KNN模型的训练及加载 KNN模型的训练及加载

 def main():

    
  
    
     (train, train_labels), (test, test_labels) = XX_load_data()
    
     train = np.array(train / 255., dtype=np.float32)
    
     test = np.array(test / 255., dtype=np.float32)
    
     knn = cv2.ml.KNearest_create()
    
  
    
     print(train.shape, train_labels.shape)
    
     print(test.shape, test_labels.shape)
    
  
    
     knn.train(train, cv2.ml.ROW_SAMPLE, train_labels)
    
     # knn.save("XXX")
    
    
    
    

  knn = cv2.ml.KNearest_load(r"XXX")

    
     (train, train_labels), (test