python opencv3.x中支持向量机(svm)模型保存与加载问题

亲自验证,可以解决svm的模型加载问题:

    import numpy as np
    from sklearn import datasets
     
    X,y = datasets.make_classification(n_samples=100,n_features=2,n_redundant=0,n_classes=2,random_state=7816)
     
    print(X.shape,y.shape)
    X = X.astype(np.float32)
    y = y * 2 - 1
    '''分离数据'''
    from sklearn import model_selection as ms
    X_train, X_test, y_train, y_test = ms.train_test_split(
        X, y, test_size=0.2, random_state=42
    )
    import cv2
    svm = cv2.ml.SVM_create()
    svm.setKernel(cv2.ml.SVM_LINEAR)
    '''开始训练'''
     
    y_train = y_train.reshape(-1, 1)
    # print(y_train)
    svm.train(X_train, cv2.ml.ROW_SAMPLE, y_train)
    svm.save("svmtest.mat")
    print ("Done\n")
     
    svm2 = cv2.ml.SVM_load("svmtest.mat")
     
    # svm2.load("svmtest.mat")
    # print(svm2)
    '''开始预测'''
    _, y_pred = svm2.predict(X_test)
     
    '''用scikit-learn的metrics模块计算准确率'''
    from sklearn import metrics
    print(metrics.accuracy_score(y_test, y_pred))

关键代码如下:

创建:

    import cv2
    svm = cv2.ml.SVM_create()
    svm.setKernel(cv2.ml.SVM_LINEAR)

其它的写法都是以前较老的版本,基本上都不行

加载:

svm2 = cv2.ml.SVM_load("svmtest.mat")

猜你喜欢

转载自blog.csdn.net/weixin_38208741/article/details/84521372
今日推荐