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Add sample code to compare the results across the different auto Gamm…
…a methods.
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tutorial/imgproc/brightness/tutorial-compare-auto-gamma.cpp
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//! \example tutorial-compare-auto-gamma | ||
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#include <iostream> | ||
#include <visp3/core/vpConfig.h> | ||
#include <visp3/core/vpImage.h> | ||
#include <visp3/core/vpIoTools.h> | ||
#include <visp3/core/vpImageTools.h> | ||
#include <visp3/core/vpCannyEdgeDetection.h> | ||
#include <visp3/core/vpImageFilter.h> | ||
#include <visp3/core/vpFont.h> | ||
#include <visp3/io/vpImageIo.h> | ||
#include <visp3/io/vpVideoReader.h> | ||
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// VISP_HAVE_SIMDLIB is required for INTERPOLATION_AREA | ||
#if defined(VISP_HAVE_MODULE_IMGPROC) && defined(VISP_HAVE_SIMDLIB) && \ | ||
((__cplusplus >= 201103L) || (defined(_MSVC_LANG) && (_MSVC_LANG >= 201103L))) | ||
#include <visp3/imgproc/vpImgproc.h> | ||
#include <memory> | ||
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#ifdef ENABLE_VISP_NAMESPACE | ||
using namespace VISP_NAMESPACE_NAME; | ||
#endif | ||
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namespace | ||
{ | ||
template <class T> | ||
void computeMeanMaxStdev(const vpImage<T> &I, float &mean, float &max, float &stdev) | ||
{ | ||
max = std::numeric_limits<float>::epsilon(); | ||
mean = 0.; | ||
stdev = 0.; | ||
unsigned int nbRows = I.getRows(); | ||
unsigned int nbCols = I.getCols(); | ||
float scale = 1.f / (static_cast<float>(nbRows) * static_cast<float>(nbCols)); | ||
for (unsigned int r = 0; r < nbRows; r++) { | ||
for (unsigned int c = 0; c < nbCols; c++) { | ||
mean += I[r][c]; | ||
max = std::max<float>(max, static_cast<float>(I[r][c])); | ||
} | ||
} | ||
mean *= scale; | ||
for (unsigned int r = 0; r < nbRows; r++) { | ||
for (unsigned int c = 0; c < nbCols; c++) { | ||
stdev += (I[r][c] - mean) * (I[r][c] - mean); | ||
} | ||
} | ||
stdev *= scale; | ||
stdev = std::sqrt(stdev); | ||
} | ||
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void computeCanny(const vpImage<unsigned char> &I, vpCannyEdgeDetection &cannyDetector, int gaussianKernelSize, | ||
float gaussianStdev, int apertureSize, vpImageFilter::vpCannyFilteringAndGradientType filteringType, | ||
vpImage<unsigned char> &dIxy_uchar, vpImage<unsigned char> &I_canny_visp) | ||
{ | ||
vpImage<float> dIx, dIy, dIxy(I.getHeight(), I.getWidth()); | ||
vpImageFilter::computePartialDerivatives(I, dIx, dIy, true, true, true, gaussianKernelSize, gaussianStdev, | ||
apertureSize, filteringType); | ||
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for (unsigned int i = 0; i < dIx.getHeight(); i++) { | ||
for (unsigned int j = 0; j < dIx.getWidth(); j++) { | ||
dIxy[i][j] = std::sqrt(dIx[i][j]*dIx[i][j] + dIy[i][j]*dIy[i][j]); | ||
} | ||
} | ||
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float mean, max, stdev; | ||
computeMeanMaxStdev(dIxy, mean, max, stdev); | ||
vpImageConvert::convert(dIx, dIxy_uchar); | ||
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// Set the gradients of the vpCannyEdgeDetection | ||
cannyDetector.setGradients(dIx, dIy); | ||
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I_canny_visp = cannyDetector.detect(I); | ||
} | ||
} // namespace | ||
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int main(int argc, const char **argv) | ||
{ | ||
std::string input = "Sample_low_brightness.png"; | ||
std::string output = "Results"; | ||
int gaussianKernelSize = 3; | ||
float gaussianStdev = 1.; | ||
int apertureSize = 3; | ||
bool half = false; | ||
vpImageFilter::vpCannyFilteringAndGradientType filteringType = vpImageFilter::CANNY_GBLUR_SOBEL_FILTERING; | ||
