// ./Sp_demo_for_direc.py -d <directory_name> -i_std ... -n... --imgs_of_the_same_size
int main( int argc, char** argv )
{
// get the image filename, nPixels_in_square_side and i_std
// the defaults
const char* direc = "image/";
int nPixels_in_square_side = 15;
int i_std = 20;
bool same_size = false;
for (int i = 1; i < argc; ++i) {
std::string arg = argv[i];
if ((arg == "-h") || (arg == "--help")) {
show_usage(argv[0]);
return 0;
}
else if ((arg == "-d") || (arg == "--image_direc")) {
if (i + 1 < argc) {
i++;
direc = argv[i];
} else {
std::cerr << "--img_filename option requires one argument." << std::endl;
return 1;
}
}
else if ((arg == "-n") || (arg == "--nPixels_on_side")) {
if (i + 1 < argc) {
i++;
nPixels_in_square_side = atoi (argv[i]);
if (nPixels_in_square_side<3) {
std::cerr << "--nPixels_in_square_side option requires nPixels_in_square_side >= 3." << std::endl;
return 1;
}
} else {
std::cerr << "--nPixels_on_side option requires one argument." << std::endl;
return 1;
}
}
else if (arg == "--i_std") {
if (i + 1 < argc) {
i++;
i_std = atoi (argv[i]);
if (i_std<5 || i_std>40) {
std::cerr << "--i_std option requires 5<= value <=40." << std::endl;
return 1;
}
} else {
std::cerr << "--i_std option requires a number." << std::endl;
return 1;
}
}else{
}
}
DIR *dpdf;
struct dirent *epdf;
superpixel_options spoptions = get_sp_options(nPixels_in_square_side,i_std);
int count = 0;
//Superpixels sp = Superpixels(0,0,spoptions);
dpdf = opendir(direc);
if (dpdf != NULL){
while (epdf = readdir(dpdf)){
String img_name = epdf->d_name;
String filename = string(direc) + img_name;
Mat image = imread(filename, CV_LOAD_IMAGE_COLOR);
if(! image.data )continue;
cout << "Filename: " << filename <<endl;
Superpixels sp = Superpixels(image.cols, image.rows, spoptions);
cudaDeviceSynchronize();
//cout << "finish init sp" << endl;
sp.load_img((unsigned char*)(image.data));
//cout << "finish loading the image" << endl;
// Part 3: Do the superpixel segmentation
clock_t start,finish;
start = clock();
sp.calc_seg();
cudaDeviceSynchronize();
sp.gpu2cpu();
finish = clock();
cout<< "Segmentation takes " << ((double)(finish-start)/CLOCKS_PER_SEC) << " sec" << endl;
// Part 4: Save the mean/boundary image
cudaError_t err_t = cudaDeviceSynchronize();
if (err_t){
std::cerr << "CUDA error after cudaDeviceSynchronize." << std::endl;
return 0;
}
String img_number = img_name.substr (0, img_name.find("."));
Mat border_img = sp.get_img_overlaid();
String fname_res_border = "image/result/"+img_number+"_border.png";
imwrite(fname_res_border, border_img);
cout << "saving " << fname_res_border << endl;
Mat mean_img = sp.get_img_cartoon();
String fname_res_mean = "image/result/"+img_number+"_mean.png";
imwrite(fname_res_mean, mean_img);
cout << "saving " << fname_res_mean << endl << endl;
count++;
}
}
return 0;
}
//./Sp_demo -i <img_filename> -n <nPixels_on_side> --i_std <i_std>
int main( int argc, char** argv )
{
// get the image filename, nPixels_in_square_side and i_std
// the defaults
String filename = "image/2.jpg";
int nPixels_in_square_side = 15;
int i_std = 20;
for (int i = 1; i < argc; ++i) {
std::string arg = argv[i];
if ((arg == "-h") || (arg == "--help")) {
show_usage(argv[0]);
return 0;
}
else if ((arg == "-i") || (arg == "--img_filename")) {
if (i + 1 < argc) {
i++;
filename = argv[i];
} else {
std::cerr << "--img_filename option requires one argument." << std::endl;
return 1;
}
}
else if ((arg == "-n") || (arg == "--nPixels_on_side")) {
if (i + 1 < argc) {
i++;
nPixels_in_square_side = atoi (argv[i]);
if (nPixels_in_square_side<3) {
std::cerr << "--nPixels_in_square_side option requires nPixels_in_square_side >= 3." << std::endl;
return 1;
}
} else {
std::cerr << "--nPixels_on_side option requires one argument." << std::endl;
return 1;
}
}
else if (arg == "--i_std") {
if (i + 1 < argc) {
i++;
i_std = atoi (argv[i]);
if (i_std<5 || i_std>40) {
std::cerr << "--i_std option requires 5<= value <=40." << std::endl;
return 1;
}
} else {
std::cerr << "--i_std option requires a number." << std::endl;
return 1;
}
}else{
}
}
cout << "finish reading the arguments" << endl;
Mat image = imread(filename, CV_LOAD_IMAGE_COLOR);
// Check for invalid input
if(! image.data ){
cout << "Could not open or find the image" << std::endl ;
return -1;
}
cout << "finish reading the image" << endl;
//Part 1: Specify the parameters:
superpixel_options spoptions = get_sp_options(nPixels_in_square_side, i_std);
// Part 2 : prepare for segmentation
int dimy = image.rows;
int dimx = image.cols;
Superpixels sp = Superpixels(dimx, dimy, spoptions);
//cout << "finish init sp" << endl;
cudaDeviceSynchronize();
sp.load_img((unsigned char*)(image.data));
//cout << "finish loading the image" << endl;
// Part 3: Do the superpixel segmentation
clock_t start,finish;
start = clock();
sp.calc_seg();
cudaDeviceSynchronize();
sp.gpu2cpu();
cudaError_t err_t = cudaDeviceSynchronize();
if (err_t){
std::cerr << "CUDA error after cudaDeviceSynchronize. " << std::endl;
return 0;
}
finish = clock();
cout<< "Segmentation takes " << ((double)(finish-start)/CLOCKS_PER_SEC) << " sec" << endl;
// Part 4: Save the mean/boundary image
Mat border_img = sp.get_img_overlaid();
String fname_res_border = "image/result/img_border.png";
imwrite(fname_res_border, border_img);
cout << "saved " << fname_res_border << endl;
Mat mean_img = sp.get_img_cartoon();
String fname_res_mean = "image/result/img_mean.png";
imwrite(fname_res_mean, mean_img);
cout << "saving " << fname_res_mean << endl;
return 0;
}
