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Question

在提取图像文件夹的HOG功能后，我想将所有这些结果添加到一个矩阵中。我怎么能这样做？这是我在matlab中的代码：

training_female = 'E:\Training Set\Female Images';

% read all images with specified extention, its jpg in our case
filenames = dir(fullfile(training_female, '*.jpg'));

% count total number of photos present in that folder
total_images = numel(filenames);

for n = 1:total_images

% Specify images names with full path and extension    
full_name= fullfile(training_female, filenames(n).name);

% Read images
training_images = imread(full_name);
[featureVector, hogVisualization] = extractHOGFeatures(training_images);
figure (n)

    % Show all images
    imshow(training_images); hold on;                  
    plot(hogVisualization);
end

Answer 1

通过查看documentation，调用extractHOGFeatures计算给定输入图像的1 x N向量。因为计算它的输出大小可能有点麻烦，这也取决于您为HOG检测器设置的参数，所以最好首先创建一个空矩阵并在每次迭代时动态连接这些特征。通常，对于性能，如果要在迭代的基础上填充元素，则预先分配矩阵。不这样做会给性能带来轻微的影响，但考虑到你的情况，它是最具适应性的。您可能希望调整HOG参数，如果我们以动态方式执行，则可以消除确定矩阵总大小应该是什么的麻烦。

所以做这样的事情。我已将%//New个标记放在我修改代码的位置：

training_female = 'E:\Training Set\Female Images';

% read all images with specified extention, its jpg in our case
filenames = dir(fullfile(training_female, '*.jpg'));

% count total number of photos present in that folder
total_images = numel(filenames);

featureMatrix = []; %// New - Declare feature matrix

for n = 1:total_images

    % Specify images names with full path and extension    
    full_name= fullfile(training_female, filenames(n).name);

    % Read images
    training_images = imread(full_name);
    [featureVector, hogVisualization] = extractHOGFeatures(training_images);

    %// New - Add feature vector to matrix
    featureMatrix = [featureMatrix; featureVector];
    figure(n);

    % Show all images
    imshow(training_images); hold on;                  
    plot(hogVisualization);
end

featureMatrix将包含您的HOG功能，其中每行代表每个图像。因此，对于特定图像i，您可以通过以下方式确定HOG功能：

feature = featureMatrix(i,:);

买者

我需要提一下，上面的代码假设目录中的所有图片大小相同。如果它们不是，则每个HOG调用的输出向量大小将不同。如果是这种情况，您将需要一个单元阵列来适应不同的大小。

因此，做这样的事情：

training_female = 'E:\Training Set\Female Images';

% read all images with specified extention, its jpg in our case
filenames = dir(fullfile(training_female, '*.jpg'));

% count total number of photos present in that folder
total_images = numel(filenames);

featureMatrix = cell(1,total_images); %// New - Declare feature matrix

for n = 1:total_images

    % Specify images names with full path and extension    
    full_name= fullfile(training_female, filenames(n).name);

    % Read images
    training_images = imread(full_name);
    [featureVector, hogVisualization] = extractHOGFeatures(training_images);

    %// New - Add feature vector to matrix
    featureMatrix{n} = featureVector;
    figure(n);

    % Show all images
    imshow(training_images); hold on;                  
    plot(hogVisualization);
end

要访问特定图片的功能或图像i，请执行以下操作：

feature = featureMatrix{i};

如何将HOG功能添加到矩阵（matlab）

1 个答案:

买者