项目备份

2026-04-09 10:37:51 +08:00
parent 7ed8d2dcb4
commit 4eab443148
32 changed files with 9468 additions and 0 deletions
--- a/module/aiortc_parse.py
+++ b/module/aiortc_parse.py
@@ -0,0 +1,287 @@
+
+import asyncio
+import json
+import threading
+import cv2
+import numpy as np
+import win32gui
+import win32ui
+import win32con
+import win32api
+
+import aiortc
+from aiortc import MediaStreamTrack, RTCPeerConnection, RTCSessionDescription
+from aiortc.contrib.media import MediaBlackhole, MediaPlayer, MediaRecorder
+from aiortc.sdp import SessionDescription
+import webview
+
+# -------------------------- 2. 兼容VideoFrame导入 --------------------------
+try:from aiortc.contrib.media import VideoFrame,AudioFrame
+except ImportError:from aiortc import VideoFrame,AudioFrame
+
+
+# -------------------------- 1. Windows 11高DPI适配 --------------------------
+ctypes.windll.shcore.SetProcessDpiAwareness(2)  # 解决高分屏采集偏移问题
+
+# -------------------------- 2. 兼容VideoFrame导入 --------------------------
+try:from aiortc.contrib.media import VideoFrame,AudioFrame
+except ImportError:from aiortc import VideoFrame,AudioFrame
+
+# -------------------------- 2. 屏幕视频采集轨道 --------------------------
+class ScreenVideoTrack(MediaStreamTrack):
+    kind = "video"
+    def __init__(self, fps=30, scale_factor=1.0):
+        super().__init__()
+        self.fps = fps
+        self.scale_factor = scale_factor
+        self.stop_flag = False
+        self.pts = 0
+        self.frame_interval = 1.0 / fps
+
+        # 获取真实屏幕分辨率（适配高DPI）
+        self.user32 = ctypes.windll.user32
+        self.screen_width = self.user32.GetSystemMetrics(0)
+        self.screen_height = self.user32.GetSystemMetrics(1)
+
+    def capture_screen(self):
+        """Windows 11原生API采集屏幕（低延迟）"""
+        left, top, width, height = 0, 0, self.screen_width, self.screen_height
+
+        # 1. 创建设备上下文（DC）
+        hdesktop = win32gui.GetDesktopWindow()
+        hwnd_dc = win32gui.GetWindowDC(hdesktop)
+        mfc_dc = win32ui.CreateDCFromHandle(hwnd_dc)
+        save_dc = mfc_dc.CreateCompatibleDC()
+
+        # 2. 复制屏幕内容到位图
+        save_bitmap = win32ui.CreateBitmap()
+        save_bitmap.CreateCompatibleBitmap(mfc_dc, width, height)
+        save_dc.SelectObject(save_bitmap)
+        save_dc.BitBlt((0, 0), (width, height), mfc_dc, (left, top), win32con.SRCCOPY)
+
+        # 3. 转换为numpy数组（BGR格式）
+        bmp_data = save_bitmap.GetBitmapBits(True)
+        frame = np.frombuffer(bmp_data, dtype=np.uint8).reshape((height, width, 4))
+        frame = frame[:, :, :3]  # 去掉Alpha通道
+        frame = frame[:, :, ::-1]  # BGRA → BGR（适配aiortc）
+
+        # 4. 缩放（可选，降低文件大小）
+        if self.scale_factor != 1.0:
+            new_width = int(width * self.scale_factor)
+            new_height = int(height * self.scale_factor)
+            frame = cv2.resize(frame, (new_width, new_height), interpolation=cv2.INTER_AREA)
+
+        # 5. 释放资源（避免内存泄漏）
+        win32gui.DeleteObject(save_bitmap.GetHandle())
+        save_dc.DeleteDC()
+        mfc_dc.DeleteDC()
+        win32gui.ReleaseDC(hdesktop, hwnd_dc)
+
+        return frame
+
+    async def recv(self):
+        """aiortc核心方法：持续返回视频帧"""
+        if self.stop_flag:
+            raise StopAsyncIteration
+        # 控制帧率
+        await asyncio.sleep(self.frame_interval)  
+        # 获取windows11 原始的视频帧
+        frame_data = self.capture_screen()
+
+        # 转换为aiortc VideoFrame
+        video_frame = self._convert_to_video_frame(frame_data)
+
+        video_frame.pts = int(self.pts)
+        video_frame.time_base = np.array([1, self.fps])
+        self.pts += 1
+
+        return video_frame
+
+    def _convert_to_video_frame(self, img):
+        """将numpy数组转换为aiortc的VideoFrame"""  
+        return VideoFrame.from_ndarray(img, format="bgr24")
+
+    def stop(self):
+        """停止屏幕采集"""
+        self.stop_flag = True
+
+# -------------------------- 3. 系统音频采集轨道 --------------------------
+class SystemAudioTrack(MediaStreamTrack):
+    kind = "audio"
+
+    def __init__(self, sample_rate=48000, channels=2):
+        super().__init__()
+        self.sample_rate = sample_rate
+        self.channels = channels
+        self.stop_flag = False
+        self.pts = 0
+        self.audio_queue = asyncio.Queue(maxsize=10)  # 音频数据队列
+
+        # 启动麦克风/系统音频采集（这里默认采集麦克风，系统音频见备注）
+        self._start_audio_capture()
+
+    def _start_audio_capture(self):
+        """启动音频采集（麦克风）"""
+        def audio_callback(indata, frames, time, status):
+            if status or self.stop_flag:
+                return
+            # 将音频数据转为float32格式（aiortc要求）
+            audio_data = indata.astype(np.float32)
+            self.audio_queue.put_nowait(audio_data)
+
+        # 打开音频输入流
