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Speeding up the fully connected layer through better data layout

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Tadas Baltrusaitis
2017-08-24 17:00:32 +01:00
parent a25da69550
commit 92dde3b80f
1 changed files with 22 additions and 16 deletions
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38
lib/local/LandmarkDetector/src/FaceDetectorMTCNN.cpp
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@@ -205,52 +205,58 @@ void fully_connected(std::vector<cv::Mat_<float> >& outputs, const std::vector<c
{
// Concatenate all the maps
cv::Size orig_size = input_maps[0].size();
cv::Mat_<float> input_concat = input_maps[0].t();
input_concat = input_concat.reshape(0, 1);
cv::Mat_<float> input_concat(input_maps.size(), input_maps[0].cols * input_maps[0].rows);
for (size_t in = 1; in < input_maps.size(); ++in)
for (size_t in = 0; in < input_maps.size(); ++in)
{
cv::Mat_<float> add = input_maps[in].t();
cv::Mat_<float> add = input_maps[in];
// Reshape if all of the data will be flattened
if (input_concat.rows != weights.cols)
{
add = add.t();
}
add = add.reshape(0, 1);
cv::vconcat(input_concat, add, input_concat);
add.copyTo(input_concat.row(in));
}
// Treat the input as separate feature maps
if (input_concat.rows == weights.rows)
if (input_concat.rows == weights.cols)
{
input_concat = input_concat.t() * weights;
input_concat = weights * input_concat;
// Add biases
for (size_t k = 0; k < biases.rows; ++k)
{
input_concat.col(k) = input_concat.col(k) + biases.at<float>(k);
input_concat.row(k) = input_concat.row(k) + biases.at<float>(k);
}
outputs.clear();
// Resize and add as output
for (size_t k = 0; k < biases.rows; ++k)
{
cv::Mat_<float> reshaped = input_concat.col(k).clone();
reshaped = reshaped.reshape(1, orig_size.width).t();
cv::Mat_<float> reshaped = input_concat.row(k).clone();
reshaped = reshaped.reshape(1, orig_size.height);
outputs.push_back(reshaped);
}
}
else
{
// Flatten the input
input_concat = input_concat.reshape(0, 1);
input_concat = input_concat.reshape(0, input_concat.rows * input_concat.cols);
input_concat = input_concat * weights + biases.t();
input_concat = weights * input_concat + biases;
outputs.clear();
outputs.push_back(input_concat.t());
outputs.push_back(input_concat);
}
}
else
{
cv::Mat out = input_maps[0].t() * weights + biases.t();
cv::Mat out = weights * input_maps[0] + biases;
outputs.clear();
outputs.push_back(out);
outputs.push_back(out.t());
}
}
@@ -892,7 +898,7 @@ void CNN::Read(const string& location)
// Fully connected layer
cv::Mat_<float> weights;
ReadMatBin(cnn_stream, weights);
cnn_fully_connected_layers_weights.push_back(weights);
cnn_fully_connected_layers_weights.push_back(weights.t());
}
else if (layer_type == 3)