我有一个名为data
的TrainingSets(下面的结构)向量class TrainingSet
{
public:
int time;
float input[2];
float output[3*NUM_TRACKING_POINTS];
TrainingSet(int t, float in[2], float out[3*NUM_TRACKING_POINTS])
{
time = t;
for (int i = 0; i < 2; i++)
input[i] = in[i];
for (int i = 0; i < 3*NUM_TRACKING_POINTS; i++)
output[i] = out[i];
}
TrainingSet()
{
}
};
然后我尝试获取此Vector的内容,并将它们放入CvMats中以便训练神经网络。
int datasize = data.size();
float** in = new float*[datasize];
float** out = new float*[datasize];
for (int i = 0; i < datasize; i++) {
in[i] = new float[2*TIME_STEPS];
out[i] = new float[3*NUM_TRACKING_POINTS];
}
for ( int i = 0 ; i < datasize; i ++)
{
// get the first set in the sequence.
TrainingSet tset = data.front();
data.pop();
// get the inputs
in[i] = new float[2*TIME_STEPS];
in[i][0] = tset.input[0];
in[i][1] = tset.input[1];
// get the outputs
out[i] = new float[3*NUM_TRACKING_POINTS];
for (int j = 0; j < 3*NUM_TRACKING_POINTS; j++)
out[i][j] = tset.output[j];
for (int j = 2; j < 2*TIME_STEPS; j++)
{
if (i == 0)
in[i][j] = 0.0f;
else
in[i][j] = in[i - 1][j - 2];
}
}
// make matrices from data.
CvMat *trainInput = cvCreateMat(datasize, 2*TIME_STEPS, CV_32FC1);
cvInitMatHeader(trainInput, datasize, 2*TIME_STEPS, CV_32FC1, in);
CvMat *trainOutput = cvCreateMat(datasize, 3*NUM_TRACKING_POINTS, CV_32FC1);
cvInitMatHeader(trainOutput, datasize, 3*NUM_TRACKING_POINTS, CV_32FC1, out);
for (int x = 0; x < datasize; x++)
{
cout << "IN: ";
for (int y = 0; y < 2*TIME_STEPS; y++)
cout << cvmGet(trainInput, x, y) << " ";
cout << endl << "IN: ";
for (int y = 0; y < 2*TIME_STEPS; y++)
cout << in[x][y] << " ";
cout << endl << "OUT: ";
for (int y = 0; y < 3 * NUM_TRACKING_POINTS; y++)
cout << cvmGet(trainOutput, x, y) << " ";
cout << endl << "OUT: ";
for (int y = 0; y < 3 * NUM_TRACKING_POINTS; y++)
cout << out[x][y] << " ";
cout << endl << endl;
}
最后一个forloop是检查矩阵内容是否是我刚刚提供的数据,但它们不匹配。矩阵似乎有完全不同的数据。
关于出了什么问题的任何想法?
答案 0 :(得分:0)
我觉得in
和out
不是连续的数组,而是一个指针数组。
我认为cvMat需要一个连续的内存阵列才能对其进行操作。
一旦你创建了数组,你就不需要从它创建一个CvMat了 使用
CvSetData( header, data ).