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Fixing max-pooling for different stride sizes.

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Tadas Baltrusaitis
2017-08-15 08:55:37 +01:00
parent 1d76c96cc8
commit 02a66563e1
1 changed files with 12 additions and 2 deletions
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14
lib/local/LandmarkDetector/src/FaceDetectorMTCNN.cpp
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@@ -245,9 +245,18 @@ std::vector<cv::Mat_<float>> CNN::Inference(const cv::Mat& input_img)
for (int x = 0; x < input_maps[in].cols; x += stride_x)
{
int max_x = cv::min(input_maps[in].cols, x + kernel_size_x);
int x_in_out = floor(x / stride_x);
if (x_in_out >= out_x)
continue;
for (int y = 0; y < input_maps[in].rows; y += stride_y)
{
int y_in_out = floor(y / stride_y);
if (y_in_out >= out_y)
continue;
int max_y = cv::min(input_maps[in].rows, y + kernel_size_y);
float curr_max = -FLT_MAX;
@@ -263,8 +272,6 @@ std::vector<cv::Mat_<float>> CNN::Inference(const cv::Mat& input_img)
}
}
}
int x_in_out = floor(x / stride_x);
int y_in_out = floor(y / stride_y);
sub_out.at<float>(y_in_out, x_in_out) = curr_max;
}
}
@@ -798,6 +805,9 @@ bool FaceDetectorMTCNN::DetectFaces(vector<cv::Rect_<double> >& o_regions, const
prop_img = (prop_img - 127.5) * 0.0078125;
proposal_imgs.push_back(prop_img);
// Perform RNet on the proposal image
std::vector<cv::Mat_<float> > rnet_out = RNet.Inference(prop_img);
}
return true;