mirror of
https://github.com/NanjingForestryUniversity/supermachine--tomato-passion_fruit.git
synced 2025-11-09 14:54:07 +00:00
167 lines
6.6 KiB
Python
167 lines
6.6 KiB
Python
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import numpy as np
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import socket
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import logging
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import matplotlib.pyplot as plt
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import cv2
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def rec_socket(recv_sock: socket.socket, cmd_type: str, ack: bool) -> bool:
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if ack:
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cmd = 'A' + cmd_type
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else:
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cmd = 'D' + cmd_type
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while True:
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try:
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temp = recv_sock.recv(1)
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except ConnectionError as e:
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logging.error(f'连接出错, 错误代码:\n{e}')
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return False
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except TimeoutError as e:
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logging.error(f'超时了，错误代码: \n{e}')
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return False
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except Exception as e:
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logging.error(f'遇见未知错误，错误代码: \n{e}')
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return False
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if temp == b'\xaa':
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break
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# 获取报文长度
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temp = b''
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while len(temp) < 4:
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try:
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temp += recv_sock.recv(1)
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except Exception as e:
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logging.error(f'接收报文长度失败, 错误代码: \n{e}')
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return False
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try:
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data_len = int.from_bytes(temp, byteorder='big')
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except Exception as e:
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logging.error(f'转换失败,错误代码 \n{e}, \n报文内容\n{temp}')
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return False
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# 读取报文内容
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temp = b''
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while len(temp) < data_len:
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try:
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temp += recv_sock.recv(data_len)
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except Exception as e:
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logging.error(f'接收报文内容失败, 错误代码: \n{e}，\n报文内容\n{temp}')
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return False
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data = temp
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if cmd.strip().upper() != data[:4].decode('ascii').strip().upper():
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logging.error(f'客户端接收指令错误,\n指令内容\n{data}')
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return False
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else:
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if cmd == 'DIM':
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print(data)
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# 进行数据校验
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temp = b''
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while len(temp) < 3:
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try:
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temp += recv_sock.recv(1)
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except Exception as e:
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logging.error(f'接收报文校验失败, 错误代码: \n{e}')
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return False
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if temp == b'\xff\xff\xbb':
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return True
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else:
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logging.error(f"接收了一个完美的只错了校验位的报文，\n data: {data}")
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return False
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# def main():
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# socket_receive = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
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# socket_receive.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
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# socket_receive.bind(('127.0.0.1', 21123))
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# socket_receive.listen(5)
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# socket_send = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
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# socket_send.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
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# socket_send.bind(('127.0.0.1', 21122))
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# socket_send.listen(5)
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# print('等待连接')
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# socket_send_1, receive_addr_1 = socket_send.accept()
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# print("连接成功：", receive_addr_1)
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# # socket_send_2 = socket_send_1
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# socket_send_2, receive_addr_2 = socket_receive.accept()
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# print("连接成功：", receive_addr_2)
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# while True:
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# cmd = input('请输入指令：').strip().upper()
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# if cmd == 'IM':
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# with open('data/newrawfile_ref.raw', 'rb') as f:
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# data = np.frombuffer(f.read(), dtype=np.float32).reshape(750, 288, 384)
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# data = data[:, [91, 92, 93, 94, 95, 96, 97, 98, 99, 100], :]
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# n_rows, n_bands, n_cols = data.shape[0], data.shape[1], data.shape[2]
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# print(f'n_rows：{n_rows}, n_bands：{n_bands}, n_cols：{n_cols}')
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# n_rows, n_cols, n_bands = [x.to_bytes(2, byteorder='big') for x in [n_rows, n_cols, n_bands]]
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# data = data.tobytes()
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# length = len(data) + 10
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# print(f'length: {length}')
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# length = length.to_bytes(4, byteorder='big')
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# msg = b'\xaa' + length + (' ' + cmd).upper().encode('ascii') + n_rows + n_cols + n_bands + data + b'\xff\xff\xbb'
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# socket_send_1.send(msg)
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# print('发送成功')
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# result = socket_send_2.recv(5)
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# length = int.from_bytes(result[1:5], byteorder='big')
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# result = b''
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# while len(result) < length:
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# result += socket_send_2.recv(length)
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# print(result)
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# data = result[4:length].decode()
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# print(data)
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def main():
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socket_receive = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
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socket_receive.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
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socket_receive.bind(('127.0.0.1', 21123))
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socket_receive.listen(5)
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socket_send = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
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socket_send.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
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socket_send.bind(('127.0.0.1', 21122))
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socket_send.listen(5)
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print('等待连接')
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socket_send_1, receive_addr_1 = socket_send.accept()
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print("连接成功：", receive_addr_1)
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# socket_send_2 = socket_send_1
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socket_send_2, receive_addr_2 = socket_receive.accept()
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print("连接成功：", receive_addr_2)
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while True:
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cmd = input().strip().upper()
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if cmd == 'IM':
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image_paths = [
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r"D:\project\deep-learning-for-image-processing-master\data_set\test_image\1.jpg",
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r"D:\project\deep-learning-for-image-processing-master\data_set\test_image\2.jpg",
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r"D:\project\deep-learning-for-image-processing-master\data_set\test_image\3.jpg",
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r"D:\project\deep-learning-for-image-processing-master\data_set\test_image\4.jpg",
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r"D:\project\deep-learning-for-image-processing-master\data_set\test_image\5.jpg",
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]
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# 连续发送五张图片
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for image_path in image_paths:
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# 读取图片文件
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img = cv2.imread(image_path)
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# img = cv2.imread(r"/Users/zhouchao/Library/CloudStorage/OneDrive-macrosolid/PycharmProjects/wood_color/data/data20220919/dark/rgb60.png")
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# img = cv2.imread(r"D:\project\Astragalin\data\02newrawfile_ref.png")
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img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
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img = np.asarray(img, dtype=np.uint8)
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width = img.shape[0]
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height = img.shape[1]
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print(width, height)
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img_bytes = img.tobytes()
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length = len(img_bytes) + 8
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print(length)
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length = length.to_bytes(4, byteorder='big')
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width = width.to_bytes(2, byteorder='big')
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height = height.to_bytes(2, byteorder='big')
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send_message = b'\xaa' + length + (' ' + cmd).upper().encode('ascii') + width + height + img_bytes + b'\xff\xff\xbb'
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socket_send_1.send(send_message)
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print('发送成功')
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result = socket_send_2.recv(10)
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print(result)
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if __name__ == '__main__':
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main() |