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.)

Answer 1

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);
   ...