CODEWITHSUNDEEP
pythonopencvopencv3.1
F.X.
F.X.

Reputation: 7327

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

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.)

Upvotes: 1

Views: 7023

Answers (1)

Kinght 金
Kinght 金

Reputation: 18341

Simple answer:

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

With details:

  1. 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);
}

  2. 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.

  3. 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);
...

Upvotes: 5

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