feat: 增加循跡回歸雙服務端

cfg_infer_server.toml

@@ -7,6 +7,7 @@ logger_format = "{time} {level} {message}"
 lane_infer_port = 6666
 yolo_infer_port = 6667
 ocr_infer_port = 6668
+lane_infer_port1 = 6669
 
 [camera]
 front_camera_port = 5555

lane_server/infer.py

@@ -2,7 +2,8 @@ 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"):
+    # def __init__(self, model_dir="./lane_model/7_12_6"):
+    def __init__(self, model_dir="./lane_model/6_9"):
         # 初始化 paddle 推理
         self.model_dir = model_dir
         self.config = paddle_infer.Config(model_dir + "/model.pdmodel", model_dir + "/model.pdiparams")
@@ -21,6 +22,9 @@ class Lane_model_infer:
         self.normalize_transform = T.Normalize(mean=[127.5], std=[127.5])
         # print(self.config.summary())
     def infer(self,src) -> np.ndarray:
+        # 7_12_3 [60:240,:]
+        # crop_src = src[60:240,:]
+        # image = self.normalize_transform(crop_src)
         image = self.normalize_transform(src)
         image = image.transpose(2, 0, 1)
         image = np.expand_dims(image, axis=0)

lane_server/lane_infer_server.py

@@ -16,8 +16,8 @@ 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
+    logger.info("lane server thread init success")
     
     context = zmq.Context()
     # 启动 server

lane_server/lane_infer_server1.py

@@ -0,0 +1,99 @@
+import toml
+import threading
+from loguru import logger
+import logging
+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
+def server_resp(lane_infer_port):
+    global response
+    global model_id
+    logger.info("lane server1 thread init success")
+    
+    context = zmq.Context()
+    # 启动 server
+    socket = context.socket(zmq.REP)
+    socket.bind(f"tcp://*:{lane_infer_port}")
+    logger.info("lane infer1 server init success")
+    while True:
+        message = socket.recv_string()
+        with lock:
+            socket.send_pyobj(response)
+
+
+def lane_infer1_server_main(queue):
+
+    # context2 = zmq.Context()
+    # socket_server = context2.socket(zmq.PUB)
+    # socket_server.setsockopt(zmq.SNDHWM,10)
+    # socket_server.bind("tcp://*:7778")
+
+    if queue != None:
+        class Handler(logging.Handler):
+            def emit(self, record):
+                log_entry = self.format(record)
+                queue.put({'level': record.levelname.lower(), 'content': log_entry})
+        # logger.remove()
+        handler = Handler()
+        logger.add(handler, format="{time:MM-DD HH:mm:ss} {message}", level="DEBUG")
+
+    cfg = toml.load('/home/evan/Workplace/project_infer/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")
+
+    # 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.REQ)
+    camera_socket.connect(f"tcp://localhost:{cfg['camera']['front_camera_port']}")
+    logger.info("connect camera success")
+
+    # 初始化 paddle 推理器
+    predictor = Lane_model_infer(model_dir="./lane_model/7_12_6")
+    logger.info("lane model load success")
+    # 启动 lane_infer_server 线程
+    mythread = threading.Thread(target=server_resp,
+                                args=(cfg['server']['lane_infer_port1'],),
+                                daemon=True)
+    
+    mythread.start()
+    import signal
+    import sys
+    def signal_handler(signum, frame):
+        logger.info("Received signal, exiting...")
+        camera_socket.close()
+        context.term()
+        sys.exit(0)
+
+    # 注册信号处理函数
+    signal.signal(signal.SIGTERM, signal_handler)
+    signal.signal(signal.SIGINT, signal_handler)
+
+
+    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.cvtColor(frame, cv2.COLOR_RGB2BGR)
+        frame = frame[60:240,:]
+        result = predictor.infer(frame)
+        with lock:
+            response['data'] = result
+        if cv2.waitKey(1) == 27:
+            break
+    mythread.join()
+    logger.info("lane infer1 server exit")
+
+if __name__ == "__main__":
+    lane_infer1_server_main(None)

lane_server/lane_model/6_9/说明.txt

@@ -0,0 +1,4 @@
+十字增强
+补充十字_备份原数据
+
+与初代相似 直角弯内切 十字正常 红色球后的弯压线

lane_server/lane_model/7_12_3/readme.txt

@@ -0,0 +1 @@
+crop_frame = frame[60:240,:]能用的

lane_server/lane_model/说明.txt

@@ -0,0 +1,8 @@
+根目录下的模型 最初版本 很久没调了
+2024-04-28-19-19-15
+
+
+6_9 在 2024-04-28-19-19-15 数据基础上补充了十字 mobilenet v3 small 全图 
+7_10_2 新标注的数据集  mobilenet v3 small 全图 
+7_12_3 使用和 6_9 相同的数据集 mobilenet v3 large 裁剪上面 60 行像素 [60:240,:]
+7_12_6 使用和 6_9 相同的数据集 mobilenet v3 small 裁剪上面 60 行像素 [60:240,:]

ocr_server/ocr_infer_server.py

@@ -5,6 +5,7 @@ import cv2
 import numpy as np
 import requests  
 import base64
+import datetime 
 
