RTC提交

rtc/rtc.py

@@ -5,57 +5,46 @@ import aiohttp
 import cv2
 import numpy as np
 from aiortc import RTCPeerConnection, RTCSessionDescription, RTCConfiguration
-from aiortc.mediastreams import MediaStreamTrack
 from ocr.ocr_violation_detector import OCRViolationDetector
 from ws.ws import send_message_to_client
 
 
-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, stop_event):
     """
-    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
+    接收RTC帧并往队列放入cv2格式的帧数据
+    当队列已满时直接丢弃新帧，不阻塞等待
     当stop_event被设置时停止接收
     """
     pc = RTCPeerConnection(RTCConfiguration(iceServers=[]))
-    video_track = VideoTrack()
-    pc.addTrack(video_track)
 
-    # 累计帧计数器
+    # 累计帧计数器和丢弃帧计数器
     total_frames = 0
+    dropped_frames = 0
 
     @pc.on("track")
     async def on_track(track):
-        nonlocal total_frames
+        nonlocal total_frames, dropped_frames
         if track.kind == "video":
             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
                 # 接收当前帧并累计计数
                 frame = await track.recv()
+                total_frames += 1
+
                 # 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
+                    # 检查队列是否已满
-
+                    if frame_queue.full():
-                    # 对每帧都检查队列状态、队列为空则放入
+                        # 队列已满，丢弃当前帧
-                    if frame_queue.empty() and not stop_event.is_set():  # 确保还未收到停止信号
+                        dropped_frames += 1
-                        # 队列为空、放入当前cv2帧
+                        print(f"第{total_frames}帧：队列已满，丢弃该帧（累计丢弃: {dropped_frames}）")
-                        await frame_queue.put(frame_cv2)
                     else:
-                        # 队列非空或已收到停止信号、跳过当前帧
+                        # 队列未满，放入当前帧
-                        if not stop_event.is_set():
+                        await frame_queue.put(frame_cv2)
-                            print(f"第{total_frames}帧：队列非空、跳过该帧")
+                        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")
 
@@ -67,18 +56,26 @@ async def rtc_frame_receiver(url, frame_queue, stop_event):
     # 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(
+        try:
-                url,
+            async with session.post(
-                data=offer.sdp.encode(),
+                    url,
-                headers={
+                    data=offer.sdp.encode(),
-                    "Content-Type": "application/sdp",
+                    headers={
-                    "Content-Length": str(len(offer.sdp))
+                        "Content-Type": "application/sdp",
-                },
+                        "Content-Length": str(len(offer.sdp))
-                ssl=False
+                    },
-        ) as response:
+                    ssl=False
-            print("已接收到服务器的响应、开始处理 SDP Answer")
+            ) as response:
-            answer_sdp = await response.text()
+                if response.status == 200:
-            await pc.setRemoteDescription(RTCSessionDescription(sdp=answer_sdp, type='answer'))
+                    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'))
+                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，直到收到停止信号
@@ -87,64 +84,68 @@ async def rtc_frame_receiver(url, frame_queue, stop_event):
     except KeyboardInterrupt:
         print("用户中断")
     finally:
-        print("开始关闭 RTCPeerConnection")
+        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):
     """
-    从队列中读取cv2帧并处理（队列空时会阻塞等待）
+    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
-
-    Args:
-        ip: IP地址
-        frame_queue: 帧队列
-        stop_event: 用于控制任务停止的事件
     """
     # 创建OCR检测器实例
     ocr_detector = OCRViolationDetector(
-        forbidden_words_path=r"D:\Git\bin\video\ocr\forbidden_words.txt",  # 替换为实际路径
+        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
-        # 从队列中获取cv2帧（队列为空时会阻塞等待新帧）
+        try:
-        current_frame = await frame_queue.get()
+            # 阻塞等待队列中的帧
-        has_violation, words, confidences = ocr_detector.detect(current_frame)
+            current_frame = await frame_queue.get()
-        print(has_violation)
-        print( words)
-        print( 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(),
-            }
-            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
+            # 进行OCR检测
-            print("检测到违规内容，准备关闭AI检测")
+            has_violation, words, confidences = ocr_detector.detect(current_frame)
-            stop_event.set()
+            print(f"检测结果: {'有违规内容' if has_violation else '无违规内容'}")
-        else:
+            print(f"检测到的词: {words}")
-            print("测试结果：图片中未检测到违禁词")
+            print(f"置信度: {confidences}")
 
-        # 标记任务完成
+            # 输出所有检测到的违禁词
-        frame_queue.task_done()
+            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
     """
-    # 创建队列和停止事件
+    # 创建队列（大小为1）和停止事件
-    frame_queue = asyncio.Queue(maxsize=1)
+    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
@@ -153,14 +154,18 @@ def process_webrtc_stream(ip, webrtc_url):
         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))
 
-        # 等待任一任务完成（当stop_event被设置时，两个任务都会退出）
+        # 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
         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
         cv2.destroyAllWindows()