diff --git a/src/ai_engine_module/RoadSegAnalysis.cpp b/src/ai_engine_module/RoadSegAnalysis.cpp index 989e174..779e5fe 100644 --- a/src/ai_engine_module/RoadSegAnalysis.cpp +++ b/src/ai_engine_module/RoadSegAnalysis.cpp @@ -63,9 +63,9 @@ std::vector RoadSegAnalysis::detect(vector vec_img){ for (int b = 0; b < batchsize; b++) { auto one_result = results[b]; - RoadInfo one_road; - one_road.vec_line = parse_line(one_result, vec_img[b]); - one_road.vec_road = parse_road(one_result, vec_img[b]); + RoadInfo one_road = parse_road(one_result, vec_img[b]); + // one_road.vec_line = parse_line(one_result, vec_img[b]); + // one_road.vec_road = parse_road(one_road, one_result, vec_img[b]); one_road.vec_direct = parse_direct(one_result, vec_img[b]); vec_road_info.push_back(one_road); } @@ -147,14 +147,14 @@ cv::Mat mask_to_rgb(cv::Mat img, cv::Mat mask) { return masks; } -std::vector RoadSegAnalysis::parse_road(rs_result one_result, sy_img src) +RoadInfo RoadSegAnalysis::parse_road(rs_result one_result, sy_img src) { int src_width = src.w_; int src_height = src.h_; float scale_w = src_width / 640.0; float scale_h = src_height / 360.0; - std::vector vec_road; + RoadInfo one_road; std::vector, int>> combined; lanes_process(one_result.reg_array, one_result.lane_count, combined); @@ -167,88 +167,82 @@ std::vector RoadSegAnalysis::parse_road(rs_result one_result, sy_img sr cv::Mat seg_output = seg_post_process(large_resolution, one_result.seg_array, combined, poly_masks, region_classes, lanes, cats, x_sort); //m_masks:mask前的结果 poly_masks后的结果 // cv::Mat image_lane(cv::Size(src_width, src_height), CV_8UC3, cv::Scalar(0, 0, 0)); - // for (int i = 0; i < lanes.size(); ++i) { - // LineInfo info; - // const cv::Scalar color(seg_colors[i][0], seg_colors[i][1], seg_colors[i][2]); - // for (size_t j = 0; j < lanes[i].size(); j++) { - // cv::Point pt; - // pt.x = lanes[i][j].x * scale_w; - // pt.x = lanes[i][j].y * scale_h; - // clip_xy(pt.x, pt.y, src_width, src_height); - // info.vec_pt.push_back(pt); - - // if (j > 0) { - // cv::line(image_lane, info.vec_pt[j-1], info.vec_pt[j], color, 2, 8); - // } + for (int i = 0; i < lanes.size(); ++i) { + LineInfo info; + const cv::Scalar color(seg_colors[i][0], seg_colors[i][1], seg_colors[i][2]); + for (size_t j = 0; j < lanes[i].size(); j++) { + cv::Point pt; + pt.x = lanes[i][j].x * scale_w; + pt.y = lanes[i][j].y * scale_h; + clip_xy(pt.x, pt.y, src_width, src_height); + info.vec_pt.push_back(pt); + + // if (j > 0) { + // cv::line(image_lane, info.vec_pt[j-1], info.vec_pt[j], color, 2, 8); + // } - // } + } - // info.line_type = cats[i]; - // one_road.vec_line.push_back(info); - // } - cv::Mat cvImg(cv::Size(src_width, src_height), CV_8UC3, cv::Scalar(0, 0, 0)); - cv::Mat tmp; - cv::resize(cvImg, tmp, cv::Size(640,360), 0, 0, cv::INTER_LINEAR); - cv::Mat vis_image = mask_to_rgb(tmp, seg_output); - cv::imwrite("./image_lane.jpg", vis_image); - seg_output.release(); - cvImg.release(); + info.line_type = cats[i]; + one_road.vec_line.push_back(info); + } + + // cv::imwrite("./image_lane.jpg", image_lane); + // seg_output.release(); + // image_lane.release(); - cv::Mat