From a24f40a3bd5c0a68569d97578f50cf4d5622ca89 Mon Sep 17 00:00:00 2001
From: wrz1-zzzzz <914921336@qq.com>
Date: Thu, 12 Dec 2024 16:25:38 +0800
Subject: [PATCH] Create test.py
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
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添加图像
---
 socket/test.py | 104 +++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 104 insertions(+)
 create mode 100644 socket/test.py

diff --git a/socket/test.py b/socket/test.py
new file mode 100644
index 0000000..8cde648
--- /dev/null
+++ b/socket/test.py
@@ -0,0 +1,104 @@
+import socket
+import time
+
+import cv2
+import numpy as np
+#
+class VirtualValve:
+    def __init__(self, host, port, column_num=64):
+        self.client = socket.socket(socket.AF_INET, socket.SOCK_STREAM)  # 声明socket类型，同时生成链接对象
+        self.client.connect((host, port))  # 建立一个链接，连接到本地的13452端口
+        self.column_num = column_num
+
+    @staticmethod
+    def decode_data_to_matrix(data, column_num):
+        """
+        将接收到的数据解码为矩阵形式
+        :param data: 原始字节数据
+        :param column_num: 列数，用于解码为矩阵
+        :return: 解码后的矩阵
+        """
+        try:
+            # 假设数据中包含字节打包的矩阵
+            unpacked_data = np.frombuffer(data, dtype=np.uint8)  # 转换为无符号8位整型数组
+            unpacked_bits = np.unpackbits(unpacked_data)  # 将字节解压为位数组
+
+            # 计算行数（确保数据长度是列数的倍数）
+            row_num = len(unpacked_bits) // column_num
+            if len(unpacked_bits) % column_num != 0:
+                print("数据长度不是列数的整数倍，可能存在错误。")
+                return None
+
+            # 转换为矩阵
+            matrix = unpacked_bits.reshape((row_num, column_num))
+            return matrix
+        except Exception as e:
+            print(f"解码数据为矩阵时发生错误: {e}")
+            return None
+
+    @staticmethod
+    def display_matrix_as_image(matrix, cell_size=20):
+        """
+        显示矩阵对应的黑白图像，每个矩阵元素对应固定大小的正方形像素，并添加网格线。
+        :param matrix: 解码后的矩阵
+        :param cell_size: 每个单元格的大小（像素）
+        """
+        try:
+            import cv2
+            import numpy as np
+
+            # 将矩阵转换为0-255的灰度图像（0为黑，255为白）
+            image = (matrix * 255).astype(np.uint8)
+
+            # 放大矩阵
+            rows, cols = matrix.shape
+            enlarged_image = np.kron(image, np.ones((cell_size, cell_size), dtype=np.uint8))
+
+            # 添加网格线
+            grid_image = cv2.cvtColor(enlarged_image, cv2.COLOR_GRAY2BGR)
+            for r in range(0, rows * cell_size, cell_size):
+                cv2.line(grid_image, (0, r), (cols * cell_size, r), (128, 128, 128), 1)
+            for c in range(0, cols * cell_size, cell_size):
+                cv2.line(grid_image, (c, 0), (c, rows * cell_size), (128, 128, 128), 1)
+
+            # 显示图像
+            cv2.imshow("Matrix Image with Grid", grid_image)
+            cv2.waitKey(0)  # 显示窗口的同时继续运行程序
+            cv2.destroyAllWindows()
+        except Exception as e:
+            print(f"显示矩阵图像时发生错误: {e}")
+
+    def run(self):
+        while True:
+            data = self.client.recv(4096)  # 接收信息，指定接收的大小
+            if not data:
+                break
+
+            print("原始报文:")
+            print(data.hex())  # 输出接收到的原始字节数据
+
+            # 尝试解码为矩阵形式
+            matrix = self.decode_data_to_matrix(data, self.column_num)
+            if matrix is not None:
+                print("转换后的矩阵:")
+                print(matrix)
+
+                # 显示对应的黑白图像
+                self.display_matrix_as_image(matrix)
+            else:
+                print("无法将数据转换为矩阵。")
+
+
+if __name__ == '__main__':
+    import argparse
+    parser = argparse.ArgumentParser(description='阀门测程序')
+    parser.add_argument('-c', default=True, action='store_true', help='是否是开个客户端', required=False)
+    parser.add_argument('-m', default='127.0.0.1', help='指定master主机名')
+    parser.add_argument('-p', default=13452, help='指定端口')
+    parser.add_argument('-cnt', default=64, help='指定端口')
+    args = parser.parse_args()
+    mask_size = (1024, args.cnt)  # size of cv (Width, Height)
+    if args.c:
+        print("运行客户机")
+        virtual_valve = VirtualValve(host=args.m, port=args.p)
+        virtual_valve.run()