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Removing some un-needed includes and removing some warnings.

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This commit is contained in:
Tadas Baltrusaitis
2018-05-08 17:49:46 +01:00
parent 0a3b740591
commit 74f42ed41a
10 changed files with 60 additions and 68 deletions
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4
lib/3rdParty/dlib/include/dlib/matrix/matrix_trsm.h vendored
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@@ -12,13 +12,13 @@ namespace dlib
#ifndef CBLAS_H
extern "C"
{
void cblas_strsmFIX(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side,
void cblas_strsm(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side,
const enum CBLAS_UPLO Uplo, const enum CBLAS_TRANSPOSE TransA,
const enum CBLAS_DIAG Diag, const int M, const int N,
const float alpha, const float *A, const int lda,
float *B, const int ldb);
void cblas_dtrsmFIX(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side,
void cblas_dtrsm(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side,
const enum CBLAS_UPLO Uplo, const enum CBLAS_TRANSPOSE TransA,
const enum CBLAS_DIAG Diag, const int M, const int N,
const double alpha, const double *A, const int lda,

2
lib/local/FaceAnalyser/include/FaceAnalyserParameters.h
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@@ -69,7 +69,7 @@ public:
void OptimizeForVideos();
void OptimizeForImages();
double getAlignMask() const { return sim_align_face_mask; }
bool getAlignMask() const { return sim_align_face_mask; }
double getSimScaleOut() const { return sim_scale_out; }
int getSimSizeOut() const { return sim_size_out; }
bool getDynamic() const { return dynamic; }

4
lib/local/FaceAnalyser/include/Face_utils.h
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@@ -47,8 +47,8 @@ namespace FaceAnalysis
// Defining a set of useful utility functions to be used within FaceAnalyser
// Aligning a face to a common reference frame
void AlignFace(cv::Mat& aligned_face, const cv::Mat& frame, const cv::Mat_<float>& detected_landmarks, cv::Vec6f params_global, const LandmarkDetector::PDM& pdm, bool rigid = true, float scale = 0.6, int width = 96, int height = 96);
void AlignFaceMask(cv::Mat& aligned_face, const cv::Mat& frame, const cv::Mat_<float>& detected_landmarks, cv::Vec6f params_global, const LandmarkDetector::PDM& pdm, const cv::Mat_<int>& triangulation, bool rigid = true, float scale = 0.6, int width = 96, int height = 96);
void AlignFace(cv::Mat& aligned_face, const cv::Mat& frame, const cv::Mat_<float>& detected_landmarks, cv::Vec6f params_global, const LandmarkDetector::PDM& pdm, bool rigid = true, double scale = 0.7, int width = 96, int height = 96);
void AlignFaceMask(cv::Mat& aligned_face, const cv::Mat& frame, const cv::Mat_<float>& detected_landmarks, cv::Vec6f params_global, const LandmarkDetector::PDM& pdm, const cv::Mat_<int>& triangulation, bool rigid = true, double scale = 0.7, int width = 96, int height = 96);
void Extract_FHOG_descriptor(cv::Mat_<double>& descriptor, const cv::Mat& image, int& num_rows, int& num_cols, int cell_size = 8);

2
lib/local/FaceAnalyser/src/FaceAnalyser.cpp
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@@ -242,7 +242,7 @@ int GetViewId(const vector<cv::Vec3d> orientations_all, const cv::Vec3d& orienta
if(i == 0 || d < dbest)
{
dbest = d;
id = i;
id = (int) i;
}
}
return id;

4
lib/local/FaceAnalyser/src/Face_utils.cpp
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@@ -114,7 +114,7 @@ namespace FaceAnalysis
}
// Aligning a face to a common reference frame
void AlignFace(cv::Mat& aligned_face, const cv::Mat& frame, const cv::Mat_<float>& detected_landmarks, cv::Vec6f params_global, const LandmarkDetector::PDM& pdm, bool rigid, float sim_scale, int out_width, int out_height)
void AlignFace(cv::Mat& aligned_face, const cv::Mat& frame, const cv::Mat_<float>& detected_landmarks, cv::Vec6f params_global, const LandmarkDetector::PDM& pdm, bool rigid, double sim_scale, int out_width, int out_height)
{
// Will warp to scaled mean shape
cv::Mat_<float> similarity_normalised_shape = pdm.mean_shape * sim_scale;
@@ -153,7 +153,7 @@ namespace FaceAnalysis
}
// Aligning a face to a common reference frame
void AlignFaceMask(cv::Mat& aligned_face, const cv::Mat& frame, const cv::Mat_<float>& detected_landmarks, cv::Vec6f params_global, const LandmarkDetector::PDM& pdm, const cv::Mat_<int>& triangulation, bool rigid, float sim_scale, int out_width, int out_height)
void AlignFaceMask(cv::Mat& aligned_face, const cv::Mat& frame, const cv::Mat_<float>& detected_landmarks, cv::Vec6f params_global, const LandmarkDetector::PDM& pdm, const cv::Mat_<int>& triangulation, bool rigid, double sim_scale, int out_width, int out_height)
{
// Will warp to scaled mean shape
cv::Mat_<float> similarity_normalised_shape = pdm.mean_shape * sim_scale;

