initial commit

lane_server/infer.py

@@ -1,20 +1,25 @@
 import paddle.inference as paddle_infer
 import numpy as np
 import paddle.vision.transforms as T
-
 class Lane_model_infer:
     def __init__(self, model_dir="./lane_model"):
-        # 初始化paddle推理
+        # 初始化 paddle 推理
         self.model_dir = model_dir
         self.config = paddle_infer.Config(model_dir + "/model.pdmodel", model_dir + "/model.pdiparams")
+        self.config.disable_glog_info()
         self.config.enable_use_gpu(200, 0)
+        # self.config.enable_memory_optim(True)
+        # self.config.switch_ir_optim(True)
+        # self.config.switch_use_feed_fetch_ops(False)
+        # self.config.delete_pass("conv_elementwise_add_act_fuse_pass")
+        # self.config.delete_pass("conv_elementwise_add_fuse_pass")
         self.predictor = paddle_infer.create_predictor(self.config)
         self.input_names = self.predictor.get_input_names()
         self.input_handle = self.predictor.get_input_handle(self.input_names[0])
         self.output_names = self.predictor.get_output_names()
         self.output_handle = self.predictor.get_output_handle(self.output_names[0])
         self.normalize_transform = T.Normalize(mean=[127.5], std=[127.5])
-    
+        # print(self.config.summary())
     def infer(self,src) -> np.ndarray:
         image = self.normalize_transform(src)
         image = image.transpose(2, 0, 1)
@@ -22,4 +27,11 @@ class Lane_model_infer:
         self.input_handle.copy_from_cpu(image)
         self.predictor.run()
         results = self.output_handle.copy_to_cpu()[0]
-        return results
+        return results
+
+# if __name__ == "__main__":
+#     predictor = Lane_model_infer()
+#     import time
+#     while True:
+#         time.sleep(1)
+#         print('123')

lane_server/lane_infer_server.py

@@ -5,16 +5,22 @@ import zmq
 from infer import Lane_model_infer
 import numpy as np
 import cv2
+
 lock = threading.Lock()
 response = {'code': 0, 'data': 0}
 
-# 处理server响应数据
+
+# context2 = zmq.Context()
+# socket_server = context2.socket(zmq.PUB)
+# socket_server.bind("tcp://*:7778")
+
+# 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
+    # 启动 server
     socket = context.socket(zmq.REP)
     socket.bind(f"tcp://*:{lane_infer_port}")
     logger.info("lane infer server init success")
@@ -23,8 +29,6 @@ def server_resp(lane_infer_port):
         with lock:
             socket.send_pyobj(response)
 
-
-
 if __name__ == "__main__":
 
     cfg = toml.load('../cfg_infer_server.toml')
@@ -32,29 +36,36 @@ if __name__ == "__main__":
     # 配置日志输出
     logger.add(cfg['debug']['logger_filename'], format=cfg['debug']['logger_format'], retention = 5, level="INFO")
 
-    # 连接摄像头server 巡线只需要连接前摄像头
+    # 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 = context.socket(zmq.REQ)
     camera_socket.connect(f"tcp://localhost:{cfg['camera']['front_camera_port']}")
-    camera_socket.setsockopt_string(zmq.SUBSCRIBE, "")
     logger.info("connect camera success")
-    # 初始化paddle推理器
+
+    # 初始化 paddle 推理器
     predictor = Lane_model_infer()
     logger.info("lane model load success")
-    # 启动lane_infer_server线程
+    # 启动 lane_infer_server 线程
     mythread = threading.Thread(target=server_resp,
                                 args=(cfg['server']['lane_infer_port'],),
                                 daemon=True)
+    
     mythread.start()
 
     while True:
+        camera_socket.send_string("")
         message = camera_socket.recv()
         np_array = np.frombuffer(message, dtype=np.uint8)
         frame = cv2.imdecode(np_array, cv2.IMREAD_COLOR)
-        frame = cv2.resize(frame,(320,240))
+        frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
         result = predictor.infer(frame)
         with lock:
             response['data'] = result
+        # print(result)
+        # cv2.circle(frame,(int(result[0]),int(result[1])),5,(0,255,0),-1)
+        # socket_server.send_pyobj(frame)
+        if cv2.waitKey(1) == 27:
+            break
     mythread.join()
     logger.info("lane infer server exit")
 

lane_server/test_camera_recv.py

@@ -5,7 +5,7 @@ import cv2
 
 context = zmq.Context()
 socket = context.socket(zmq.SUB)
-socket.connect("tcp://localhost:5555")
+socket.connect("tcp://localhost:5556")
 socket.setsockopt_string(zmq.SUBSCRIBE, '')
 
 while True: