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- #include <opencv.hpp>
- #include <math.h>
- #include <io.h>
- #include "tea_sorter.h"
- #include "utils.h"
- using namespace cv;
- namespace graft_cv{
- CTeaSort::CTeaSort(
- ConfigParam& cp,
- img_type dtpye,
- CGcvLogger*pLog)
- :
- m_cp(cp),
- m_dtype(dtpye),
- m_pLogger(pLog),
- m_ppImgSaver(0),
- m_pImginfoRaw(0),
- m_pImginfoDetected(0)
- {
- m_drop_detector = RetinaDrop(m_pLogger, 0.5, 0.5);
- }
- CTeaSort::~CTeaSort()
- {
- clear_imginfo();
- }
- int CTeaSort::detect(
- ImgInfo*imginfo,
- PositionInfo& posinfo,
- const char* fn
- )
- {
- //1 model status
- if (!m_drop_detector.IsModelLoaded()) {
- m_pLogger->ERRORINFO(
- string("tea detect model NOT loaded"));
- return 1;
- }
- //2 update recognize threshold
- if (m_dtype == img_type::tea_grab) {
- m_drop_detector.SetThreshold(m_cp.object_threshold_grab, m_cp.nms_threshold_grab);
- }
- else {
- m_drop_detector.SetThreshold(m_cp.object_threshold_cut, m_cp.nms_threshold_cut);
- }
- //3 load data
- load_data(imginfo, fn);
- if (m_cp.image_show) {
- cv::destroyAllWindows();
- imshow_wait("input_img", m_raw_img);
- }
- //4 generate_detect_windows(vector<Rect>&boxes)
- vector<Rect> drop_regions;
- int region_cnt = generate_detect_windows(drop_regions);
- if (region_cnt == 0) {
- stringstream buff_;
- buff_ << m_imgId << m_dtype_str << "tea detect image regions' size == 0";
- m_pLogger->ERRORINFO(buff_.str());
- return 1;
- }
- else {
- stringstream bufftmp;
- bufftmp << m_imgId << m_dtype_str << "tea detect image regions' size = "<<region_cnt;
- m_pLogger->INFO(bufftmp.str());
- }
- if (m_cp.image_show) {
- cv::Mat rects_img = m_raw_img.clone();
- int step_c = int(255 / (float)region_cnt);
- int step_cc = step_c / 2;
- int step_ccc = step_cc / 2;
- int cnt = 0;
- for (auto&r : drop_regions) {
- cv::rectangle(rects_img, r, cv::Scalar(step_cc*cnt, step_c*cnt, step_ccc*cnt), 3);
- cnt += 1;
- }
- imshow_wait("regions_img", rects_img);
- }
- //5 detect
- vector<Bbox> droplets_raw;
- int dn = detect_impl(m_raw_img, drop_regions, droplets_raw);
- if (dn < 2 && m_dtype == img_type::tea_grab) {
- //up-down flip
- cv::Mat flip_img;
- cv::flip(m_raw_img, flip_img, 0);
- if (m_cp.image_show) {
- imshow_wait("flip_img", flip_img);
- }
- vector<Bbox> droplets_flip;
- int dn_flip = detect_impl(flip_img, drop_regions, droplets_flip);
- for (auto&b: droplets_flip) {
- int y2 = flip_img.rows - b.y1;
- int y1 = flip_img.rows - b.y2;
- b.y1 = y1;
- b.y2 = y2;
-
- for (int i = 0; i < 5; ++i) {
- b.ppoint[2 * i + 1] = flip_img.rows - b.ppoint[2 * i + 1];
- }
- }
- if (dn_flip > 0) {
- droplets_raw.insert(
- droplets_raw.end(),
- droplets_flip.begin(),
- droplets_flip.end());
- }
- }
- /*for (auto rect : drop_regions) {
- Mat roi = m_raw_img(rect);
- vector<Bbox> head_droplets = m_drop_detector.RunModel(roi, m_pLogger);
- if (m_pLogger) {
- stringstream buff_;
- buff_ << m_imgId << m_dtype_str << "-------crop_rect["<< rect.x<<","<<rect.y<<","<<rect.width
- <<","<<rect.height<<"],"
- <<" roi image detect over. tea number is " << head_droplets.size();