4
lib/local/LandmarkDetector/include/stdafx.h
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@@ -23,10 +23,6 @@
#include <opencv2/imgcodecs.hpp>
#include <opencv2/highgui/highgui.hpp>
// IplImage stuff
#include <opencv2/core/core_c.h>
#include <opencv2/imgproc/imgproc_c.h>
// C++ stuff
#include <stdio.h>

6
lib/local/LandmarkDetector/src/CCNF_patch_expert.cpp
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@@ -157,9 +157,9 @@ void im2colContrastNormBias(const cv::Mat_<float>& input, const unsigned int wid
// Iterate over the blocks
unsigned int rowIdx = 0;
for (int j = 0; j< xB; j++)
for (unsigned int j = 0; j< xB; j++)
{
for (int i = 0; i< yB; i++)
for (unsigned int i = 0; i< yB; i++)
{
float* Mo = output.ptr<float>(rowIdx);
@@ -171,7 +171,7 @@ void im2colContrastNormBias(const cv::Mat_<float>& input, const unsigned int wid
const float* Mi = input.ptr<float>(i + yy);
for (unsigned int xx = 0; xx < width; ++xx)
{
int colIdx = xx*height + yy;
unsigned int colIdx = xx*height + yy;
float in = Mi[j + xx];
sum += in;

