How to use the PCACompute function from Python in OpenCV 3?

Question

The cv2.PCACompute function worked well in OpenCV 2.4 using the following syntax :

import cv2
mean, eigvec = cv2.PCACompute(data)

The function exists in OpenCV 3.1, but raises the following exception :

TypeError: Required argument 'mean' (pos 2) not found

The C++ documentation is not very helpful at explaining how I should call it from Python. I'm guessing that InputOutputArray arguments are now also mandatory arguments in the Python function signature, but I am unable to find a way to make them work.

Is there a way I can call it properly?

(Note: I know there are other ways I can run a PCA, and I'll probably end up with one of them. I'm just curious about how the new OpenCV bindings works.)

If it helps, there was an old question that is similar to this problem you faced, where the same (and other) solution were given. — DarkCygnus
– DarkCygnus, Commented Dec 5, 2017 at 19:06

Kinght 金 · Accepted Answer · 2017-10-31 05:16:55Z

5

Simple answer:

mean, eigvec = cv2.PCACompute(data, mean=None)

With details:

Let search PCACompute the source first.Then find this:

// [modules/core/src/pca.cpp](L351-L360)
void cv::PCACompute(InputArray data, InputOutputArray mean,
                    OutputArray eigenvectors, int maxComponents)
{
    CV_INSTRUMENT_REGION()

    PCA pca;
    pca(data, mean, 0, maxComponents);
    pca.mean.copyTo(mean);
    pca.eigenvectors.copyTo(eigenvectors);
}

OK, now we read the document:

C++: PCA& PCA::operator()(InputArray data, InputArray mean, int flags, int maxComponents=0)
Python: cv2.PCACompute(data[, mean[, eigenvectors[, maxComponents]]]) → mean, eigenvectors

Parameters: 
    data – input samples stored as the matrix rows or as the matrix columns.
    mean – optional mean value; if the matrix is empty (noArray()), the mean is computed from the data.
flags –
    operation flags; currently the parameter is only used to specify the data layout.

    CV_PCA_DATA_AS_ROW indicates that the input samples are stored as matrix rows.
    CV_PCA_DATA_AS_COL indicates that the input samples are stored as matrix columns.
maxComponents – maximum number of components that PCA should retain; by default, all the components are retained.

This to say,

## py
mean, eigvec = cv2.PCACompute(data, mean=None)

is equals to

// cpp 
PCA pca;
pca(data, mean=noArray(), flags=CV_PCA_DATA_AS_ROW);
...

answered Oct 31, 2017 at 5:16

Kinght 金

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2 Comments

F.X. Over a year ago

Thank you, the fact that you had to pass None wasn't obvious at all in the docs, even those about noArray() :)

Kinght 金 Over a year ago

The document says mean – optional mean value; if the matrix is empty (noArray()), the mean is computed from the data. So, just pass None.

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