- m_pLogger->INFO(buff_.str());
- }
- for (Bbox& b : head_droplets) {
- b.x1 += rect.x;
- b.x2 += rect.x;
- b.y1 += rect.y;
- b.y2 += rect.y;
- for (int i = 0; i < 5; ++i) {
- b.ppoint[2 * i] += rect.x;
- b.ppoint[2 * i + 1] += rect.y;
- }
- }
- if (head_droplets.size()) {
- droplets_raw.insert(
- droplets_raw.end(),
- head_droplets.begin(),
- head_droplets.end());
- }
- }*/
- if (m_pLogger) {
- stringstream buff_;
- buff_ << m_imgId<<m_dtype_str << "image detect over. tea number is " << droplets_raw.size();
- m_pLogger->INFO(buff_.str());
- }
- //6 nms, width(height) filt and area calculation
- vector<Bbox> droplets;
- vector<int> keep;
- nms_bbox(droplets_raw, m_drop_detector.GetNmsThreshold(), keep);
- //nms keep and area filter
- double min_area_th = m_cp.min_area_ratio_grab;
- double max_area_th = m_cp.max_area_ratio_grab;
- if (m_dtype == img_type::tea_cut) {
- min_area_th = m_cp.min_area_ratio_cut;
- max_area_th = m_cp.max_area_ratio_cut;
- }
- for (int i : keep) {
- Bbox&tbox = droplets_raw[i];
- double area_ratio = static_cast<double>(tbox.y2 - tbox.y1) * static_cast<double>(tbox.x2 - tbox.x1);
- area_ratio = fabs(area_ratio);
- area_ratio /= static_cast<double>(m_raw_img.rows);
- area_ratio /= static_cast<double>(m_raw_img.cols);
- tbox.area = area_ratio;
- if (area_ratio < min_area_th || area_ratio > max_area_th) { continue; }
- droplets.push_back(tbox);
- }
- if (m_pLogger) {
- stringstream buff_;
- buff_ << m_imgId << m_dtype_str << "after nms, keep tea number is " << droplets.size();
- for (auto&tbox : droplets) {
- buff_ << "\nscore:" << tbox.score << ", area_ratio:" << tbox.area << ", left_top:(" << tbox.x1 << "," << tbox.y1 << "), bottom_rigt:(" << tbox.x2 << "," << tbox.y2 << ")";
- }
- m_pLogger->INFO(buff_.str());
- }
-
-
- int valid_cnt = 0;
- if (m_dtype == img_type::tea_grab) {
- //grab
- double pre_cx, pre_cy;
- double min_dist_grab = m_cp.min_distance_grab;
- pre_cx = -min_dist_grab;
- pre_cy = -min_dist_grab;
- for (int i = 0; i < droplets.size(); ++i) {
- if (valid_cnt > 1) { break; }
- Bbox&b = droplets.at(i);
- double cx = 0.5*(b.x1 + b.x2);
- double cy = 0.5*(b.y1 + b.y2);
- double dist = sqrt((cx - pre_cx)*(cx - pre_cx) + (cy - pre_cy)*(cy - pre_cy));
- if (dist < min_dist_grab) {
- continue;
- }
- double grab_x, grab_y;
- double angle = calculate_angle(b, grab_x, grab_y);
-
- //grab point
- if (valid_cnt == 0) {
- posinfo.tea_grab_x1 = grab_x;
- posinfo.tea_grab_y1 = grab_y;
- posinfo.tea_grab_angle1 = angle;
- }
- else {
- posinfo.tea_grab_x2 = grab_x;
- posinfo.tea_grab_y2 = grab_y;
- posinfo.tea_grab_angle2 = angle;
- }
- pre_cx = cx;
- pre_cy = cy;
- b.status = 1;
- valid_cnt += 1;
- }
- }
- else {
- //cut
- for (int i = 0; i < droplets.size();++i) {
- if (i > 1) { break; }
- Bbox&b = droplets.at(i);
- b.status = 1; // selected
- double grab_x, grab_y;
- double angle = calculate_angle(b, grab_x, grab_y);
- valid_cnt += 1;
- if (i == 0) {
- // 切割点是3、4的中间的点
- posinfo.tea_cut_x1 = 0.5 * (b.ppoint[4] + b.ppoint[6]);
- posinfo.tea_cut_y1 = 0.5 * (b.ppoint[5] + b.ppoint[7]);
