trainingandtesting.py 文件源码

def trainClassifier(foldername,classifierName):
    model = cv2.ml.KNearest_create()
    features = []
    labels = []
    os.chdir(foldername)
    for filename in glob.iglob('*.png'):
        features.append(cv2.imread((filename),-1))
        labels.append(filename[0])
    list_hog_fd = []
    for feature in features:
        fd = hog(feature.reshape((27, 35)), orientations=9, pixels_per_cell=(9, 7), cells_per_block=(1, 1), visualise=False)
        list_hog_fd.append(fd)
    hog_features = np.array(list_hog_fd, 'float64')
    os.chdir("..")
    clf = LinearSVC()
    clf.fit(hog_features, labels)
    joblib.dump(clf,classifierName, compress=3)
    os.chdir("..")