根据时间戳值对RGB和深度图像排序代码的时间缩短

Question

我有RGB图像，深度图像和OpenPose图像(从RGB图像生成)。RGB和深度图像的数量是不同的，所以我必须找到确切的RGB图像对应于哪个深度图像。这是使用我对RGB和深度图像的时间戳值来完成的。

这里的问题是，我编写的这段代码大约需要7-10分钟才能执行，我觉得这需要花费很多时间。怎样才能缩短同样的时间？这里主要写的是花了很多时间。

function image_sorting(color_img, depth_img, Openpose, selected_color, selected_depth)


filePattern = fullfile(depth_img, '*.timestamp');
file = dir(filePattern);

filePattern2 = fullfile(color_img, '*.timestamp');
file2 = dir(filePattern2);

filePattern3 = fullfile(depth_img, '*.bmp');
file3 = dir(filePattern3);

filePattern4 = fullfile(Openpose, '*.png');
file4 = dir(filePattern4);

for k = 1:length(file)
    depthTimestampBase = file(k).name;
    depthTimestamp = fullfile(depth_img, depthTimestampBase);
    fileID = fopen(depthTimestamp,'r');
    % format longG
    A(k,:) = textscan(fileID,'%d64') ;
    fclose(fileID);
end


for m = 1:length(file2)
    rgbTimestampBase = file2(m).name;
    rgbTimestamp = fullfile(color_img, rgbTimestampBase);
    fileID2 = fopen(rgbTimestamp,'r');
    %format longG
    B(m,:) = textscan(fileID2,'%d64') ;
    fclose(fileID2);
end

%%%%%% Here there are two parts. Use any of them according to conditions
if length(file2) <= length(file)
    %PART 1:- If RGB images are less than depth then use the following code

    for m = 1:length(file2)
        for k = 1:length(file)

            C{k,m} = A{k,1} - B{m,1};
            if C{k,m}<0
                C{k,m} = -C{k,m};
            end
        end
    end

    [V,X] = min(cell2mat(C),[],1); % Is a row vector containing the minimum value of columns
    % V gives minimum value and X gives Index

    m = 1;
    for w= X

        depthDataBase = file3(w).name;
        rgbDataBase = file4(m).name;

        depthData = fullfile(depth_img, depthDataBase);
        rgbData = fullfile(Openpose, rgbDataBase);

        imageArrayy = imread(depthData);
        imageArrayy2 = imread(rgbData);

        depthData2 = fullfile(selected_depth, depthDataBase);
        imwrite(imageArrayy, depthData2);
        rgbData2 = fullfile(selected_color, rgbDataBase);
        imwrite(imageArrayy2, rgbData2);


        m = m+1; % for part 2 m = m+1
    end


    %
    % PART 2:- If RGB images are more than depth then use the following code
else

    for m = 1:length(file2)
        for k = 1:length(file)

            C{m,k} = A{k,1} - B{m,1};
            if C{m,k}<0
                C{m,k} = -C{m,k};
            end
        end
    end

    [V,X] = min(cell2mat(C),[],1); % Is a row vector containing the minimum value of columns
    % V gives minimum value and X gives Index

    w = 1;
    for m= X

        depthDataBase = file3(w).name;
        rgbDataBase = file4(m).name;

        depthData = fullfile(depth_img, depthDataBase);
        rgbData = fullfile(Openpose, rgbDataBase);

        imageArrayy = imread(depthData);
        imageArrayy2 = imread(rgbData);

        depthData2 = fullfile(selected_depth, depthDataBase);
        imwrite(imageArrayy, depthData2);
        rgbData2 = fullfile(selected_color, rgbDataBase);
        imwrite(imageArrayy2, rgbData2);

        w = w+1;
    end
end

更新1:-概要文件执行时间的屏幕截图。

Answer 1

按照Cris的建议，对路径进行了更改，并使用了复制文件的提示，现在大约需要21秒。这是解决办法

function image_sorting(color_img, depth_img, Openpose, selected_color, selected_depth)


file = dir(fullfile(depth_img, '*.timestamp'));

file2 = dir(fullfile(color_img, '*.timestamp'));

file3 = dir(fullfile(depth_img, '*.bmp'));

file4 = dir(fullfile(Openpose, '*.png'));


for k = 1:length(file)
    fileID = fopen(fullfile(depth_img, file(k).name),'r');
    % format longG
    A(k,:) = textscan(fileID,'%d64') ;
    fclose(fileID);
end


for m = 1:length(file2)

    fileID2 = fopen(fullfile(color_img, file2(m).name),'r');
    %format longG
    B(m,:) = textscan(fileID2,'%d64') ;
    fclose(fileID2);
end

%%%%%% Here there are two parts. Use any of them according to conditions
if length(file2) <= length(file)
    %PART 1:- If RGB images are less than depth then use the following code

    for m = 1:length(file2)
        for k = 1:length(file)

            C{k,m} = A{k,1} - B{m,1};
            if C{k,m}<0
                C{k,m} = -C{k,m};
            end
        end
    end

    [V,X] = min(cell2mat(C),[],1); % Is a row vector containing the minimum value of columns
    % V gives minimum value and X gives Index

    m = 1;
    copyfile(Openpose, selected_color) 
    for w= X

        depthDataBase = file3(w).name;
        %rgbDataBase = file4(m).name;

        depthData = fullfile(depth_img, depthDataBase);
        %rgbData = fullfile(Openpose, rgbDataBase);

        imageArrayy = imread(depthData);
        %imageArrayy2 = imread(rgbData);

        depthData2 = fullfile(selected_depth, depthDataBase);
        imwrite(imageArrayy, depthData2);
        %rgbData2 = fullfile(selected_color, rgbDataBase);
        %imwrite(imageArrayy2, rgbData2);
        %movefile(file4, file5) 


        m = m+1; % for part 2 m = m+1
    end


    %
    % PART 2:- If RGB images are more than depth then use the following code
else

    for m = 1:length(file2)
        for k = 1:length(file)

            C{m,k} = A{k,1} - B{m,1};
            if C{m,k}<0
                C{m,k} = -C{m,k};
            end
        end
    end

    [V,X] = min(cell2mat(C),[],1); % Is a row vector containing the minimum value of columns
    % V gives minimum value and X gives Index

    copyfile(depth_img, selected_depth)
    for m= X

        %depthDataBase = file3(w).name;
        rgbDataBase = file4(m).name;

        %depthData = fullfile(depth_img, depthDataBase);
        rgbData = fullfile(Openpose, rgbDataBase);

        %imageArrayy = imread(depthData);
        imageArrayy2 = imread(rgbData);

        %depthData2 = fullfile(selected_depth, depthDataBase);
        %imwrite(imageArrayy, depthData2);
        rgbData2 = fullfile(selected_color, rgbDataBase);
        imwrite(imageArrayy2, rgbData2);


        w = w+1;
    end
end