- posinfo.tea_cut_angle1 = angle;
- }
- else {
- // 切割点是3、4的中间的点
- posinfo.tea_cut_x2 = 0.5 * (b.ppoint[4] + b.ppoint[6]);
- posinfo.tea_cut_y2 = 0.5 * (b.ppoint[5] + b.ppoint[7]);
- posinfo.tea_cut_angle2 = angle;
- }
- }
- }
-
- //6 draw
- if (m_cp.image_return) {
- this->clear_imginfo();
- cv::Mat img_rst = m_raw_img.clone();
- for (auto& b : droplets) {
- //rectangle
- cv::Rect r = cv::Rect(cv::Point2i(b.x1, b.y1), cv::Point2i(b.x2, b.y2));
- if (b.status > 0) {
- cv::rectangle(img_rst, r, cv::Scalar(0, 0, 255),2);
- }
- else {
- cv::rectangle(img_rst, r, cv::Scalar(0, 255, 0),2);
- }
- //score
- char name[256];
- cv::Scalar color(120, 120, 0);//bgr
-
- sprintf_s(name, "%.2f", b.score);
- cv::putText(img_rst, name,
- cv::Point(b.x1, b.y1),
- cv::FONT_HERSHEY_COMPLEX, 0.7, color, 2);
- //points
- cv::circle(img_rst, cv::Point(int(b.ppoint[0]), int(b.ppoint[1])), 4, cv::Scalar(255, 0, 255), -1, 3, 0);
- cv::circle(img_rst, cv::Point(int(b.ppoint[2]), int(b.ppoint[3])), 4, cv::Scalar(0, 255, 255), -1, 3, 0);
- cv::circle(img_rst, cv::Point(int(b.ppoint[4]), int(b.ppoint[5])), 4, cv::Scalar(255, 0, 0), -1, 3, 0);
- cv::circle(img_rst, cv::Point(int(b.ppoint[6]), int(b.ppoint[7])), 4, cv::Scalar(0, 255, 0), -1, 3, 0);
- cv::circle(img_rst, cv::Point(int(b.ppoint[8]), int(b.ppoint[9])), 4, cv::Scalar(0, 0, 255), -1, 3, 0);
-
- //grab points
- if (m_dtype == img_type::tea_grab) {
- double grab_x, grab_y;
- calculate_angle(b, grab_x, grab_y);
- //cv::circle(img_rst, cv::Point(int(grab_x), int(grab_y)), 4, cv::Scalar(0, 215, 255), -1, 3, 0);
- //lines, p4-p5, p5-grab
- cv::line(img_rst,
- cv::Point(int(b.ppoint[6]), int(b.ppoint[7])),
- cv::Point(int(b.ppoint[8]), int(b.ppoint[9])),
- cv::Scalar(0, 215, 255), 2);
- cv::line(img_rst,
- cv::Point(int(b.ppoint[8]), int(b.ppoint[9])),
- cv::Point(int(grab_x), int(grab_y)),
- cv::Scalar(0, 215, 255), 2);
- //line x
- int radius = 20;
- int cx = int(grab_x);
- int cy = int(grab_y);
- cv::line(img_rst, cv::Point(cx - radius, cy - radius), cv::Point(cx + radius, cy + radius), cv::Scalar(0, 215, 255), 2);
- cv::line(img_rst, cv::Point(cx - radius, cy + radius), cv::Point(cx + radius, cy - radius), cv::Scalar(0, 215, 255), 2);
- }
- //cut points
- if (m_dtype == img_type::tea_cut) {
- //lines, p3-p4
- cv::line(img_rst,
- cv::Point(int(b.ppoint[4]), int(b.ppoint[5])),
- cv::Point(int(b.ppoint[6]), int(b.ppoint[7])),
- cv::Scalar(0, 215, 255), 2);
- //line x
- int cx = int(0.5 * (b.ppoint[4] + b.ppoint[6]));
- int cy = int(0.5 * (b.ppoint[5] + b.ppoint[7]));
- int radius = 20;
- cv::line(img_rst, cv::Point(cx - radius, cy - radius), cv::Point(cx + radius, cy + radius), cv::Scalar(0, 215, 255),2);
- cv::line(img_rst, cv::Point(cx - radius, cy + radius), cv::Point(cx + radius, cy - radius), cv::Scalar(0, 215, 255),2);
- }
- }
- if (m_cp.image_show) {
- imshow_wait("result_img", img_rst);
- }
- m_pImginfoRaw = mat2imginfo(m_raw_img);
- m_pImginfoDetected = mat2imginfo(img_rst);
- posinfo.pp_images[0] = m_pImginfoRaw;
- posinfo.pp_images[1] = m_pImginfoDetected;
- if (m_ppImgSaver && *m_ppImgSaver) {