 
 
@@ -58,6 +59,7 @@ def ocr_api_request(image_base64):
 
 if __name__ == "__main__":
 
+    logger.info("ocr server 开始加载")
     cfg = toml.load('/home/evan/Workplace/project_infer/cfg_infer_server.toml')
 
     # 配置日志输出
@@ -68,11 +70,11 @@ if __name__ == "__main__":
     # camera_socket.connect(f"tcp://localhost:{cfg['camera']['camera2_port']}")
     # logger.info("connect camera success")
 
-    cap = cv2.VideoCapture(20)
-    cap.set(cv2.CAP_PROP_FOURCC, cv2.VideoWriter.fourcc('M','J','P','G'))
-    cap.set(cv2.CAP_PROP_FPS, 20)
-    cap.set(cv2.CAP_PROP_FRAME_WIDTH, 960)
-    cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 540)
+    # cap = cv2.VideoCapture(20)
+    # cap.set(cv2.CAP_PROP_FOURCC, cv2.VideoWriter.fourcc('M','J','P','G'))
+    # cap.set(cv2.CAP_PROP_FPS, 20)
+    # cap.set(cv2.CAP_PROP_FRAME_WIDTH, 960)
+    # cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 540)
 
     # 初始化 server
     context = zmq.Context()
@@ -83,7 +85,7 @@ if __name__ == "__main__":
     import signal
     import sys
     def signal_handler(signum, frame):
-        logger.info("Received signal, exiting...")
+        logger.info(f"接收到退出信号 {signum}, 退出中")
         socket.close()
         context.term()
         sys.exit(0)
@@ -92,15 +94,30 @@ if __name__ == "__main__":
     signal.signal(signal.SIGTERM, signal_handler)
     signal.signal(signal.SIGINT, signal_handler)
 
+    logger.info("ocr server 加载完成")
+
     while True:
         message1 = socket.recv_string()
-        logger.info("recv client request")
+        logger.info("收到客户端请求")
+
+        logger.info("构造摄像头")
+        cap = cv2.VideoCapture(20)
+        cap.set(cv2.CAP_PROP_FOURCC, cv2.VideoWriter.fourcc('M','J','P','G'))
+        cap.set(cv2.CAP_PROP_FPS, 20)
+        cap.set(cv2.CAP_PROP_FRAME_WIDTH, 960)
+        cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 540)
+
+        for _ in range(5):
             ret, frame = cap.read()
+            cv2.waitKey(1)
+
         if ret:
             frame = frame[:,0:480]
             frame = cv2.rotate(frame, cv2.ROTATE_90_COUNTERCLOCKWISE)
             
-            output_file_path = 'rotate.jpg'
+            now = datetime.datetime.now()  
+            timestamp = now.strftime("%Y%m%d_%H%M%S")  
+            output_file_path = f"./saved_picture/{timestamp}.jpg"  
             success = cv2.imwrite(output_file_path, frame)
             
             _, frame = cv2.imencode('.jpg', frame)
@@ -108,13 +125,19 @@ if __name__ == "__main__":
             encoded_image = base64.b64encode(frame).decode('utf-8')
             
             result = ocr_api_request(encoded_image)
-            print(result)
+            # print(result)
             if result != None:
                 socket.send_pyobj({'code': 0, 'content': result.get('words_result')})
+                logger.info(f"ocr 返回 {result.get('words_result')}")
             else:
                 socket.send_pyobj({'code': -1, 'content': " ocr 没找到文字"})
+                logger.error("ocr 没找到文字")
         else:
             socket.send_pyobj({'code': -1, 'content': "ocr 摄像头读取出错"})
+            logger.critical("ocr 摄像头读取出错")
+
+        cap.release()
+        
         if cv2.waitKey(1) == 27:
             break
     logger.info("ocr infer server exit")

yolo_server/readme.txt

@@ -0,0 +1 @@
+上次使用模型 0622