std::vector< Vec4i > get_v_lines(Mat& img)
{
int h = img.rows;
int w = img.cols;
std::vector< Vec4i > lines;
unsigned int length_th = 200;
for (int y = 0; y<h; y++)
{
int x1 = 0;
int x2 = 0;
int in_row = 0;
Vec4i longest_line(0, 0, 0, 0);
for (int x = 0; x<w; x++)
{
if (img.at<unsigned char>(y, x) < 140)
{
if (in_row == 0)
x1 = x;
in_row += 1;
}
else
{
if (in_row > length_th)
lines.push_back(Vec4i(x1, y, x, y));
in_row = 0;
}
}
if (in_row > length_th)
lines.push_back(Vec4i(x1, y, w - 1, y));
}
return lines;
}
/* This function calls "add_line_to_node" for each line of the vocab file. */
int add_line(vocab_t **listavocab, FILE *archivo, int cat) {
char *buffer;
int num_nodes = 0;
unsigned short learning = 0;
char tipo;
buffer = (char *)calloc(longest_line(archivo)+1,sizeof(char));
rewind(archivo);
while (fscanf(archivo,"%c", &tipo) != EOF) {
// It's a word.
if (tipo == '&') {
if (fscanf(archivo,"%hu %*c %[^\n] %*[\n]",&learning, buffer) != EOF) {
if (add_line_to_node(listavocab,buffer, true, cat, learning))
num_nodes++;
}
// It's a category.
} else if (tipo == ';') {
if (fscanf(archivo," %*c %[^\n] %*[\n]", buffer) != EOF) {
if (add_line_to_node(listavocab,buffer,false, cat, learning))
num_nodes++;
}
}
}
if (buffer) {
free(buffer);
buffer = NULL;
}
return num_nodes;
}
std::vector< Vec4i > get_h_lines(Mat& img)
{
int h = img.rows;
int w = img.cols;
std::vector< Vec4i > lines;
int length_th = 100;
for (int x = 0; x<w; x++)
{
int y1 = 0;
int in_row = 0;
int longest = 0;
Vec4i longest_line(0, 0, 0, 0);
for (int y = 0; y<h; y++)
{
if (img.at<unsigned char>(y, x) < 140)
{
if (in_row == 0)
y1 = y;
in_row += 1;
}
else
{
if (in_row > length_th)
lines.push_back(Vec4i(x, y1, x, y - 1));
in_row = 0;
}
}
if (in_row > length_th)
lines.push_back(Vec4i(x, y1, x, h - 1));
}
return lines;
}
