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80 lines
2.3 KiB
80 lines
2.3 KiB
# 导入 socket、sys 模块
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import socket
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import numpy as np
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import cv2
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import time
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def read_and_process_txt(file_path):
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processed_data = []
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with open(file_path, "r") as file:
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for line in file:
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# 去除每行末尾的换行符
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line = line.strip()
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# 按空格分割每行
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items = line.split()
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# 这里简单地将分割后的数据作为一个列表加入到结果列表中
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# 实际应用中，你可能需要根据具体数据结构进行更复杂的处理
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processed_data.append(items)
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# 如果你确实需要将这些数据转换为JSON，可能需要构造一个合适的结构
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# 例如，如果你的文本文件每行代表一个对象的属性，你可能需要构建字典
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# 下面是一个假设的例子，将每行转换为字典并尝试转为JSON字符串
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json_data = {items[0]: items[1] for items in processed_data}
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try:
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return json_data
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except TypeError as e:
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print(f"Error converting to JSON: {e}")
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baseConfig = read_and_process_txt("./base.txt")
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print(baseConfig)
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# 创建 socket 对象
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socketlocal = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
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# 设置本地主机名
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host = "127.0.0.1"
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# 设置端口号
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port = int(baseConfig["udpPngPort1"])
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# 1.创建一个udp套接字
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udp_socket = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
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local_addr = (host, port)
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udp_socket.bind(local_addr)
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prev_frame_time = 0
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new_frame_time = 0
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count = 0
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countTotal = 0
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while True:
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# 接收数据:
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data = udp_socket.recv(1219112 * 2)
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# print("recv data",data)
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# 解码
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nparr = np.frombuffer(data, np.uint8)
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# 解码成图片numpy
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img_decode = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
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# 帧率计算
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new_frame_time = time.time()
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if new_frame_time - prev_frame_time < 1:
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count += 1
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else:
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countTotal = count
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count = 0
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prev_frame_time = new_frame_time
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if count != 0:
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countTotal = max([countTotal, count])
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cv2.putText(
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img_decode,
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"FPS:{}".format(countTotal),
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(30, 45),
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cv2.FONT_HERSHEY_SIMPLEX,
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0.5,
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(0, 0, 255),
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1,
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)
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if img_decode is not None and img_decode.shape[0] > 0 and img_decode.shape[1] > 0:
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cv2.imshow("result1", img_decode)
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if cv2.waitKey(1) & 0xFF == ord("q"):
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break
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