90
lib/local/LandmarkDetector/src/CNN_utils.cpp
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@@ -50,18 +50,18 @@ namespace LandmarkDetector
if (input_output_maps.size() > 1)
{
int h = input_output_maps[0].rows;
int w = input_output_maps[0].cols;
size_t size_in = h * w;
unsigned int h = input_output_maps[0].rows;
unsigned int w = input_output_maps[0].cols;
unsigned int size_in = h * w;
for (size_t k = 0; k < input_output_maps.size(); ++k)
for (int k = 0; k < (int) input_output_maps.size(); ++k)
{
// Apply the PReLU
auto iter = input_output_maps[k].begin();
float neg_mult = prelu_weights.at<float>(k);
for (size_t i = 0; i < size_in; ++i)
for (unsigned int i = 0; i < size_in; ++i)
{
float in_val = *iter;
@@ -76,7 +76,7 @@ namespace LandmarkDetector
int w = input_output_maps[0].cols;
for (size_t k = 0; k < prelu_weights.rows; ++k)
for (int k = 0; k < prelu_weights.rows; ++k)
{
auto iter = input_output_maps[0].row(k).begin();
float neg_mult = prelu_weights.at<float>(k);
@@ -107,9 +107,9 @@ namespace LandmarkDetector
{
// Concatenate all the maps
cv::Size orig_size = input_maps[0].size();
cv::Mat_<float> input_concat(input_maps.size(), input_maps[0].cols * input_maps[0].rows);
cv::Mat_<float> input_concat((int)input_maps.size(), input_maps[0].cols * input_maps[0].rows);
for (size_t in = 0; in < input_maps.size(); ++in)
for (int in = 0; in < input_maps.size(); ++in)
{
cv::Mat_<float> add = input_maps[in];
@@ -128,14 +128,14 @@ namespace LandmarkDetector
{
input_concat = weights * input_concat;
// Add biases
for (size_t k = 0; k < biases.rows; ++k)
for (int k = 0; k < biases.rows; ++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)
for (int k = 0; k < biases.rows; ++k)
{
cv::Mat_<float> reshaped = input_concat.row(k).clone();
reshaped = reshaped.reshape(1, orig_size.height);
@@ -172,8 +172,8 @@ namespace LandmarkDetector
for (size_t in = 0; in < input_maps.size(); ++in)
{
// Help with rounding up a bit, to match caffe style output
int out_x = round((float)(input_maps[in].cols - kernel_size_x) / (float)stride_x) + 1;
int out_y = round((float)(input_maps[in].rows - kernel_size_y) / (float)stride_y) + 1;
int out_x = (int)round((float)(input_maps[in].cols - kernel_size_x) / (float)stride_x) + 1;
int out_y = (int)round((float)(input_maps[in].rows - kernel_size_y) / (float)stride_y) + 1;
cv::Mat_<float> sub_out(out_y, out_x, 0.0);
cv::Mat_<float> in_map = input_maps[in];
@@ -360,15 +360,15 @@ namespace LandmarkDetector
}
}
void im2col_t(const cv::Mat_<float>& input, int width, int height, cv::Mat_<float>& output)
void im2col_t(const cv::Mat_<float>& input, const unsigned int width, const unsigned int height, cv::Mat_<float>& output)
{
int m = input.cols;
int n = input.rows;
const unsigned int m = input.cols;
const unsigned int n = input.rows;
// determine how many blocks there will be with a sliding window of width x height in the input
int yB = m - height + 1;
int xB = n - width + 1;
const unsigned int yB = m - height + 1;
const unsigned int xB = n - width + 1;
// Allocate the output size
if (output.rows != width * height || output.cols != xB*yB)
@@ -377,10 +377,10 @@ namespace LandmarkDetector
}
// Iterate over the whole image
for (int i = 0; i< yB; i++)
for (unsigned int i = 0; i< yB; i++)
{
int rowIdx = i;
for (int j = 0; j< xB; j++)
unsigned int rowIdx = i;
for (unsigned int j = 0; j< xB; j++)
{
//int rowIdx = i; +j*yB;
// iterate over the blocks within the image
@@ -390,7 +390,7 @@ namespace LandmarkDetector
const float* Mi = input.ptr<float>(j + yy);
for (unsigned int xx = 0; xx < width; ++xx)
{
int colIdx = xx*height + yy;
unsigned int colIdx = xx*height + yy;
output.at<float>(colIdx, rowIdx) = Mi[i + xx];
}
@@ -413,10 +413,10 @@ namespace LandmarkDetector
int yB = height_in - height_k + 1;
int xB = width_n - width_k + 1;
cv::Mat_<float> input_matrix(input_maps.size() * height_k * width_k + 1.0, yB * xB, 1.0f);
cv::Mat_<float> input_matrix((int)input_maps.size() * height_k * width_k + 1, yB * xB, 1.0f);
// Comibine im2col accross channels to prepare for matrix multiplication
for (size_t i = 0; i < input_maps.size(); ++i)
for (int i = 0; i < (int)input_maps.size(); ++i)
{
cv::Mat_<float> tmp = input_matrix(cv::Rect(0, i * height_k * width_k, yB * xB, height_k * width_k));
im2col_t(input_maps[i], width_k, height_k, tmp);
@@ -431,22 +431,22 @@ namespace LandmarkDetector
cblas_sgemm(CblasColMajor, CblasNoTrans, CblasNoTrans, input_matrix.cols, weight_matrix.rows, weight_matrix.cols, 1, m2, input_matrix.cols, m1, weight_matrix.cols, 0.0, m3, input_matrix.cols);
// Move back to vectors and reshape accordingly (also add the bias)
for (size_t k = 0; k < out.rows; ++k)
for (int k = 0; k < out.rows; ++k)
{
outputs.push_back(out.row(k).reshape(1, yB));
}
}
void im2col(const cv::Mat_<float>& input, int width, int height, cv::Mat_<float>& output)
void im2col(const cv::Mat_<float>& input, const unsigned int width, const unsigned int height, cv::Mat_<float>& output)
{
int m = input.rows;
int n = input.cols;
const unsigned int m = input.rows;
const unsigned int n = input.cols;
// determine how many blocks there will be with a sliding window of width x height in the input
int yB = m - height + 1;
int xB = n - width + 1;
const unsigned int yB = m - height + 1;
const unsigned int xB = n - width + 1;
// Allocate the output size
if (output.cols != width * height || output.rows != xB*yB)
@@ -455,10 +455,10 @@ namespace LandmarkDetector
}
// Iterate over the whole image
for (int i = 0; i< yB; i++)
for (unsigned int i = 0; i< yB; i++)
{
int rowIdx = i*xB;
for (int j = 0; j< xB; j++)
unsigned int rowIdx = i*xB;
for (unsigned int j = 0; j< xB; j++)
{
float* Mo = output.ptr<float>(rowIdx);
@@ -471,7 +471,7 @@ namespace LandmarkDetector
for (unsigned int xx = 0; xx < width; ++xx)
{
int colIdx = xx*height + yy;
unsigned int colIdx = xx*height + yy;
//output.at<float>(rowIdx, colIdx) = Mi[j + xx]; //input.at<float>(i + yy, j + xx);
Mo[colIdx] = Mi[j + xx];
}
@@ -482,31 +482,31 @@ namespace LandmarkDetector
}
}
void im2col_multimap(const vector<cv::Mat_<float> >& inputs, int width, int height, cv::Mat_<float>& output)
void im2col_multimap(const vector<cv::Mat_<float> >& inputs, const unsigned int width, const unsigned int height, cv::Mat_<float>& output)
{
int m = inputs[0].rows;
int n = inputs[0].cols;
const unsigned int m = inputs[0].rows;
const unsigned int n = inputs[0].cols;
// determine how many blocks there will be with a sliding window of width x height in the input
int yB = m - height + 1;
int xB = n - width + 1;
const unsigned int yB = m - height + 1;
const unsigned int xB = n - width + 1;
int stride = height * width;
size_t num_maps = inputs.size();
unsigned int num_maps = (unsigned int)inputs.size();
// Allocate the output size
if (output.cols != width * height * inputs.size() + 1 || output.rows < xB*yB)
if (output.cols != width * height * inputs.size() + 1 || (unsigned int) output.rows < xB*yB)
{
output = cv::Mat::ones(xB*yB, width * height * num_maps + 1, CV_32F);
}
// Iterate over the whole image
for (int i = 0; i< yB; i++)
for (unsigned int i = 0; i< yB; i++)
{
int rowIdx = i*xB;
for (int j = 0; j< xB; j++)
unsigned int rowIdx = i*xB;
for (unsigned int j = 0; j< xB; j++)
{
float* Mo = output.ptr<float>(rowIdx);
@@ -523,7 +523,7 @@ namespace LandmarkDetector
for (unsigned int xx = 0; xx < width; ++xx)
{
int colIdx = xx*height + yy + in_maps * stride;
unsigned int colIdx = xx*height + yy + in_maps * stride;
//output.at<float>(rowIdx, colIdx) = Mi[j + xx]; //input.at<float>(i + yy, j + xx);
Mo[colIdx] = Mi[j + xx];
}
@@ -570,7 +570,7 @@ namespace LandmarkDetector
out = out.t();
// Move back to vectors and reshape accordingly
for (size_t k = 0; k < out.rows; ++k)
for (int k = 0; k < out.rows; ++k)
{
outputs.push_back(out.row(k).reshape(1, yB));
}

