5.24

lane_server/lane_infer_server.py

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+import toml
+import threading
+from loguru import logger
+import zmq
+from infer import Lane_model_infer
+import numpy as np
+
+lock = threading.Lock()
+response = {'code': 0, 'data': 0}
+
+# 处理server响应数据
+def server_resp(lane_infer_port):
+    logger.info("lane server thread init success")
+    global response
+    
+    context = zmq.Context()
+    # 启动server
+    socket = context.socket(zmq.REP)
+    socket.bind(f"tcp://*:{lane_infer_port}")
+    logger.info("lane infer server init success")
+    while True:
+        message = socket.recv_string()
+        with lock:
+            socket.send_pyobj(response)
+
+
+
+if __name__ == "__main__":
+
+    cfg = toml.load('../cfg_infer_server.toml')
+
+    # 配置日志输出
+    logger.add(cfg['debug']['logger_filename'], format=cfg['debug']['logger_format'], retention = 5, level="INFO")
+    camera_cfg = cfg['camera']
+
+    # 连接摄像头server 巡线只需要连接前摄像头
+    context = zmq.Context()
+    camera_socket = context.socket(zmq.SUB)
+    camera_socket.connect(f"tcp://*:{camera_cfg['front_camera_port']}")
+    camera_socket.setsockopt(zmq.SUBSCRIBE, '')
+    logger.info("connect camera success")
+    # 初始化paddle推理器
+    predictor = Lane_model_infer()
+    logger.info("lane model load success")
+    # 启动lane_infer_server线程
+    mythread = threading.Thread(target=server_resp,
+                                args=(camera_cfg['lane_infer_port'],),
+                                daemon=True)
+    mythread.start()
+
+    while True:
+        image_data_bytes = camera_socket.recv(320*240)
+        image = np.frombuffer(image_data_bytes, dtype=np.uint8).reshape((240, 320, 3))
+        result = predictor.infer(image)
+        with lock:
+            response['data'] = result
+    mythread.join()
+    logger.info("lane infer server exit")
+