+        self.audio_stream = sd.InputStream(
+            samplerate=self.sample_rate,
+            channels=self.channels,
+            callback=audio_callback,
+            blocksize=1024
+        )
+        self.audio_stream.start()
+
+    async def recv(self):
+        """aiortc核心方法：持续返回音频帧"""
+        if self.stop_flag and self.audio_queue.empty():
+            raise StopAsyncIteration
+
+        # 从队列获取音频数据
+        audio_data = await self.audio_queue.get()
+        sample_count = len(audio_data)
+
+        # 转换为aiortc AudioFrame
+        audio_frame = AudioFrame(
+            samples=audio_data.T,  # 转置为 (channels, samples)
+            sample_rate=self.sample_rate,
+            channels=self.channels
+        )
+        audio_frame.pts = int(self.pts)
+        audio_frame.time_base = np.array([1, self.sample_rate])
+        self.pts += sample_count
+
+        return audio_frame
+
+    def stop(self):
+        """停止音频采集"""
+        self.stop_flag = True
+        self.audio_stream.stop()
+        self.audio_stream.close()
+
+ 
+class WebRTCService:
+    def __init__(self):
+        super().__init__()
+        self.peer=None
+        self.channel = None
+        self.screen_track = None
+        self.loop = asyncio.new_event_loop()
+        self.thread = None
+    
+    def start_async_loop(self):
+        """在子线程运行asyncio循环"""
+        asyncio.set_event_loop(self.loop)
+        self.loop.run_forever()
+    
+    # 1. 初始化 RTCPeerConnection
+    async def init_connection(self):
+        # 初始化 RTCPeerConnection
+        if self.peer :self.peer =None
+        # 创建 RTCPeerConnection 实例
+        self.peer = RTCPeerConnection()
+        
+        # 添加事件监听器
+        @self.peer.on("connectionstatechange")
+        async def on_connectionstatechange():
+            print(f"连接状态: {self.peer.connectionState}")
+    
+    async def recv(self):
+        """捕获屏幕帧并转换为 aiortc 可处理的 VideoFrame"""
+        if not self.running:
+            raise RuntimeError("Track stopped")
+
+        # 1. 捕获屏幕（返回 numpy 数组）
+        img = np.array(self.sct.grab(self.monitor))
+        # 2. 转换格式：mss 捕获的是 BGRA，转为 BGR（OpenCV 格式）
+        img = cv2.cvtColor(img, cv2.COLOR_BGRA2BGR)
+        # 3. 转换为 VideoFrame（aiortc 要求的格式）
+        frame = VideoFrame.from_ndarray(img, format="bgr24")
+        
+        # 调整时间戳（保证流的时序）
+        frame.pts = self.pts
+        frame.time_base = self.time_base
+        self.pts += 1
+        
+        return frame
+
+    # 2. 获取用户媒体
+    async def setup_media(self):
+        # 使用摄像头和麦克风
+        # player = MediaPlayer('/dev/video0')  # Linux 摄像头
+        # 或者使用文件
+        media_flag = True
+        if media_flag:
+            player = MediaPlayer('screen_60fps.mp4')
+            return player.audio, player.video
+        else:
+            player_video = ScreenVideoTrack(fps=30)
+            player_audio = SystemAudioTrack()
+            return player_audio, player_video
+    
+    # 3. 创建 Offer
+    async def create_offer(self):
+        # 添加音视频轨道
+        audio_track, video_track = await self.setup_media()
+        
+        if audio_track:
+            self.peer.addTrack(audio_track)
+        if video_track:
+            self.peer.addTrack(video_track)
+        
+        # 创建 offer
+        offer = await self.peer.createOffer()
+        await self.peer.setLocalDescription(offer)
+        
+        return offer
+    
+    # 3. 创建 接收 offer 并创建 Answer
+    async def handle_remote_offer(self, offer_sdp):
+        # 设置远程描述
+        offer = RTCSessionDescription(sdp=offer_sdp, type="offer")
+        await self.peer.setRemoteDescription(offer)
+        
+        # 创建 answer
+        answer = await self.peer.createAnswer()
+        await self.peer.setLocalDescription(answer)
+        return answer
+
+    async def handle_remote_answer(self,answer_sdp):
+        await self.peer.setRemoteDescription(obj)
+        
+        # 监听ICE候选，发送到信令服务器
+        @self.peer.on("icecandidate")
+        async def on_icecandidate(candidate):
+            if candidate:
+                # await signaling.send(candidate)
+                pass
+
+    # 4. 数据通道使用
+    async def setup_data_channel(self,pc):
+        # 初始化 数据通道
+        if self.channel : self.channel = None
+        # 创建数据通道
+        self.channel = self.peer.createDataChannel("chat")
+        
+        @self.channel.on("open")
+        def on_open():
+            print("数据通道已打开")
+            # 发送消息
+            self.channel.send("Hello from aiortc!")
+        
+        @self.channel.on("message")
+        def on_message(message):
+            print(f"收到消息: {message}")
+        
+        return self.channel
+    
+if __name__ == "__main__":
+    rtc=rtc()
+    rtc.setup_media()
+    pass