        # 发送Offer到服务器并接收Answer
-    async with aiohttp.ClientSession() as session:
+        async with aiohttp.ClientSession() as session:
-        print("开始向服务器发送 SDP Offer")
+            print(f"开始向服务器 {webrtc_url} 发送SDP Offer")
-        try:
             async with session.post(
-                    url,
+                    webrtc_url,
                     data=offer.sdp.encode(),
                     headers={
                         "Content-Type": "application/sdp",
@@ -66,107 +73,83 @@ async def rtc_frame_receiver(url, frame_queue, stop_event):
                     },
                     ssl=False
             ) as response:
-                if response.status == 200:
+                print("已接收到服务器的响应")
-                    print("已接收到服务器的响应、开始处理 SDP Answer")
+                answer_sdp = await response.text()
-                    answer_sdp = await response.text()
+                await pc.setRemoteDescription(RTCSessionDescription(sdp=answer_sdp, type='answer'))
-                    await pc.setRemoteDescription(RTCSessionDescription(sdp=answer_sdp, type='answer'))
-                else:
-                    print(f"服务器响应错误: {response.status}")
-                    stop_event.set()
-        except Exception as e:
-            print(f"发送SDP Offer失败: {str(e)}")
-            stop_event.set()
 
-    try:
+        # 保持连接
-        # 保持连接，直到收到停止信号
-        while not stop_event.is_set():
-            await asyncio.sleep(1)
-    except KeyboardInterrupt:
-        print("用户中断")
-    finally:
-        print(f"开始关闭 RTCPeerConnection，共接收{total_frames}帧，丢弃{dropped_frames}帧")
-        await pc.close()
-        print("已关闭 RTCPeerConnection")
-
-
-async def frame_consumer(ip, frame_queue, stop_event):
-    """
-    从队列中阻塞读取cv2帧并处理（队列为空时阻塞等待）
-    检测到违规内容后设置stop_event以终止所有任务
-    """
-    # 创建OCR检测器实例
-    ocr_detector = OCRViolationDetector(
-        forbidden_words_path=r"D:\Git\bin\video\ocr\forbidden_words.txt",
-        ocr_confidence_threshold=0.5, )
-
-    while not stop_event.is_set():  # 检查是否需要停止
         try:
-            # 阻塞等待队列中的帧
+            while True:
-            current_frame = await frame_queue.get()
+                await asyncio.sleep(0.1)
-
+        except KeyboardInterrupt:
-            # 进行OCR检测
+            pass
-            has_violation, words, confidences = ocr_detector.detect(current_frame)
+        finally:
-            print(f"检测结果: {'有违规内容' if has_violation else '无违规内容'}")
+            print("关闭RTCPeerConnection")
-            print(f"检测到的词: {words}")
+            await pc.close()
-            print(f"置信度: {confidences}")
-
-            # 输出所有检测到的违禁词
-            if has_violation:
-                print(f"测试结果：图片中共检测到 {len(words)} 个违禁词：")
-                response_data = {
-                    "status": "stop",
-                    "timestamp": datetime.now().isoformat(),
-                    "violations": [{"word": w, "confidence": c} for w, c in zip(words, confidences)]
-                }
-                await send_message_to_client(ip, response_data)
-
-                for word, conf in zip(words, confidences):
-                    print(f"- {word}（置信度：{conf:.4f}）")
-
-                # 检测到违规，设置停止事件
-                print("检测到违规内容，准备关闭AI检测")
-                stop_event.set()
-
-            # 标记任务完成，允许生产者放入新的帧
-            frame_queue.task_done()
-
-        except Exception as e:
-            print(f"处理帧时发生错误: {str(e)}")
-            frame_queue.task_done()
-
-
-def process_webrtc_stream(ip, webrtc_url):
-    """
-    处理WEBRTC流并持续打印OCR检测结果，检测到违规后关闭
-    队列大小为1，满时直接丢弃新帧
-
-    Args:
-        ip: IP地址
-        webrtc_url: WEBRTC服务器地址
-    """
-    # 创建队列（大小为1）和停止事件
-    frame_queue = asyncio.Queue(maxsize=1)  # 只存储一帧
-    stop_event = asyncio.Event()  # 用于控制任务停止的事件
-
-    # 定义事件循环中的主任务
-    async def main_task():
-        # 创建任务
-        receiver_task = asyncio.create_task(rtc_frame_receiver(webrtc_url, frame_queue, stop_event))
-        consumer_task = asyncio.create_task(frame_consumer(ip, frame_queue, stop_event))
-
-        # 等待任务完成
-        await asyncio.gather(receiver_task, consumer_task)
-
-        # 确保队列处理完毕
-        await frame_queue.join()
 
     try:
-        # 运行事件循环
+        loop.run_until_complete(main())
-        asyncio.run(main_task())
-    except KeyboardInterrupt:
-        print("用户中断处理流程")
-        stop_event.set()
     finally:
-        # 确保关闭所有cv2窗口
+        loop.close()
-        cv2.destroyAllWindows()
+
-        print("AI检测已关闭")
+
+def frame_consumer():
+    """
+    消费者方法：从队列中读取帧并处理
+    每次处理后休眠200ms模拟延迟
+    """
+    print("消费者启动，开始等待帧...")
+    try:
+        while True:
+            # 阻塞等待队列中的帧
+            frame = frame_queue.get()
+            print(f"消费帧，大小: {frame.shape}")
+
+            # 模拟处理延迟
+            time.sleep(0.2)  # 200ms
+
+            # 标记任务完成
+            frame_queue.task_done()
+    except KeyboardInterrupt:
+        print("消费者退出")
+
+
+def start_webrtc_stream(webrtc_url):
+    """
+    启动WebRTC视频流处理的主方法
+    参数: webrtc_url - WebRTC服务器地址
+    """
+    print(f"开始连接到WebRTC服务器: {webrtc_url}")
+
+    # 启动生产者线程
+    producer_thread = threading.Thread(
+        target=webrtc_producer,
+        args=(webrtc_url,),
+        daemon=True,
+        name="webrtc-producer"
+    )
+
+    # 启动消费者线程
+    consumer_thread = threading.Thread(
+        target=frame_consumer,
+        daemon=True,
+        name="frame-consumer"
+    )
+
+    producer_thread.start()
+    consumer_thread.start()
+    print("生产者和消费者线程已启动")
+
+    try:
+        # 保持主线程运行
+        while True:
+            time.sleep(1)
+    except KeyboardInterrupt:
+        print("程序正在退出...")
+
+
+if __name__ == "__main__":
+    # 示例用法
+    # 实际使用时替换为真实的WebRTC服务器地址
+    webrtc_server_url = "http://192.168.110.65:1985/rtc/v1/whep/?app=live&stream=677a4845aa48cb8526c811ad56fc5e60"
+    start_webrtc_stream(webrtc_server_url)