void StereoProcessor::processDisparity(const cv::Mat& left_rect, const cv::Mat& right_rect,
const image_geometry::StereoCameraModel& model,
stereo_msgs::DisparityImage& disparity) const
{
// Fixed-point disparity is 16 times the true value: d = d_fp / 16.0 = x_l - x_r.
static const int DPP = 16; // disparities per pixel
static const double inv_dpp = 1.0 / DPP;
// Block matcher produces 16-bit signed (fixed point) disparity image
block_matcher_(left_rect, right_rect, disparity16_);
// Fill in DisparityImage image data, converting to 32-bit float
sensor_msgs::Image& dimage = disparity.image;
dimage.height = disparity16_.rows;
dimage.width = disparity16_.cols;
dimage.encoding = sensor_msgs::image_encodings::TYPE_32FC1;
dimage.step = dimage.width * sizeof(float);
dimage.data.resize(dimage.step * dimage.height);
cv::Mat_<float> dmat(dimage.height, dimage.width, (float*)&dimage.data[0], dimage.step);
// We convert from fixed-point to float disparity and also adjust for any x-offset between
// the principal points: d = d_fp*inv_dpp - (cx_l - cx_r)
disparity16_.convertTo(dmat, dmat.type(), inv_dpp, -(model.left().cx() - model.right().cx()));
ROS_ASSERT(dmat.data == &dimage.data[0]);
/// @todo is_bigendian? :)
// Stereo parameters
disparity.f = model.right().fx();
disparity.T = model.baseline();
/// @todo Window of (potentially) valid disparities
// Disparity search range
disparity.min_disparity = getMinDisparity();
disparity.max_disparity = getMinDisparity() + getDisparityRange() - 1;
disparity.delta_d = inv_dpp;
}
void DisparityWideNodelet::imageCb(const ImageConstPtr& l_image_msg,
const CameraInfoConstPtr& l_info_msg,
const ImageConstPtr& r_image_msg,
const CameraInfoConstPtr& r_info_msg)
{
/// @todo Convert (share) with new cv_bridge
assert(l_image_msg->encoding == sensor_msgs::image_encodings::MONO8);
assert(r_image_msg->encoding == sensor_msgs::image_encodings::MONO8);
// Update the camera model
model_.fromCameraInfo(l_info_msg, r_info_msg);
// Allocate new disparity image message
DisparityImagePtr disp_msg = boost::make_shared<DisparityImage>();
disp_msg->header = l_info_msg->header;
disp_msg->image.header = l_info_msg->header;
disp_msg->image.height = l_image_msg->height;
disp_msg->image.width = l_image_msg->width;
disp_msg->image.encoding = sensor_msgs::image_encodings::TYPE_32FC1;
disp_msg->image.step = disp_msg->image.width * sizeof(float);
disp_msg->image.data.resize(disp_msg->image.height * disp_msg->image.step);
// Stereo parameters
disp_msg->f = model_.right().fx();
disp_msg->T = model_.baseline();
// Compute window of (potentially) valid disparities
cv::Ptr<CvStereoBMState> params = block_matcher_.state;
int border = params->SADWindowSize / 2;
int left = params->numberOfDisparities + params->minDisparity + border - 1;
int wtf = (params->minDisparity >= 0) ? border + params->minDisparity : std::max(border, -params->minDisparity);
int right = disp_msg->image.width - 1 - wtf;
int top = border;
int bottom = disp_msg->image.height - 1 - border;
disp_msg->valid_window.x_offset = left;
disp_msg->valid_window.y_offset = top;
disp_msg->valid_window.width = right - left;
disp_msg->valid_window.height = bottom - top;
// Disparity search range
disp_msg->min_disparity = params->minDisparity;
disp_msg->max_disparity = params->minDisparity + params->numberOfDisparities - 1;
disp_msg->delta_d = 1.0 / 16; // OpenCV uses 16 disparities per pixel
// Create cv::Mat views onto all buffers
const cv::Mat_<uint8_t> l_image(l_image_msg->height, l_image_msg->width,
const_cast<uint8_t*>(&l_image_msg->data[0]),
l_image_msg->step);
const cv::Mat_<uint8_t> r_image(r_image_msg->height, r_image_msg->width,
const_cast<uint8_t*>(&r_image_msg->data[0]),
r_image_msg->step);
cv::Mat_<float> disp_image(disp_msg->image.height, disp_msg->image.width,
reinterpret_cast<float*>(&disp_msg->image.data[0]),
disp_msg->image.step);
// Perform block matching to find the disparities
block_matcher_(l_image, r_image, disp_image, CV_32F);
// Adjust for any x-offset between the principal points: d' = d - (cx_l - cx_r)
double cx_l = model_.left().cx();
double cx_r = model_.right().cx();
if (cx_l != cx_r)
cv::subtract(disp_image, cv::Scalar(cx_l - cx_r), disp_image);
pub_disparity_.publish(disp_msg);
}