diff --git a/asset/saved_video/ground_station_record.mp4 b/asset/saved_video/ground_station_record.mp4 new file mode 100644 index 0000000..f0cd945 Binary files /dev/null and b/asset/saved_video/ground_station_record.mp4 differ diff --git a/config.json b/config.json index 6724c8d..d8e8174 100644 --- a/config.json +++ b/config.json @@ -5,7 +5,7 @@ "device_id": 0 }, "video": { - "video_source": 0, + "video_source": "rtsp://192.168.144.25:8554/main.264", "jpeg_quality": 75 }, "network": { diff --git a/infer_camera_modular.py b/infer_camera_modular.py index 4ba0758..101a6d2 100644 --- a/infer_camera_modular.py +++ b/infer_camera_modular.py @@ -15,7 +15,7 @@ from drone_controller.pid_counter import PID # =================================================== class VideoStreaming: - """ 📡 视频流采集与后台图传模块 """ + """ 📡 视频流采集与后台图传模块（支持 RTSP 自动重连） """ def __init__(self, video_cfg, net_cfg): self.video_source = video_cfg.get("video_source", 0) @@ -23,32 +23,108 @@ class VideoStreaming: self.gs_ip = net_cfg.get("ground_station_ip", "127.0.0.1") self.udp_port = net_cfg.get("udp_port", 9999) - self.cap = cv2.VideoCapture(self.video_source) - self.tx_queue = queue.Queue(maxsize=2) # 限制队列，防积压 + # RTSP 特殊参数 + self.is_rtsp = isinstance(self.video_source, str) and self.video_source.startswith("rtsp://") + self.cap = None + self.frame_buffer = queue.Queue(maxsize=1) # 只保留最新一帧 self.is_running = True + self.capture_thread = None - if not self.cap.isOpened(): - raise RuntimeError(f"❌ 无法打开视频源: {self.video_source}") + # 启动后台采集线程 + self._start_capture_thread() - # 启动后台图传线程 + # 图传发送队列与线程（原样保留） + self.tx_queue = queue.Queue(maxsize=2) self.sender_thread = threading.Thread(target=self._udp_stream_sender_worker, daemon=True) self.sender_thread.start() + def _start_capture_thread(self): + """ 独立线程负责从摄像头/RTSP 读取帧，避免主循环阻塞 """ + self.capture_thread = threading.Thread(target=self._capture_worker, daemon=True) + self.capture_thread.start() + + def _capture_worker(self): + """ 后台不断读取帧，存入 frame_buffer """ + while self.is_running: + # 如果摄像头未打开或已断开，尝试连接 + if self.cap is None or not self.cap.isOpened(): + self._open_camera() + if self.cap is None or not self.cap.isOpened(): + time.sleep(1) # 等待重连 + continue + + ret, frame = self.cap.read() + if not ret: + # 读取失败，关闭并标记需重连 + print("⚠️ RTSP 读取失败，准备重连...") + self.cap.release() + self.cap = None + continue + + # 清空旧帧，只保留最新一帧 + while not self.frame_buffer.empty(): + try: + self.frame_buffer.get_nowait() + except queue.Empty: + break + self.frame_buffer.put(frame) + + if self.cap is not None: + self.cap.release() + + def _open_camera(self): + """ 打开摄像头或 RTSP 流，并设置低延迟参数 """ + try: + print(f"📷 正在连接视频源: {self.video_source}") + self.cap = cv2.VideoCapture(self.video_source) + + if self.is_rtsp: + # 设置 RTSP 缓冲区大小（只保留 1 帧，降低延迟） + self.cap.set(cv2.CAP_PROP_BUFFERSIZE, 1) + # 