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- some cleanup with depth

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This commit is contained in:
Tadas Baltrusaitis
2017-10-21 12:15:22 +01:00
parent 1cfb765bb9
commit e71d13a22a
16 changed files with 15 additions and 122 deletions
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80
lib/local/LandmarkDetector/src/SVR_patch_expert.cpp
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@@ -195,72 +195,6 @@ void SVR_patch_expert::Response(const cv::Mat_<float>& area_of_interest, cv::Mat
}
void SVR_patch_expert::ResponseDepth(const cv::Mat_<float>& area_of_interest, cv::Mat_<float> &response)
{
// How big the response map will be
int response_height = area_of_interest.rows - weights.rows + 1;
int response_width = area_of_interest.cols - weights.cols + 1;
// the patch area on which we will calculate reponses
cv::Mat_<float> normalised_area_of_interest;
if(response.rows != response_height || response.cols != response_width)
{
response.create(response_height, response_width);
}
if(type == 0)
{
// Perform normalisation across whole patch
cv::Scalar mean;
cv::Scalar std;
// ignore missing values
cv::Mat_<uchar> mask = area_of_interest > 0;
cv::meanStdDev(area_of_interest, mean, std, mask);
// if all values the same don't divide by 0
if(std[0] == 0)
{
std[0] = 1;
}
normalised_area_of_interest = (area_of_interest - mean[0]) / std[0];
// Set the invalid pixels to 0
normalised_area_of_interest.setTo(0, mask == 0);
}
else
{
printf("ERROR(%s,%d): Unsupported patch type %d!\n", __FILE__,__LINE__,type);
abort();
}
cv::Mat_<float> svr_response;
// The empty matrix as we don't pass precomputed dft's of image
cv::Mat_<double> empty_matrix_0(0,0,0.0);
cv::Mat_<float> empty_matrix_1(0,0,0.0);
cv::Mat_<float> empty_matrix_2(0,0,0.0);
// Efficient calc of patch expert response across the area of interest
matchTemplate_m(normalised_area_of_interest, empty_matrix_0, empty_matrix_1, empty_matrix_2, weights, weights_dfts, svr_response, CV_TM_CCOEFF);
response.create(svr_response.size());
cv::MatIterator_<float> p = response.begin();
cv::MatIterator_<float> q1 = svr_response.begin(); // respone for each pixel
cv::MatIterator_<float> q2 = svr_response.end();
while(q1 != q2)
{
// the SVR response passed through a logistic regressor
*p++ = 1.0/(1.0 + exp( -(*q1++ * scaling + bias )));
}
}
// Copy constructor
Multi_SVR_patch_expert::Multi_SVR_patch_expert(const Multi_SVR_patch_expert& other) : svr_patch_experts(other.svr_patch_experts)
{
@@ -321,17 +255,3 @@ void Multi_SVR_patch_expert::Response(const cv::Mat_<float> &area_of_interest, c
}
void Multi_SVR_patch_expert::ResponseDepth(const cv::Mat_<float>& area_of_interest, cv::Mat_<float>& response)
{
int response_height = area_of_interest.rows - height + 1;
int response_width = area_of_interest.cols - width + 1;
if(response.rows != response_height || response.cols != response_width)
{
response.create(response_height, response_width);
}
// With depth patch experts only do raw data modality
svr_patch_experts[0].ResponseDepth(area_of_interest, response);
}
//===========================================================================