- (*m_ppImgSaver)->saveImage(img_rst, m_imgId + "_rst_0");
- }
- }
- //拍照无苗, 返回识别结果-1
- if (valid_cnt == 0) { return -1; }
- return 0;
- }
- int CTeaSort::detect_impl(
- cv::Mat& raw_img, //input, image
- vector<Rect>&drop_regions, //input, detect regions
- vector<Bbox> &droplets_raw //output, detect result
- )
- {
- //return number of detect result
- droplets_raw.clear();
- for (auto rect : drop_regions) {
- Mat roi = raw_img(rect);
- vector<Bbox> head_droplets = m_drop_detector.RunModel(roi, m_pLogger);
- if (m_pLogger) {
- stringstream buff_;
- buff_ << m_imgId << m_dtype_str << "-------crop_rect[" << rect.x << "," << rect.y << "," << rect.width
- << "," << rect.height << "],"
- << " roi image detect over. tea number is " << head_droplets.size();
- m_pLogger->INFO(buff_.str());
- }
- for (Bbox& b : head_droplets) {
- b.x1 += rect.x;
- b.x2 += rect.x;
- b.y1 += rect.y;
- b.y2 += rect.y;
- for (int i = 0; i < 5; ++i) {
- b.ppoint[2 * i] += rect.x;
- b.ppoint[2 * i + 1] += rect.y;
- }
- }
- if (head_droplets.size()) {
- droplets_raw.insert(
- droplets_raw.end(),
- head_droplets.begin(),
- head_droplets.end());
- }
- }
- return droplets_raw.size();
- }
- double CTeaSort::calculate_angle(
- Bbox&b, //input
- double& grab_x, //output
- double& grab_y //output
- )
- {
- grab_x = grab_y = 0.0;
- double angle = 0.0;
- float x3,y3,x4,y4,x5,y5;
- x3 = b.ppoint[4];
- y3 = b.ppoint[5];
- x4 = b.ppoint[6];
- y4 = b.ppoint[7];
- x5 = b.ppoint[8];
- y5 = b.ppoint[9];
- if (m_dtype == img_type::tea_grab) {
- calculate_stem_grab_position(b, grab_x, grab_y);
- //calculate line of p4 ans p5
- double r45 = sqrt((x4 - x5)*(x4 - x5) + (y4 - y5)*(y4 - y5));
- if (r45 < 15.0) {
- angle = atan2(x5 - x3, y5 - y3);
- }
- else {
- angle = atan2(x5 - x4, y5 - y4);
- }
- //计算抓取点
- if (grab_x < 0 && grab_y < 0) {
- double pr = (double)m_cp.offset_grab;
- double dx = pr * sin(angle);
- double dy = pr * cos(angle);
- grab_x = x5 + dx;
- grab_y = y5 + dy;
- }
-
- }
- else {
- //tea cut, calculate line of p3 ans p4
- angle = atan2(x3 - x4, y3 - y4);
- }
-
- angle *= (180.0 / 3.1415926);
- return angle;
- }
- int CTeaSort::load_data(
- ImgInfo*imginfo,
- const char* fn/* = 0*/)
- {
- //数据加载功能实现,并生成imageid,保存原始数据到文件
- int rst = 0;
- //generate image id
- if (m_dtype == img_type::tea_grab) {
- m_imgId = getImgId(img_type::tea_grab);
- m_dtype_str = string(" tea_grab ");
- }
- else {
- m_imgId = getImgId(img_type::tea_cut);
- m_dtype_str = string(" tea_cut ");
- }
- if (imginfo) {
- if (m_pLogger) {
- stringstream buff;
- buff << m_imgId << m_dtype_str << "image, width=" << imginfo->width
- << "\theight=" << imginfo->height;
- m_pLogger->INFO(buff.str());
- }
- if (!isvalid(imginfo) || (imginfo->channel!=1 && imginfo->channel!=3)) {
- if (m_pLogger) {
- m_pLogger->ERRORINFO(m_imgId + m_dtype_str + "input image invalid.");
- }
- throw_msg(m_imgId + " invalid input image");
- }
- if (imginfo->channel == 1) {
- cv::Mat tmp_img = imginfo2mat(imginfo);
- vector<Mat> channels;
- for (size_t i = 0; i < 3; ++i) { channels.push_back(tmp_img); }
