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ml: don't use "getSubVector()" with 2D matrix

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It is designed for 1D vectors only
This commit is contained in:
Alexander Alekhin 2018-08-17 16:45:31 +03:00 committed by Alexander Alekhin
parent 7ee69740e8
commit 6e84abc746
2 changed files with 67 additions and 58 deletions
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13
modules/ml/include/opencv2/ml.hpp
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@ -239,7 +239,18 @@ public:
/** @brief Returns vector of symbolic names captured in loadFromCSV() */
CV_WRAP void getNames(std::vector<String>& names) const;
CV_WRAP static Mat getSubVector(const Mat& vec, const Mat& idx);
/** @brief Extract from 1D vector elements specified by passed indexes.
@param vec input vector (supported types: CV_32S, CV_32F, CV_64F)
@param idx 1D index vector
*/
static CV_WRAP Mat getSubVector(const Mat& vec, const Mat& idx);
/** @brief Extract from matrix rows/cols specified by passed indexes.
@param matrix input matrix (supported types: CV_32S, CV_32F, CV_64F)
@param idx 1D index vector
@param layout specifies to extract rows (cv::ml::ROW_SAMPLES) or to extract columns (cv::ml::COL_SAMPLES)
*/
static CV_WRAP Mat getSubMatrix(const Mat& matrix, const Mat& idx, int layout);
/** @brief Reads the dataset from a .csv file and returns the ready-to-use training data.

112
modules/ml/src/data.cpp
View File

@ -43,6 +43,8 @@
#include <algorithm>
#include <iterator>
#include <opencv2/core/utils/logger.hpp>
namespace cv { namespace ml {
static const float MISSED_VAL = TrainData::missingValue();
@ -54,69 +56,65 @@ Mat TrainData::getTestSamples() const
{
Mat idx = getTestSampleIdx();
Mat samples = getSamples();
return idx.empty() ? Mat() : getSubVector(samples, idx);
return idx.empty() ? Mat() : getSubMatrix(samples, idx, getLayout());
}
Mat TrainData::getSubVector(const Mat& vec, const Mat& idx)
{
if( idx.empty() )
return vec;
int i, j, n = idx.checkVector(1, CV_32S);
int type = vec.type();
CV_Assert( type == CV_32S || type == CV_32F || type == CV_64F );
int dims = 1, m;
if (!(vec.cols == 1 || vec.rows == 1))
CV_LOG_WARNING(NULL, "'getSubVector(const Mat& vec, const Mat& idx)' call with non-1D input is deprecated. It is not designed to work with 2D matrixes (especially with 'cv::ml::COL_SAMPLE' layout).");
return getSubMatrix(vec, idx, vec.rows == 1 ? cv::ml::COL_SAMPLE : cv::ml::ROW_SAMPLE);
}
if( vec.cols == 1 || vec.rows == 1 )
template<typename T>
Mat getSubMatrixImpl(const Mat& m, const Mat& idx, int layout)
{
int nidx = idx.checkVector(1, CV_32S);
int dims = m.cols, nsamples = m.rows;
Mat subm;
if (layout == COL_SAMPLE)
{
dims = 1;
m = vec.cols + vec.rows - 1;
std::swap(dims, nsamples);
subm.create(dims, nidx, m.type());
}
else
{
dims = vec.cols;
m = vec.rows;
subm.create(nidx, dims, m.type());
}
Mat subvec;
for (int i = 0; i < nidx; i++)
{
int k = idx.at<int>(i); CV_CheckGE(k, 0, "Bad idx"); CV_CheckLT(k, nsamples, "Bad idx or layout");
if (dims == 1)
{
subm.at<T>(i) = m.at<T>(k); // at() has "transparent" access for 1D col-based / row-based vectors.
}
else if (layout == COL_SAMPLE)
{
for (int j = 0; j < dims; j++)
subm.at<T>(j, i) = m.at<T>(j, k);
}
else
{
for (int j = 0; j < dims; j++)
subm.at<T>(i, j) = m.at<T>(k, j);
}
}
return subm;
}
if( vec.cols == m )
subvec.create(dims, n, type);
else
subvec.create(n, dims, type);
if( type == CV_32S )
for( i = 0; i < n; i++ )
{
int k = idx.at<int>(i);
CV_Assert( 0 <= k && k < m );
if( dims == 1 )
subvec.at<int>(i) = vec.at<int>(k);
else
for( j = 0; j < dims; j++ )
subvec.at<int>(i, j) = vec.at<int>(k, j);
}
else if( type == CV_32F )
for( i = 0; i < n; i++ )
{
int k = idx.at<int>(i);
CV_Assert( 0 <= k && k < m );
if( dims == 1 )
subvec.at<float>(i) = vec.at<float>(k);
else
for( j = 0; j < dims; j++ )
subvec.at<float>(i, j) = vec.at<float>(k, j);
}
else
for( i = 0; i < n; i++ )
{
int k = idx.at<int>(i);
CV_Assert( 0 <= k && k < m );
if( dims == 1 )
subvec.at<double>(i) = vec.at<double>(k);
else
for( j = 0; j < dims; j++ )
subvec.at<double>(i, j) = vec.at<double>(k, j);
}
return subvec;
Mat TrainData::getSubMatrix(const Mat& m, const Mat& idx, int layout)
{
if (idx.empty())
return m;
int type = m.type();
CV_CheckType(type, type == CV_32S || type == CV_32F || type == CV_64F, "");
if (type == CV_32S || type == CV_32F) // 32-bit
return getSubMatrixImpl<int>(m, idx, layout);
if (type == CV_64F) // 64-bit
return getSubMatrixImpl<double>(m, idx, layout);
CV_Error(Error::StsInternal, "");
}
class TrainDataImpl CV_FINAL : public TrainData
@ -172,30 +170,30 @@ public:
}
Mat getTrainSampleWeights() const CV_OVERRIDE
{
return getSubVector(sampleWeights, getTrainSampleIdx());
return getSubVector(sampleWeights, getTrainSampleIdx()); // 1D-vector
}
Mat getTestSampleWeights() const CV_OVERRIDE
{
Mat idx = getTestSampleIdx();
return idx.empty() ? Mat() : getSubVector(sampleWeights, idx);
return idx.empty() ? Mat() : getSubVector(sampleWeights, idx); // 1D-vector
}
Mat getTrainResponses() const CV_OVERRIDE
{
return getSubVector(responses, getTrainSampleIdx());
return getSubMatrix(responses, getTrainSampleIdx(), cv::ml::ROW_SAMPLE); // col-based responses are transposed in setData()
}
Mat getTrainNormCatResponses() const CV_OVERRIDE
{
return getSubVector(normCatResponses, getTrainSampleIdx());
return getSubMatrix(normCatResponses, getTrainSampleIdx(), cv::ml::ROW_SAMPLE); // like 'responses'
}
Mat getTestResponses() const CV_OVERRIDE
{
Mat idx = getTestSampleIdx();
return idx.empty() ? Mat() : getSubVector(responses, idx);
return idx.empty() ? Mat() : getSubMatrix(responses, idx, cv::ml::ROW_SAMPLE); // col-based responses are transposed in setData()
}
Mat getTestNormCatResponses() const CV_OVERRIDE
{
Mat idx = getTestSampleIdx();
return idx.empty() ? Mat() : getSubVector(normCatResponses, idx);
return idx.empty() ? Mat() : getSubMatrix(normCatResponses, idx, cv::ml::ROW_SAMPLE); // like 'responses'
}
Mat getNormCatResponses() const CV_OVERRIDE { return normCatResponses; }
Mat getClassLabels() const CV_OVERRIDE { return classLabels; }