image(cv::Size(src_width, src_height), CV_8UC3, cv::Scalar(0, 0, 0)); + // cv::Mat image(cv::Size(src_width, src_height), CV_8UC3, cv::Scalar(0, 0, 0)); for (int i = 0; i < poly_masks.size(); ++i) { SegInfo seg_info; for (size_t j = 0; j < poly_masks[i].size(); j++) { cv::Point pt; pt.x = poly_masks[i][j].x * scale_w; - pt.x = poly_masks[i][j].y * scale_h; + pt.y = poly_masks[i][j].y * scale_h; clip_xy(pt.x, pt.y, src_width, src_height); seg_info.vec_pt.push_back(pt); } seg_info.seg_type = region_classes[i]; - vec_road.push_back(seg_info); + one_road.vec_road.push_back(seg_info); - int k = seg_info.seg_type; - const cv::Scalar color(seg_colors[k][0], seg_colors[k][1], seg_colors[k][2]); - polylines(image, seg_info.vec_pt, true, color, 3, cv::LINE_AA); + // int k = seg_info.seg_type; + // const cv::Scalar color(seg_colors[k][0], seg_colors[k][1], seg_colors[k][2]); + // polylines(image, seg_info.vec_pt, true, color, 3, cv::LINE_AA); } - cv::imwrite("./image_road.jpg", image); - image.release(); + // cv::imwrite("./image_road.jpg", image); + // image.release(); - return vec_road; + return one_road; } std::vector RoadSegAnalysis::parse_direct(rs_result one_result, sy_img src) { - std::vector, int>> combined; - lanes_process(one_result.reg_array, one_result.lane_count, combined); - std::vector> poly_masks, lanes; - std::vector region_classes, cats; - std::map x_sort; + + std::vector> direct_masks; + std::vector direct_classes; bool large_resolution = false; if (src.w_ > 1920) large_resolution = true; - - cv::Mat seg_output = seg_post_process(large_resolution, one_result.direct_seg, combined, poly_masks, region_classes, lanes, cats, x_sort); //m_masks:mask前的结果 poly_masks后的结果 + cv::Mat direct_output = direct_post_process(large_resolution, one_result.direct_seg, direct_masks, direct_classes); - cv::Mat image(cv::Size(640, 360), CV_8UC3, cv::Scalar(0, 0, 0)); + // cv::Mat image(cv::Size(640, 360), CV_8UC3, cv::Scalar(0, 0, 0)); std::vector vec_road; - for (int i = 0; i < poly_masks.size(); ++i) { + for (int i = 0; i < direct_masks.size(); ++i) { SegInfo seg_info; - seg_info.seg_type = region_classes[i]; - seg_info.vec_pt = poly_masks[i]; + seg_info.seg_type = direct_classes[i]; + seg_info.vec_pt = direct_masks[i]; vec_road.push_back(seg_info); - int k = seg_info.seg_type; - const cv::Scalar color(seg_colors[k][0], seg_colors[k][1], seg_colors[k][2]); - polylines(image, seg_info.vec_pt, true, color, 3, cv::LINE_AA); + // int k = seg_info.seg_type; + // const cv::Scalar color(seg_colors[k][0], seg_colors[k][1], seg_colors[k][2]); + // polylines(image, seg_info.vec_pt, true, color, 3, cv::LINE_AA); } - cv::imwrite("./image_direct.jpg", image); - image.release(); + // cv::imwrite("./image_direct.jpg", image); + // image.release(); return vec_road; } @@ -679,4 +673,64 @@ cv::Mat RoadSegAnalysis::seg_post_process(bool large_resolution, unsigned char * } #endif return mask_rmlane; -} \ No newline at end of file +} + +cv::Mat RoadSegAnalysis::direct_post_process(bool large_resolution, unsigned char *direct_array, std::vector> &poly_masks, std::vector ®ion_classes) { + std::vector pred_cls; + int h = 360, w = 640, step_size = h*w, seg_min_region_area = 512; + cv::Mat mask_rmlane = cv::Mat_(h,w); //车道线区域置为背景 + for (int i = 0; i < h; ++i) { + for (int j = 0; j < w; ++j) { + int max_cls = direct_array[(i * w + j)]; + pred_cls.push_back(max_cls); + mask_rmlane.ptr(i)[j] = max_cls; + } + } + +#if 1 /*mask远处区域*/ + cv::Mat mask_black = mask_rmlane.clone(); + if (large_resolution) mask_black(cv::Rect(0, 0, w, int(h * 0.14))) = 0; + else mask_black(cv::Rect(0, 0, w, int(h * 0.22))) = 0; + mask_black(cv::Rect(0, int(h * 0.95), w, int(h * 0.05))) = 0; + mask_black(cv::Rect(0, 0, int(w * 0.02), h)) = 0; + mask_black(cv::Rect(int(w * 0.95), 0, int(w * 0.05), h)) = 0; + mask_rmlane = mask_black; +#endif + //去重获取预测到的类别 + std::vector labels(pred_cls); + std::sort(labels.begin(),labels.end()); + labels.erase(std::unique(labels.begin(),labels.end()),labels.end()); + + //求道路区域 + for(auto cat: labels) { + cv::Mat b_masks, measure_labels, stats, centroids; + cv::Mat n_masks = cv::Mat_(h,w); n_masks = cv::Scalar(255); + cv::compare(mask_rmlane, cat, b_masks, cv::CMP_EQ); //将mask_rmlane元素逐个和cat比较，相同255，不同0 + //连通域计算 + int nccomps = cv::connectedComponentsWithStats (b_masks, measure_labels, stats, centroids, 8); + for(int i = 1; i < nccomps; i++ ) { //跳过背景信息0 + if (stats.at(i, cv::CC_STAT_AREA) < seg_min_region_area) { //移除过小的区域，并将对应位置置为0 + cv::Mat comparison_result; + cv::compare(measure_labels, cv::Scalar(i), comparison_result, cv::CMP_EQ); //相等为255不等为0 + n_masks.setTo(0, comparison_result); // 将comparison_result中非零区域置为0 + cv::bitwise_and(mask_rmlane,n_masks,mask_rmlane); + continue; + } + + cv::Mat region_mask; + cv::bitwise_and(measure_labels,n_masks,measure_labels);///// + cv::compare(measure_labels, i, region_mask, cv::CMP_EQ); + + std::vector> contours; + cv::findContours(region_mask,contours,cv::noArray(),cv::RETR_TREE,cv::CHAIN_APPROX_SIMPLE); + std::vector contours_poly; + for (int j = 0; j < contours.size();j++) { + cv::approxPolyDP(cv::Mat(contours[j]), contours_poly, 10, true); + if (contours_poly.size() <= 2) continue; + poly_masks.push_back(contours_poly); + region_classes.push_back(cat); + } + } + } + return mask_rmlane; +} diff --git a/src/ai_engine_module/RoadSegAnalysis.h b/src/ai_engine_module/RoadSegAnalysis.h index 3d665d7..7d734db 100644 --- a/src/ai_engine_module/RoadSegAnalysis.h +++ b/src/ai_engine_module/RoadSegAnalysis.h @@ -33,7 +33,7 @@ private: std::vector parse_line(rs_result one_result, sy_img src); - std::vector parse_road(rs_result one_result, sy_img src); + RoadInfo parse_road(rs_result one_result, sy_img src); std::vector parse_direct(rs_result one_result, sy_img src); @@ -47,6 +47,8 @@ private: int Mask2LanePoints(const cv::Mat& pred, std::vector>&lanes, std::vector& cats); cv::Mat seg_post_process(bool large_resolution, unsigned char *seg_array, std::vector, int>> combined, std::vector> &poly_masks, std::vector ®ion_classes, std::vector> &lanes, std::vector &cats, std::map &x_sort); + cv::Mat direct_post_process(bool large_resolution, unsigned char *direct_array, std::vector> &poly_masks, std::vector ®ion_classes); + private: void* m_handle{nullptr}; aclrtContext ctx{nullptr};