是否可以以字节为单位转换特征图

Question

Python 3.6

Unity 2019

我正在努力寻找将特征图数据传输到unity的最佳解决方案。

我想以字节为单位发送数据。然而，我没有找到如何将其编码为字节，然后统一解码。

基本上是一个4d阵列，需要根据我对的理解转换为字节

Python工件

for fmap in feature_maps:
bytes = []
bytes.append(fmap)
arrays_of_features.append(bytes)
data = np.array(arrays_of_features, dtype=float) # this is not working because of the fact is multidimensional array apparently. 
print(fmap)
c.sendall(data.tobytes())

UNity工件：byte[]字节=新字节[4000]；int idxUsedBytes=客户端。接收(字节(；

floatsReceived = new float[idxUsedBytes / 4];
Buffer.BlockCopy(bytes, 0, floatsReceived, 0, idxUsedBytes);
print(floatsReceived[0]);

启示：如何让Unity中的c#与Python 通信

一张功能图看起来像这样：

[[[[ 0.          0.          0.         ...  0.         12.569366
0.        ]
[ 0.          0.          0.         ...  0.          4.421044
0.        ]
[ 0.          0.          0.         ...  0.          0.19193476
0.        ]
...
[ 0.          0.          0.         ...  0.          0.
0.        ]
[ 0.          0.          0.         ...  0.          0.
0.        ]
[ 0.          0.          0.         ...  0.          0.
0.        ]]
[[ 0.          0.          0.         ...  0.         12.910363
0.        ]
[ 0.          0.          0.         ...  0.          3.987629
0.        ]
[ 0.          0.          0.         ...  0.          1.6041028
0.        ]
...
[ 0.          0.          0.         ...  0.          0.
0.        ]
[ 0.          0.          0.         ...  0.          0.
0.        ]
[ 0.          0.          0.         ...  0.          0.
0.        ]]
[[ 0.          0.          0.         ...  0.          0.
0.        ]
[ 0.          0.          0.         ...  0.          0.
0.        ]
[ 0.          0.          0.         ...  0.          0.
0.        ]
...
[ 0.          0.          0.         ...  0.          0.
0.        ]
[ 0.          0.          0.         ...  0.          0.
0.        ]
[ 0.          0.          0.         ...  0.          0.
0.        ]]
...
[[ 0.          0.          0.         ...  0.          0.
0.        ]
[ 0.          0.          0.         ...  0.          0.
0.        ]
[ 0.          0.          0.         ...  0.          0.
0.        ]
...
[ 0.          0.          0.         ...  0.          0.
49.52598   ]
[ 0.          0.          0.         ...  0.          0.
10.050183  ]
[ 0.          0.          0.         ...  0.          9.6911745
0.        ]]
[[ 0.          0.          0.         ...  0.          0.
0.        ]
[ 0.          0.          0.         ...  0.          0.
0.        ]
[ 0.          0.          0.         ...  0.          0.
0.        ]
...
[ 0.          0.          0.         ...  0.          0.
29.483086  ]
[ 0.          0.          0.         ...  0.          0.
24.422682  ]
[ 0.          0.          2.253025   ...  0.          0.
15.935954  ]]
[[ 0.          0.          0.         ...  0.          0.
0.        ]
[ 0.          0.          0.         ...  0.          0.
0.        ]
[ 0.          0.         18.458588   ... 15.824303    0.
0.        ]
...
[ 0.          0.          0.         ... 25.163502   56.87079
42.9939    ]
[ 0.          0.         11.397255   ... 36.644962   17.04247
44.108196  ]
[ 0.          0.         33.134758   ... 30.220499    8.817273
36.6427    ]]]]

Answer 1

你的问题很不清楚，我相信你对numpy的工作原理感到困惑。如果是，让我们解释一下。numpy中的数组不过是内存中的一个字节字符串。特别是，当为您显示这些字节时，它们将由数据类型进行解释。数据类型不是用来存储基础数据的，而只是用来显示它。因此，更改数据类型只会改变数据的外观，而不会改变数据本身。尺寸也是一样。数据的维度只会改变数据的显示和访问方式，python实际上不会移动数据或改变数据本身。例如，

import numpy as np
x = np.array([[1,2,3],[4,5,6]],dtype='int64') #48 bytes, each int takes up 8 bytes.
print(x)
x.dtype = 'int32'
print(x)
x.dtype = 'float'
print(x)
x.dtype = 'int16'
print(x)

请注意，我们可以更改dtype，并且绝对零计算由数组完成(因为底层数据已经是一个字节数组(。同样，我们可以改变形状，也可以进行绝对零计算。

x.shape = (2,2,6)
print(x)

形状和数据类型与内存中存储的数据无关。希望这能清楚地说明我们现在如何将数组作为字节进行处理。

x = np.array([[1,2,3],[4,5,6]],dtype='int64')
print(x)
y = x.tobytes()
# Send y somewhere. Save to a file. Etc.
z = np.frombuffer(y)
z.dtype = 'int64'
z.shape = (2,3)
print(z)