import os

from PIL import Image
import numpy as np

datamatrix = []

labels = []

for root, subdirs, files in os.walk("C:/users/andre/OneDrive/Documenti/Politecnico/MLAI/HW1/PACS_homework"):
    for directory in subdirs:
        for root, subdirectories, files in os.walk("C:/users/andre/OneDrive/Documenti/Politecnico/MLAI/HW1/PACS_homework/"+directory):
            for file in files:
                imgdata = np.asarray(Image.open("C:/users/andre/OneDrive/Documenti/Politecnico/MLAI/HW1/PACS_homework/"+directory+"/"+file))
                x=imgdata.ravel()
                datamatrix.append(x)
                labels.append(subdirs)


from numpy import *
datamatrix = (datamatrix - mean(datamatrix)) / std(datamatrix)  #standardize


from sklearn.decomposition import PCA
datamatrix_t = PCA(2).fit transform(datamatrix)