- cv::merge(channels, m_raw_img);
- }
- else {
- m_raw_img = imginfo2mat(imginfo);
- }
-
- }
- else {
- cv::Mat img = imread(fn, cv::IMREAD_COLOR);
- if (img.empty()) {
- if (m_pLogger) {
- m_pLogger->ERRORINFO(m_imgId + m_dtype_str + "input image invalid:" + string(fn));
- }
- throw_msg(m_imgId + m_dtype_str + "invalid input image: " + string(fn));
- }
- if (m_pLogger) {
- stringstream buff;
- buff << m_imgId << m_dtype_str << "image, width=" << img.cols
- << "\theight=" << img.rows;
- m_pLogger->INFO(buff.str());
- }
- m_raw_img = img.clone();
- }
- //image saver
- if (m_ppImgSaver && *m_ppImgSaver) {
- (*m_ppImgSaver)->saveImage(m_raw_img, m_imgId);
- }
- return rst;
- }
- int CTeaSort::load_model()
- {
- bool b = false;
- if (!m_drop_detector.IsModelLoaded()) {
- if (m_dtype == img_type::tea_grab) {
- b = m_drop_detector.LoadModel(m_cp.model_path_grab);
- }
- else {
- b = m_drop_detector.LoadModel(m_cp.model_path_cut);
- }
-
- }
- else {
- b = true;
- }
- return b ? 0 : 1;
- }
- void CTeaSort::clear_imginfo() {
- if (m_pImginfoDetected) {
- imginfo_release(&m_pImginfoDetected);
- m_pImginfoDetected = 0;
- }
- if (m_pImginfoRaw) {
- imginfo_release(&m_pImginfoRaw);
- m_pImginfoRaw = 0;
- }
- }
- int CTeaSort::generate_detect_windows(vector<Rect>&boxes)
- {
- boxes.clear();
- int grid_row = m_cp.grid_row_cut;
- int grid_col = m_cp.grid_col_cut;
- int grid_padding = m_cp.grid_padding_cut;
- if (m_dtype == img_type::tea_grab) {
- grid_row = m_cp.grid_row_grab;
- grid_col = m_cp.grid_col_grab;
- grid_padding = m_cp.grid_padding_grab;
- }
- if (grid_row < 1) { grid_row = 1; }
- if (grid_col < 1) { grid_col = 1; }
- if (grid_padding < 0) { grid_padding = 0; }
- int block_height = int(m_raw_img.rows / (float)grid_row + 0.5);
- int block_width = int(m_raw_img.cols / (float)grid_col + 0.5);
- for (int r = 0; r < grid_row; ++r) {
- for (int c = 0; c < grid_col; ++c) {
- int x0 = c*block_width - grid_padding;
- int y0 = r*block_height - grid_padding;
- int x1 = (c+1)*block_width + grid_padding;
- int y1 = (r+1)*block_height + grid_padding;
- if (x0 < 0) { x0 = 0; }
- if (y0 < 0) { y0 = 0; }
- if (x1 > m_raw_img.cols) { x1 = m_raw_img.cols; }
- if (y1 > m_raw_img.rows) { y1 = m_raw_img.rows; }
- Rect r(x0, y0, x1-x0, y1-y0);
- boxes.push_back(r);
- }
- }
- return boxes.size();
- }
- void CTeaSort::calculate_stem_grab_position(
- Bbox&b,
- double& grab_x, //output
- double& grab_y //output
- )
- {
- grab_x = grab_y = -1.0;
- //crop image
- int padding = 2 * m_cp.offset_grab;
- int y3 = int(b.ppoint[5]);
- int y5 = int(b.ppoint[9]);
- cv::Point p3(int(b.ppoint[4] - b.x1), int(b.ppoint[5] - b.y1));
- cv::Point p5(int(b.ppoint[8] - b.x1), int(b.ppoint[9] - b.y1));
- cv::Mat crop_img;
- if (y5 > y3) {
- // Y position
- crop_img = m_raw_img(cv::Range(b.y1, b.y2 + padding), cv::Range(b.x1, b.x2)).clone();
- }
- else {
- // ^ position
- if (b.y1 - padding < 0) {
- padding = b.y1;
- }
- p5.y = int(b.ppoint[9] - b.y1 + padding);
- p3.y = int(b.ppoint[5] - b.y1 + padding);
- crop_img = m_raw_img(cv::Range(b.y1 - padding, b.y2), cv::Range(b.x1, b.x2)).clone();
