# 导入 socket、sys 模块
import socket
import numpy as np
import cv2
import time


def read_and_process_txt(file_path):
    processed_data = []
    with open(file_path, "r") as file:
        for line in file:
            # 去除每行末尾的换行符
            line = line.strip()
            # 按空格分割每行
            items = line.split()
            # 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
            # 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
            processed_data.append(items)

    # 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
    # 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
    # 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
    json_data = {items[0]: items[1] for items in processed_data}
    try:
        return json_data
    except TypeError as e:
        print(f"Error converting to JSON: {e}")


baseConfig = read_and_process_txt("./base.txt")
print(baseConfig)
# 创建 socket 对象
socketlocal = socket.socket(socket.AF_INET, socket.SOCK_STREAM)

# 设置本地主机名
host = "127.0.0.1"
# 设置端口号
port = int(baseConfig["udpPngPort1"])

# 1.创建一个udp套接字
udp_socket = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
local_addr = (host, port)
udp_socket.bind(local_addr)

prev_frame_time = 0
new_frame_time = 0
count = 0
countTotal = 0
while True:
    # 接收数据:
    data = udp_socket.recv(1219112 * 2)
    # print("recv data",data)
    # 解码

    nparr = np.frombuffer(data, np.uint8)
    # 解码成图片numpy
    img_decode = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
    # 帧率计算
    new_frame_time = time.time()
    if new_frame_time - prev_frame_time < 1:
        count += 1
    else:
        countTotal = count
        count = 0
        prev_frame_time = new_frame_time
    if count != 0:
        countTotal = max([countTotal, count])
    cv2.putText(
        img_decode,
        "FPS:{}".format(countTotal),
        (30, 45),
        cv2.FONT_HERSHEY_SIMPLEX,
        0.5,
        (0, 0, 255),
        1,
    )
    if img_decode is not None and img_decode.shape[0] > 0 and img_decode.shape[1] > 0:
        cv2.imshow("result1", img_decode)
    if cv2.waitKey(1) & 0xFF == ord("q"):
        break