VISP_NAMESPACE_NAME::vpGammaColorHandling gamma_colorspace = VISP_NAMESPACE_NAME::GAMMA_HSV; | ||
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for (int i = 1; i < argc; i++) { | ||
if (std::string(argv[i]) == "--input" && i + 1 < argc) { | ||
++i; | ||
input = std::string(argv[i]); | ||
} | ||
else if (std::string(argv[i]) == "--half") { | ||
half = true; | ||
} | ||
else if (std::string(argv[i]) == "--gaussian-kernel-size" && i + 1 < argc) { | ||
++i; | ||
gaussianKernelSize = std::atoi(argv[i]); | ||
} | ||
else if (std::string(argv[i]) == "--gaussian-std" && i + 1 < argc) { | ||
++i; | ||
gaussianStdev = std::atof(argv[i]); | ||
} | ||
else if (std::string(argv[i]) == "--aperture-size" && i + 1 < argc) { | ||
++i; | ||
apertureSize = std::atoi(argv[i]); | ||
} | ||
else if (std::string(argv[i]) == "--canny-filtering-type" && i + 1 < argc) { | ||
++i; | ||
int type = std::atoi(argv[i]); | ||
if (type == 1) { | ||
filteringType = vpImageFilter::CANNY_GBLUR_SCHARR_FILTERING; | ||
} | ||
} | ||
else if (std::string(argv[i]) == "--gamma-rgb") { | ||
gamma_colorspace = VISP_NAMESPACE_NAME::GAMMA_RGB; | ||
} | ||
else if (std::string(argv[i]) == "--output" && i + 1 < argc) { | ||
++i; | ||
output = std::string(argv[i]); | ||
} | ||
else { | ||
std::cout << "Usage: " << argv[0] | ||
<< " [--input <input path or image sequence pattern>]" | ||
" [--half (use half image resolution)]" | ||
" [--gaussian-kernel-size <e.g. 3, 5, 7>]" | ||
" [--gaussian-std <e.g. 1>]" | ||
" [--aperture-size <e.g. 3>]" | ||
" [--canny-filtering-type <0=CANNY_GBLUR_SOBEL_FILTERING, 1=CANNY_GBLUR_SCHARR_FILTERING>]" | ||
" [--gamma-rgb (RGB colorspace, else HSV]" | ||
" [--output <folder path> (to save results)]" | ||
<< std::endl; | ||
return EXIT_SUCCESS; | ||
} | ||
} | ||
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std::cout << "Input: " << input << std::endl; | ||
std::cout << "Process on half image resolution? " << half << std::endl; | ||
std::cout << "Gaussian kernel size: " << gaussianKernelSize << std::endl; | ||
std::cout << "Gaussian standard deviation: " << gaussianStdev << std::endl; | ||
std::cout << "Aperture size: " << apertureSize << std::endl; | ||
std::cout << "Canny filtering type: " << filteringType << std::endl; | ||
std::cout << "RGB colorspace? " << (gamma_colorspace == VISP_NAMESPACE_NAME::GAMMA_RGB) << std::endl; | ||
std::cout << "Output result folder: " << output << std::endl; | ||
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// Canny parameters | ||
float lowerThresh = -1.; | ||
float upperThresh = -1.; | ||
float lowerThreshRatio = 0.6f; | ||
float upperThreshRatio = 0.8f; | ||
vpCannyEdgeDetection cannyDetector(gaussianKernelSize, gaussianStdev, apertureSize, | ||
lowerThresh, upperThresh, lowerThreshRatio, upperThreshRatio, | ||
filteringType); | ||
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bool single_image = vpIoTools::checkFilename(input); | ||
vpVideoReader reader; | ||
vpImage<vpRGBa> I_color_ori, I_color; | ||
if (single_image) { | ||
vpImageIo::read(I_color_ori, input); | ||
} | ||
else { | ||
reader.setFileName(input); | ||
reader.open(I_color_ori); | ||
} | ||
if (half) { | ||
vpImageTools::resize(I_color_ori, I_color, I_color_ori.getWidth()/2, I_color_ori.getHeight()/2, | ||
vpImageTools::INTERPOLATION_AREA); | ||
} | ||
else { | ||
I_color = I_color_ori; | ||
} | ||
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vpIoTools::makeDirectory(output); | ||
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vpImage<vpRGBa> I_color_gamma_correction, I_res_stack; | ||
vpImage<unsigned char> I_gray_gamma_correction, dIxy_uchar, I_canny_visp; | ||
vpImage<vpRGBa> dIxy_uchar_color, I_canny_visp_color; | ||
vpFont font(32); | ||
bool read_single_image = false; | ||
while (!read_single_image && (single_image || !reader.end())) { | ||