-
- }
- if (m_cp.image_show) {
- cv::Mat crop_img_tmp = crop_img.clone();
- cv::circle(crop_img_tmp, p5, 4, cv::Scalar(255, 0, 255), -1, 3, 0);
- imshow_wait("cropped box", crop_img_tmp);
- }
- //to gray
- cv::Mat gray_img;
- if (crop_img.channels() == 1) { gray_img = crop_img; }
- else {
- cv::cvtColor(crop_img, gray_img, cv::COLOR_BGR2GRAY);
- }
- //binary
- cv::Mat bin_img;
- double th = cv::threshold(gray_img, bin_img, 255, 255, cv::THRESH_OTSU);
- cv::bitwise_not(bin_img, bin_img);
- if (m_cp.image_show) {
- imshow_wait("cropped binary img", bin_img);
- }
- // skeletonize() or medial_axis()
- cv::Mat ske_img;
- thinning(bin_img, ske_img);
- /*if (m_cp.image_show) {
- imshow_wait("skeleton img", ske_img);
- }*/
- //遍历所有点,找到距离等于指定距离的点的位置
- std::vector<cv::Point> candidate_pts;
- double dist_th = 5;
- for (int r = 0; r < ske_img.rows; ++r) {
- for (int c = 0; c < ske_img.cols; ++c) {
- if (ske_img.at<unsigned char>(r, c) == 0) { continue; }
- double dist = std::powf((p5.x - c), 2) + std::powf((p5.y - r),2);
- dist = std::sqrtf(dist);
- if (std::fabs(dist - m_cp.offset_grab) < dist_th) {
- candidate_pts.push_back(cv::Point(c, r));
- }
- }
- }
- //按与参考角度的差,找到有效的候选点集合
- std::vector<cv::Point> valid_candidate_pts;
- double ref_angle = atan2(p5.x - p3.x, p5.y - p3.y);
- for (auto&p : candidate_pts) {
- double angle_to_p3 = atan2(p.x - p3.x, p.y - p3.y);
- //计算夹角
- double fabs_angle = 0;
- if (ref_angle > 0.5 * CV_PI) {
- if (angle_to_p3 < 0) {
- angle_to_p3 += 2 * CV_PI;
- }
- fabs_angle = std::fabs(angle_to_p3 - ref_angle);
- }
- else {
- if (ref_angle < -0.5 * CV_PI) {
- if (angle_to_p3 > 0) {
- angle_to_p3 -= 2 * CV_PI;
- }
- fabs_angle = std::fabs(angle_to_p3 - ref_angle);
- }
- else {
- fabs_angle = std::fabs(angle_to_p3 - ref_angle);
- }
- }
- if (fabs_angle > CV_PI / 4.0) { continue; }
- valid_candidate_pts.push_back(p);
- }
- // 找到离重心最近的点作为抓取点
- if (valid_candidate_pts.size() > 0) {
- cv::Point2f p_mu(0,0);
- for (auto&p : valid_candidate_pts) {
- p_mu.x += p.x;
- p_mu.y += p.y;
- }
- p_mu.x /= (float)(valid_candidate_pts.size());
- p_mu.y /= (float)(valid_candidate_pts.size());
- double min_dist = 1.0e8;
- for (auto&p : valid_candidate_pts) {
- double dist = std::powf((p.x - p_mu.x), 2) + std::powf((p.y - p_mu.y), 2);
- dist = std::sqrtf(dist);
- if (dist < min_dist) {
- min_dist = dist;
- grab_x = p.x;
- grab_y = p.y;
- }
- }
- }
- if (m_cp.image_show) {
- cv::Mat ske_img_tmp = ske_img.clone();
- for (auto&p : valid_candidate_pts) {
- ske_img_tmp.at<unsigned char>(p) = 100;
- }
- cv::circle(ske_img_tmp, p5, 4, cv::Scalar(255, 0, 255), 1, 3, 0);
- if (grab_x > 0 && grab_y > 0) {
- cv::circle(ske_img_tmp, cv::Point(int(grab_x), int(grab_y)), 4, cv::Scalar(156, 0, 255), 1, 3, 0);
- }
- imshow_wait("skeleton img label", ske_img_tmp);
- }
- //重新得到grab_x,grab_y的坐标
- if (grab_x > 0 && grab_y > 0) {
- int real_padding_y = p5.y - int(b.ppoint[9] - b.y1);
- grab_y -= real_padding_y;
- grab_y += b.y1;
- grab_x += b.x1;
- }
- }
- /**
- * Code for thinning a binary image using Zhang-Suen algorithm.
