import numpy as np
from sklearn.feature_extraction import image
from scipy.misc import imread, imresize, imshow
import matplotlib.pyplot as plt
from PIL import Image, ImageFilter
import os, sys

shirts = []
jerseys = []

for file in os.listdir('shirts'):
    if file != ".DS_Store":
        mat = plt.imread('shirts/'+file)
        shirts.append(mat)

for file in os.listdir('jerseys'):
    if file != ".DS_Store":
        mat = plt.imread('jerseys/'+file)
        jerseys.append(mat)

shirts_resize = []
jerseys_resize = []

for shirt in shirts:
    new_shirt = imresize(shirt, (250, 200))
    shirts_resize.append(new_shirt)

for jersey in jerseys:
    new_jersey = imresize(jersey, (250, 200))
    jerseys_resize.append(new_jersey)

from mpl_toolkits.mplot3d import Axes3D
from sklearn import decomposition

shirts_ar = np.asarray(shirts_resize)
jerseys_ar = np.asarray(jerseys_resize)

#this reshapes it, giving it the number of
shirts_2 = shirts_ar.reshape(200,-1)
jerseys_2 = jerseys_ar.reshape(200,-1)

decomposition.PCA(n_components=2)