import algorithm.extra_feature_sift as extra_feature_sift
import algorithm.classify_svm as classify_svm
import time
startTime = time.time()
# 用SIFT方法进行特征预处理
extra_feature_sift.run(method_generateFaceRS='sift')
# 用SVM进行分类
classify_svm.run(method_readFaceRS='sift')
endTime = time.time()
print('\nSIFT_SVM costs %.2f seconds.' % (endTime - startTime))
import algorithm.extra_feature_hog as extra_feature_hog
import algorithm.classify_svm as classify_svm
import time
startTime = time.time()
# 用HOG方法进行特征预处理
extra_feature_hog.run(method_generateFaceRS='hog')
# 采用SVM进行分类，输出HOG_SVM犯错矩阵
classify_svm.run(method_readFaceRS='hog')
endTime = time.time()
print('\nHOG_SVM costs %.2f seconds.' % (endTime - startTime))
import algorithm.extra_feature_lbp as extra_feature_lbp
import algorithm.classify_svm as classify_svm
import time
startTime = time.time()
# 用LBP方法进行特征预处理
extra_feature_lbp.run(method_generateFaceRS='lbp')
# 用SVM进行分类
classify_svm.run(method_readFaceRS='lbp')
endTime = time.time()
print('\nLBP_SVM costs %.2f seconds.' % (endTime - startTime))