设置读取超时（OpenCV 没有直接超时参数，但可尝试设置后端属性） + # 某些平台支持以下设置： + self.cap.set(cv2.CAP_PROP_FOURCC, cv2.VideoWriter_fourcc('H', '2', '6', '4')) + # 强制使用 tcp 协议（某些 rtsp 默认 udp 会丢包严重） + # 如果 rtsp 地址支持，可以改成 "rtsp://...?tcp" + if "?" not in self.video_source: + self.video_source += "?tcp" + # 注意：有些相机需要重新初始化，这里简单打印提示 + print("💡 建议使用 TCP 传输: 在 RTSP URL 后添加 ?tcp") + else: + # USB 摄像头也可设置缓冲区 + self.cap.set(cv2.CAP_PROP_BUFFERSIZE, 1) + + # 可选：强制指定分辨率（根据你的相机调整） + # self.cap.set(cv2.CAP_PROP_FRAME_WIDTH, 640) + # self.cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 480) + + if self.cap.isOpened(): + print("✅ 视频源连接成功") + else: + print("❌ 视频源打开失败") + except Exception as e: + print(f"❌ 打开视频源异常: {e}") + self.cap = None + def read_frame(self): - """ 读取一帧原始图像 """ - return self.cap.read() + """ 主循环调用：从缓冲区获取最新一帧（非阻塞） """ + try: + frame = self.frame_buffer.get_nowait() + return True, frame + except queue.Empty: + # 没有新帧时返回 False，主循环可根据需要 sleep + return False, None def push_to_stream(self, frame): - """ 非阻塞式推入图传队列 """ + """ 原图传推流逻辑保持不变 """ try: - # 推送前轻量化分辨率，降低带宽压力 send_frame = cv2.resize(frame, (640, 480)) self.tx_queue.put_nowait(send_frame) except queue.Full: - pass # 队列满则直接丢帧 + pass def _udp_stream_sender_worker(self): - """ 后台图传专用工作线程 """ + """ 原图传发送线程（未改动） """ sock = socket.socket(socket.AF_INET, socket.SOCK_DGRAM) server_address = (self.gs_ip, self.udp_port) print(f"📡 图传后台线程已启动，目标地面站 -> {self.gs_ip}:{self.udp_port}") @@ -58,30 +134,29 @@ class VideoStreaming: frame_to_send = self.tx_queue.get(timeout=1.0) if frame_to_send is None: break - - result, img_encode = cv2.imencode('.jpg', frame_to_send, [cv2.IMWRITE_JPEG_QUALITY, self.jpeg_quality]) + result, img_encode = cv2.imencode('.jpg', frame_to_send, + [cv2.IMWRITE_JPEG_QUALITY, self.jpeg_quality]) if not result: continue - data = img_encode.tobytes() - if len(data) > 65000: # 严格防丢包限制 + if len(data) > 65000: continue - sock.sendto(data, server_address) except queue.Empty: continue except Exception as e: print(f"❌ 图传线程异常: {e}") time.sleep(0.1) - sock.close() def release(self): """ 释放资源 """ self.is_running = False + if self.capture_thread is not None: + self.capture_thread.join(timeout=2.0) + if self.cap is not None: + self.cap.release() self.tx_queue.put(None) - self.cap.release() - class YOLO26UAVInfer: """ 🚀 昇腾 NPU 推理与图像后处理模块 """ diff --git a/infer_video_direct.py b/infer_video_direct.py index 90e6006..a6912d0 100644 --- a/infer_video_direct.py +++ b/infer_video_direct.py @@ -11,7 +11,7 @@ from ais_bench.infer.interface import InferSession MODEL_PATH = "./om/yolo26n-balloon.om" # YOLO26 模型路径 INPUT_VIDEO = "./asset/test_video.mp4" # 输入的测试视频 RTSP_URL = "rtsp://192.168.144.25:8554/main.264" -CONF_THRESHOLD = 0.25 # 置信度阈值 +CONF_THRESHOLD = 0.50 # 置信度阈值 # -------------- 无线图传网络配置 -------------- GROUND_STATION_IP = "192.168.31.239" # 地面站的局域网 IP