I'm loading a set of test images via OpenCV (in Python) which are 128x128 in size, reshape them into vectors (1, 128x128) and put them all together in a matrix to calculate PCA. I'm using the new cv2 libaries...
import os import cv2 as cv import numpy as np matrix_test = None for image in os.listdir('path_to_dir'): imgraw = cv.imread(os.path.join('path_to_dir', image), 0) imgvector = imgraw.reshape(128*128) try: matrix_test = np.vstack((matrix_test, imgvector)) except: matrix_test = imgvector # PCA mean, eigenvectors = cv.PCACompute(matrix_test, np.mean(matrix_test, axis=0))
And it allways fails on the PCA part (I tested the image loading and all, the resulting matrix is how it should be)...the error I get is:
File "main.py", line 22, in
mean, eigenvectors = cv.PCACompute(matrix_test, np.mean(matri_test, axis=0))
cv2.error: /path/to/OpenCV-2.3.1/modules/core/src/matmul.cpp:2781: error: (-215) _mean.size() == mean_sz in function operator()
I think the problem is with the size of
Its size is (128x128,) and not (1, 128x128). Thus the code below should work
mean, eigenvectors = cv.PCACompute(matrix_test, np.mean(matrix_test, axis=0).reshape(1,-1))
You can also put
cv.PCACompute(matrix_test, mean = np.array())
and the function computes the mean.