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Merge pull request #6 from iory/hough-line
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Add parameter to hough_lines_nodelet
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@k-okada
k-okada committed May 25, 2016
2 parents a4b6e82 + 31c6f1b commit e94768b
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Showing 2 changed files with 55 additions and 24 deletions.
4 changes: 4 additions & 0 deletions cfg/HoughLines.cfg
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Original file line number Diff line number Diff line change
Expand Up @@ -44,5 +44,9 @@ hough_type = gen.enum([ gen.const("Standard_Hough_Transform", int_t, 0, "Stan
gen.add("hough_type", int_t, 0, "Hough Line Methods", 0, 0, 1, edit_method=hough_type)
gen.add("threshold", int_t, 150, "Hough Line Threshold", 150, 50, 150)

gen.add("rho", double_t, 0, "The resolution of the parameter r in pixels. We use 1 pixel.", 1, 1.0, 100.0)
gen.add("theta", double_t, 0, "The resolution of the parameter \theta in radians. We use 1 degree (CV_PI/180)", 1, 1.0, 90.0)
gen.add("minLineLength", double_t, 0, "The minimum number of points that can form a line. Lines with less than this number of points are disregarded.", 30, 0, 500)
gen.add("maxLineGap", double_t, 0, "The maximum gap between two points to be considered in the same line.", 10, 0, 100)

exit(gen.generate(PACKAGE, "hough_lines", "HoughLines"))
75 changes: 51 additions & 24 deletions src/nodelet/hough_lines_nodelet.cpp
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Original file line number Diff line number Diff line change
@@ -1,3 +1,4 @@
// -*- coding:utf-8-unix; mode: c++; indent-tabs-mode: nil; c-basic-offset: 2; -*-
/*********************************************************************
* Software License Agreement (BSD License)
*
Expand Down Expand Up @@ -75,11 +76,19 @@ class HoughLinesNodelet : public opencv_apps::Nodelet
int min_threshold_;
int max_threshold_;
int threshold_;
double rho_;
double theta_;
double minLineLength_;
double maxLineGap_;

void reconfigureCallback(hough_lines::HoughLinesConfig &new_config, uint32_t level)
{
config_ = new_config;
threshold_ = config_.threshold;
config_ = new_config;
rho_ = config_.rho;
theta_ = config_.theta;
threshold_ = config_.threshold;
minLineLength_ = config_.minLineLength;
maxLineGap_ = config_.maxLineGap;
}

const std::string &frameWithDefault(const std::string &frame, const std::string &image_frame)
Expand Down Expand Up @@ -110,23 +119,44 @@ class HoughLinesNodelet : public opencv_apps::Nodelet
try
{
// Convert the image into something opencv can handle.
cv::Mat frame = cv_bridge::toCvShare(msg, msg->encoding)->image;
cv::Mat in_image = cv_bridge::toCvShare(msg, msg->encoding)->image;
cv::Mat src_gray;

if (in_image.channels() > 1) {
cv::cvtColor( in_image, src_gray, cv::COLOR_BGR2GRAY );
/// Apply Canny edge detector
Canny( src_gray, in_image, 50, 200, 3 );
}
else {
/// Check whether input gray image is filtered such that canny, sobel ...etc
bool is_filtered = true;
for(int y=0; y < in_image.rows; ++y) {
for(int x=0; x < in_image.cols; ++x) {
if(!(in_image.at<unsigned char>(y, x) == 0
|| in_image.at<unsigned char>(y, x) == 255)) {
is_filtered = false;
break;
}
if(!is_filtered) {
break;
}
}
}

if(!is_filtered) {
Canny( in_image, in_image, 50, 200, 3 );
}
}

cv::Mat out_image;
cv::cvtColor(in_image, out_image, CV_GRAY2BGR);

// Messages
opencv_apps::LineArrayStamped lines_msg;
lines_msg.header = msg->header;

// Do the work
std::vector<cv::Rect> faces;
cv::Mat src_gray, edges;

if ( frame.channels() > 1 ) {
cv::cvtColor( frame, src_gray, cv::COLOR_BGR2GRAY );
} else {
src_gray = frame;
}
/// Apply Canny edge detector
Canny( src_gray, edges, 50, 200, 3 );

if( debug_view_) {
/// Create Trackbars for Thresholds
Expand All @@ -142,16 +172,13 @@ class HoughLinesNodelet : public opencv_apps::Nodelet
}
}

