from sklearn.externals import joblib
from sklearn.model_selection import train_test_split
import numpy as np
import cv2
import pylab as pl
path = u'testingData16.txt'
data0 = np.loadtxt(path,dtype = str,delimiter = ' ')
data = np.array( [[row[i] for i in range(0, 8) if i != 7] for row in data0] )#del the last col of the array
x = data[:,(1,2,3,4,5,6)]
y = data[:,0]
x = np.uint8(x)
y = np.uint8(y)
x_train, x_test, y_train, y_test = train_test_split(x, y, random_state=1, train_size=0.6)
#X = data[:,(1,2,3,4)]
X = x
clf = joblib.load("train_model_Adaboost.m")
y_hat = clf.predict(X)
print type(y_hat)
print type(y_hat[2])
img = np.reshape(y_hat,(584,565))
cv2.imshow('img',img)
cv2.waitKey(0)