if (!single_image) { | ||
reader.acquire(I_color_ori); | ||
} | ||
if (half) { | ||
vpImageTools::resize(I_color_ori, I_color, I_color_ori.getWidth()/2, I_color_ori.getHeight()/2, | ||
vpImageTools::INTERPOLATION_AREA); | ||
} | ||
else { | ||
I_color = I_color_ori; | ||
} | ||
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const int nb_methods = VISP_NAMESPACE_NAME::GAMMA_METHOD_COUNT - 1; // all except GAMMA_MANUAL | ||
I_res_stack.init(nb_methods*I_color.getHeight(), 4*I_color.getWidth()); | ||
dIxy_uchar.init(I_color.getHeight(), I_color.getWidth()); | ||
I_canny_visp.init(I_color.getHeight(), I_color.getWidth()); | ||
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// Output results | ||
int offset_text_start_y = 25; | ||
int text_h = 40; | ||
int offset_idx = 0; | ||
double start_time = 0, end_time = 0; | ||
char buffer[FILENAME_MAX]; | ||
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for (int gamma_idx = 1; gamma_idx < VISP_NAMESPACE_NAME::GAMMA_METHOD_COUNT; ++gamma_idx, offset_idx++) { | ||
VISP_NAMESPACE_NAME::vpGammaMethod gamma_method = static_cast<VISP_NAMESPACE_NAME::vpGammaMethod>(gamma_idx); | ||
if (gamma_method == VISP_NAMESPACE_NAME::GAMMA_MANUAL) { | ||
continue; | ||
} | ||
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const double gamma = -1; | ||
start_time = vpTime::measureTimeMs(); | ||
VISP_NAMESPACE_NAME::gammaCorrection(I_color, I_color_gamma_correction, static_cast<float>(gamma), | ||
gamma_colorspace, gamma_method); | ||
end_time = vpTime::measureTimeMs(); | ||
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vpImageConvert::convert(I_color_gamma_correction, I_gray_gamma_correction); | ||
computeCanny(I_gray_gamma_correction, cannyDetector, gaussianKernelSize, gaussianStdev, apertureSize, | ||
filteringType, dIxy_uchar, I_canny_visp); | ||
vpImageConvert::convert(dIxy_uchar, dIxy_uchar_color); | ||
vpImageConvert::convert(I_canny_visp, I_canny_visp_color); | ||
I_res_stack.insert(I_color, vpImagePoint(offset_idx*I_color.getHeight(), 0)); | ||
I_res_stack.insert(I_color_gamma_correction, vpImagePoint(offset_idx*I_color.getHeight(), I_color.getWidth())); | ||
I_res_stack.insert(I_canny_visp_color, vpImagePoint(offset_idx*I_color.getHeight(), 2*I_color.getWidth())); | ||
I_res_stack.insert(dIxy_uchar_color, vpImagePoint(offset_idx*I_color.getHeight(), 3*I_color.getWidth())); | ||
std::ostringstream oss; | ||
oss << VISP_NAMESPACE_NAME::vpGammaMethodToString(gamma_method) << " (%.2f ms)"; | ||
snprintf(buffer, FILENAME_MAX, oss.str().c_str(), (end_time-start_time)); | ||
font.drawText(I_res_stack, buffer, vpImagePoint(offset_idx*I_color.getHeight() + offset_text_start_y, | ||
0.35*I_res_stack.getWidth()), vpColor::red); | ||
snprintf(buffer, FILENAME_MAX, "Canny mean: (%.2f)", I_canny_visp.getMeanValue()); | ||
font.drawText(I_res_stack, buffer, vpImagePoint(offset_idx*I_color.getHeight() + offset_text_start_y+text_h, | ||
0.35*I_res_stack.getWidth()), vpColor::red); | ||
} | ||
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if (!output.empty()) { | ||
std::stringstream output_filename; | ||
if (single_image) { | ||
output_filename << vpIoTools::createFilePath(output, vpIoTools::getNameWE(input)) << ".png"; | ||
} | ||
else { | ||
output_filename << vpIoTools::createFilePath(output, vpIoTools::getNameWE(reader.getFrameName())) << ".png"; | ||
} | ||
std::cout << "Write result to: " << output_filename.str() << std::endl; | ||
vpImageIo::write(I_res_stack, output_filename.str()); | ||
} | ||
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if (single_image) { | ||
read_single_image = true; | ||
} | ||
} | ||
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return EXIT_SUCCESS; | ||
} | ||
#else | ||
int main() | ||
{ | ||
std::cerr << "C++11 is required." << std::endl; | ||
return EXIT_SUCCESS; | ||
} | ||
#endif |