The model save and load __python of SVM in Python opencv3.x

Nonsense not much to say directly on the code:

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 '
detach data ' 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)
' start training '

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)
' Start forecast '
_, y_pred = Svm2.predict (x_ Test)

' metrics the Scikit-learn module to calculate the accuracy ' from
sklearn import metrics
print Metrics.accuracy_score ( Y_test, y_pred))

The key code is as follows:

Create:

Import cv2
SVM = cv2.ml.SVM_create ()
Svm.setkernel (Cv2.ml.SVM_LINEAR)

The other is the older version, basically not.

Load:

SVM2 = Cv2.ml.SVM_load ("Svmtest.mat")