/// Initialize
cv::cvtColor( edges, frame, cv::COLOR_GRAY2BGR );

switch (config_.hough_type) {
case hough_lines::HoughLines_Standard_Hough_Transform:
{
std::vector<cv::Vec2f> s_lines;

/// 1. Use Standard Hough Transform
cv::HoughLines( edges, s_lines, 1, CV_PI/180, min_threshold_ + threshold_, 0, 0 );
cv::HoughLines( in_image, s_lines, rho_, theta_ * CV_PI/180, threshold_, minLineLength_, maxLineGap_ );

/// Show the result
for( size_t i = 0; i < s_lines.size(); i++ )
Expand All @@ -164,9 +191,9 @@ class HoughLinesNodelet : public opencv_apps::Nodelet
cv::Point pt1( cvRound(x0 + alpha*(-sin_t)), cvRound(y0 + alpha*cos_t) );
cv::Point pt2( cvRound(x0 - alpha*(-sin_t)), cvRound(y0 - alpha*cos_t) );
#ifndef CV_VERSION_EPOCH
cv::line( frame, pt1, pt2, cv::Scalar(255,0,0), 3, cv::LINE_AA);
cv::line( out_image, pt1, pt2, cv::Scalar(255,0,0), 3, cv::LINE_AA);
#else
cv::line( frame, pt1, pt2, cv::Scalar(255,0,0), 3, CV_AA);
cv::line( out_image, pt1, pt2, cv::Scalar(255,0,0), 3, CV_AA);
#endif
opencv_apps::Line line_msg;
line_msg.pt1.x = pt1.x;
Expand All @@ -184,16 +211,16 @@ class HoughLinesNodelet : public opencv_apps::Nodelet
std::vector<cv::Vec4i> p_lines;

/// 2. Use Probabilistic Hough Transform
cv::HoughLinesP( edges, p_lines, 1, CV_PI/180, min_threshold_ + threshold_, 30, 10 );
cv::HoughLinesP( in_image, p_lines, rho_, theta_ * CV_PI/180, threshold_, minLineLength_, maxLineGap_ );

/// Show the result
for( size_t i = 0; i < p_lines.size(); i++ )
{
cv::Vec4i l = p_lines[i];
#ifndef CV_VERSION_EPOCH
cv::line( frame, cv::Point(l[0], l[1]), cv::Point(l[2], l[3]), cv::Scalar(255,0,0), 3, cv::LINE_AA);
cv::line( out_image, cv::Point(l[0], l[1]), cv::Point(l[2], l[3]), cv::Scalar(255,0,0), 3, cv::LINE_AA);
#else
cv::line( frame, cv::Point(l[0], l[1]), cv::Point(l[2], l[3]), cv::Scalar(255,0,0), 3, CV_AA);
cv::line( out_image, cv::Point(l[0], l[1]), cv::Point(l[2], l[3]), cv::Scalar(255,0,0), 3, CV_AA);
#endif
opencv_apps::Line line_msg;
line_msg.pt1.x = l[0];
Expand All @@ -209,12 +236,12 @@ class HoughLinesNodelet : public opencv_apps::Nodelet

//-- Show what you got
if( debug_view_) {
cv::imshow( window_name_, frame );
cv::imshow( window_name_, out_image );
int c = cv::waitKey(1);
}

// Publish the image.
sensor_msgs::Image::Ptr out_img = cv_bridge::CvImage(msg->header, "bgr8", frame).toImageMsg();
sensor_msgs::Image::Ptr out_img = cv_bridge::CvImage(msg->header, "bgr8", out_image).toImageMsg();
img_pub_.publish(out_img);
msg_pub_.publish(lines_msg);
}
Expand Down Expand Up @@ -262,7 +289,7 @@ class HoughLinesNodelet : public opencv_apps::Nodelet
dynamic_reconfigure::Server<hough_lines::HoughLinesConfig>::CallbackType f =
boost::bind(&HoughLinesNodelet::reconfigureCallback, this, _1, _2);
srv.setCallback(f);

img_pub_ = advertiseImage(*pnh_, "image", 1);
msg_pub_ = advertise<opencv_apps::LineArrayStamped>(*pnh_, "lines", 1);

Expand Down

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