- *
- * Author: Nash (nash [at] opencv-code [dot] com)
- * Website: http://opencv-code.com
- */
- /**
- * Perform one thinning iteration.
- * Normally you wouldn't call this function directly from your code.
- *
- * Parameters:
- * im Binary image with range = [0,1]
- * iter 0=even, 1=odd
- */
- void CTeaSort::thinningIteration(cv::Mat& img, int iter)
- {
- CV_Assert(img.channels() == 1);
- CV_Assert(img.depth() != sizeof(uchar));
- CV_Assert(img.rows > 3 && img.cols > 3);
- cv::Mat marker = cv::Mat::zeros(img.size(), CV_8UC1);
- int nRows = img.rows;
- int nCols = img.cols;
- if (img.isContinuous()) {
- nCols *= nRows;
- nRows = 1;
- }
- int x, y;
- uchar *pAbove;
- uchar *pCurr;
- uchar *pBelow;
- uchar *nw, *no, *ne; // north (pAbove)
- uchar *we, *me, *ea;
- uchar *sw, *so, *se; // south (pBelow)
- uchar *pDst;
- // initialize row pointers
- pAbove = NULL;
- pCurr = img.ptr<uchar>(0);
- pBelow = img.ptr<uchar>(1);
- for (y = 1; y < img.rows - 1; ++y) {
- // shift the rows up by one
- pAbove = pCurr;
- pCurr = pBelow;
- pBelow = img.ptr<uchar>(y + 1);
- pDst = marker.ptr<uchar>(y);
- // initialize col pointers
- no = &(pAbove[0]);
- ne = &(pAbove[1]);
- me = &(pCurr[0]);
- ea = &(pCurr[1]);
- so = &(pBelow[0]);
- se = &(pBelow[1]);
- for (x = 1; x < img.cols - 1; ++x) {
- // shift col pointers left by one (scan left to right)
- nw = no;
- no = ne;
- ne = &(pAbove[x + 1]);
- we = me;
- me = ea;
- ea = &(pCurr[x + 1]);
- sw = so;
- so = se;
- se = &(pBelow[x + 1]);
- int A = (*no == 0 && *ne == 1) + (*ne == 0 && *ea == 1) +
- (*ea == 0 && *se == 1) + (*se == 0 && *so == 1) +
- (*so == 0 && *sw == 1) + (*sw == 0 && *we == 1) +
- (*we == 0 && *nw == 1) + (*nw == 0 && *no == 1);
- int B = *no + *ne + *ea + *se + *so + *sw + *we + *nw;
- int m1 = iter == 0 ? (*no * *ea * *so) : (*no * *ea * *we);
- int m2 = iter == 0 ? (*ea * *so * *we) : (*no * *so * *we);
- if (A == 1 && (B >= 2 && B <= 6) && m1 == 0 && m2 == 0)
- pDst[x] = 1;
- }
- }
- img &= ~marker;
- }
- /**
- * Function for thinning the given binary image
- *
- * Parameters:
- * src The source image, binary with range = [0,255]
- * dst The destination image
- */
- void CTeaSort::thinning(const cv::Mat& src, cv::Mat& dst)
- {
- dst = src.clone();
- dst /= 255; // convert to binary image
- cv::Mat prev = cv::Mat::zeros(dst.size(), CV_8UC1);
- cv::Mat diff;
- do {
- thinningIteration(dst, 0);
- thinningIteration(dst, 1);
- cv::absdiff(dst, prev, diff);
- dst.copyTo(prev);
- } while (cv::countNonZero(diff) > 0);
- dst *= 255;
- }
- }
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