小编Sea*_*tar的帖子

我在使用Python 2.7在Tensorflow 1.3.0中实现DNNClassifier时遇到错误.我从Tensorflow tf.estimator Quickstart教程中获取了示例代码,我想用自己的数据集运行它:3D坐标和10个不同的类(int标签).这是我的实现:

#!/usr/bin/env python
# -*- coding: utf-8 -*-

def ReadLabels(file):
    #load the labels from test file here
    labelFile = open(file, "r")
    Label = labelFile.readlines();
    returnL = [[Label[i][j+1] for j in range(len(Label[0])-3)] for i in range(len(Label))]
    returnLint = list();
    for i in range(len(returnL)):
        tmp = ''
        for j in range(len(returnL[0])):
            tmp += str(returnL[i][j])
        returnLint.append(int(tmp))
    return returnL, returnLint

def NumpyReadBin(file,numcols,type):
    #load the data from binary file here
    import numpy as np
    trainData = np.fromfile(file,dtype=type)
    numrows = len(trainData)/numcols …

我目前正在同一个类中用c ++实现不同的opencv机器学习工具.因此,我遇到了将超类的指针向下转换cv::ml::StatModel为子类的问题cv::ml::SVM(例如).

在在线教程中,人们通常会发现opencv分类器的实现,如下所示:

cv::Ptr<cv::ml::SVM> classifier = cv::ml::SVM::create();

我想要做的是在类构造函数中进行动态转换.这是我的类变量的一部分:

class Classifier{
private:
    cv::Ptr<cv::ml::StatModel> classifier;
    cv::Ptr<cv::ml::SVM> SVM;
//... followed by more code };

在我的构造函数中:

Classifier::Classifier(const char* filename, cv::ml::SVM& svm){
    bool load = Classifier::getData(filename);
    if (load==0){
        cout << "Error opening file!" << endl;
    }
    else{
        classifier = &svm;
        //Here I want to do something linke this, just with cv::Ptr:
        //the following line gives compiler errors because c++ does not know that cv::Ptr is a pointer...
        SVM = dynamic_cast<cv::ml::SVM*>(classifier); 
        Classifier::setUpSVM(); …