4
lib/local/LandmarkDetector/src/Patch_experts.cpp
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@@ -36,10 +36,6 @@
#include "Patch_experts.h"
// OpenCV includes
#include <opencv2/core/core_c.h>
#include <opencv2/imgproc/imgproc_c.h>
// TBB includes
#include <tbb/tbb.h>

8
lib/local/Utilities/src/Visualizer.cpp
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@@ -256,7 +256,7 @@ void Visualizer::SetObservationActionUnits(const std::vector<std::pair<std::stri
const int MARGIN_X = 185;
const int MARGIN_Y = 10;
const int nb_aus = au_names.size();
const int nb_aus = (int) au_names.size();
// Do not reinitialize
if (action_units_image.empty())
@@ -299,14 +299,14 @@ void Visualizer::SetObservationActionUnits(const std::vector<std::pair<std::stri
}
// then, build the graph
size_t idx = 0;
unsigned int idx = 0;
for (auto& au : aus)
{
std::string name = au.first;
bool present = au.second.first;
double intensity = au.second.second;
auto offset = MARGIN_Y + idx * (AU_TRACKBAR_HEIGHT + 10);
int offset = MARGIN_Y + idx * (AU_TRACKBAR_HEIGHT + 10);
std::ostringstream au_i;
au_i << std::setprecision(2) << std::setw(4) << std::fixed << intensity;
cv::putText(action_units_image, name, cv::Point(10, offset + 10), CV_FONT_HERSHEY_SIMPLEX, 0.5, CV_RGB(present ? 0 : 200, 0, 0), 1, CV_AA);
@@ -316,7 +316,7 @@ void Visualizer::SetObservationActionUnits(const std::vector<std::pair<std::stri
{
cv::putText(action_units_image, au_i.str(), cv::Point(160, offset + 10), CV_FONT_HERSHEY_SIMPLEX, 0.3, CV_RGB(0, 100, 0), 1, CV_AA);
cv::rectangle(action_units_image, cv::Point(MARGIN_X, offset),
cv::Point(MARGIN_X + AU_TRACKBAR_LENGTH * intensity / 5, offset + AU_TRACKBAR_HEIGHT),
cv::Point((int)(MARGIN_X + AU_TRACKBAR_LENGTH * intensity / 5.0), offset + AU_TRACKBAR_HEIGHT),
cv::Scalar(128, 128, 128),
CV_FILLED);
}