Matlab与python图像数据传递（或matlab与numpy array数据传递）

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Matlab与python图像数据传递（或matlab与numpy array数据传递）

2024-06-28 05:06| 来源: 网络整理| 查看: 265

matlab中读入的图像数据是uint8数据类型的矩阵，而python中使用的图像数据格式为ndarray。中间涉及数据转换。

处理过程：matlab读入图像，在python语言中使用opencv做灰度化处理，再将灰度图像传递回matlab。

matlab中代码：（transferdata.m）

clear classes close all % 读入图像 image=imread('Default.jpg'); % 显示图像 figure imshow(image); % 1,3通道交换 image=changechannel(image); % 转换成python图像数据格式 imagenparry=mat2nparray(image); % 导入python包，test.py文件 obj = py.importlib.import_module('test'); % 重载obj py.importlib.reload(obj); % 灰度化处理 graynparry=obj.mytest(imagenparry); % 转化成mat数据格式 gray=nparray2mat(graynparry); % 更改数据格式 gray=uint8(gray); % 显示图像 figure imshow(gray);

python中代码：（test.py）

#encoding=utf-8 import cv2 def mytest(image): cv2.imshow('src', image) cv2.waitKey() imggray=cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) return imggray if __name__ == "__main__": image = cv2.imread('Default.jpg') results=mytest(image) cv2.imshow('gray', results) cv2.waitKey()

几点重要的说明：

1）changechannel.m函数代码为：

function output = changechannel( input ) %matlab image的图像通道顺序为R，G，B %opencv image的图像通道顺序为B，G，R %此函数进行1,3通道的交换 output=input; output(:,:,1)=input(:,:,3); output(:,:,3)=input(:,:,1); end

matlab读入的图像RGB通道的顺序，与opencv的读入图像的RGB通道不一致，所以要将1,3通道交换之后再传递图像数据。

2）使用py.importlib.reload(obj)重载test.py。

matlab中默认将test.py加入到工作空间，如果不重载的话，就算更改了test.py的代码，在matlab工作空间也不会生效。

3）mat2nparray.m将mat图像数据转化为numpy array图像数据，以便在Python中使用

function result = mat2nparray( matarray ) %mat2nparray Convert a Matlab array into an nparray % Convert an n-dimensional Matlab array into an equivalent nparray data_size=size(matarray); if length(data_size)==1 % 1-D vectors are trivial result=py.numpy.array(matarray); elseif length(data_size)==2 % A transpose operation is required either in Matlab, or in Python due % to the difference between row major and column major ordering transpose=matarray'; % Pass the array to Python as a vector, and then reshape to the correct % size result=py.numpy.reshape(transpose(:)', int32(data_size)); else % For an n-dimensional array, transpose the first two dimensions to % sort the storage ordering issue transpose=permute(matarray,[length(data_size):-1:1]); % Pass it to python, and then reshape to the python style of matrix % sizing result=py.numpy.reshape(transpose(:)', int32(fliplr(size(transpose)))); end end

4）nparray2mat.m将python的图像数据转化为mat图像数据，以便在matlab中使用

function result = nparray2mat( nparray ) %nparray2mat Convert an nparray from numpy to a Matlab array % Convert an n-dimensional nparray into an equivalent Matlab array data_size = cellfun(@int64,cell(nparray.shape)); if length(data_size)==1 % This is a simple operation result=double(py.array.array('d', py.numpy.nditer(nparray))); elseif length(data_size)==2 % order='F' is used to get data in column-major order (as in Fortran % 'F' and Matlab) result=reshape(double(py.array.array('d', ... py.numpy.nditer(nparray, pyargs('order', 'F')))), ... data_size); else % For multidimensional arrays more manipulation is required % First recover in python order (C contiguous order) result=double(py.array.array('d', ... py.numpy.nditer(nparray, pyargs('order', 'C')))); % Switch the order of the dimensions (as Python views this in the % opposite order to Matlab) and reshape to the corresponding C-like % array result=reshape(result,fliplr(data_size)); % Now transpose rows and columns of the 2D sub-arrays to arrive at the % correct Matlab structuring result=permute(result,[length(data_size):-1:1]); end end

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Matlab与python图像数据传递（或matlab与numpy array数据传递）

Matlab与python图像数据传递（或matlab与numpy array数据传递）

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