提交 831f9324 编写于 作者: R root

Add polygon score param to config

上级 bc14d8f8
......@@ -49,6 +49,8 @@ public:
this->det_db_unclip_ratio = stod(config_map_["det_db_unclip_ratio"]);
this->use_polygon_score = bool(stoi(config_map_["use_polygon_score"]));
this->det_model_dir.assign(config_map_["det_model_dir"]);
this->rec_model_dir.assign(config_map_["rec_model_dir"]);
......@@ -86,6 +88,8 @@ public:
double det_db_unclip_ratio = 2.0;
bool use_polygon_score = false;
std::string det_model_dir;
std::string rec_model_dir;
......
......@@ -44,7 +44,8 @@ public:
const bool &use_mkldnn, const int &max_side_len,
const double &det_db_thresh,
const double &det_db_box_thresh,
const double &det_db_unclip_ratio, const bool &visualize,
const double &det_db_unclip_ratio,
const bool &use_polygon_score, const bool &visualize,
const bool &use_tensorrt, const bool &use_fp16) {
this->use_gpu_ = use_gpu;
this->gpu_id_ = gpu_id;
......@@ -57,6 +58,7 @@ public:
this->det_db_thresh_ = det_db_thresh;
this->det_db_box_thresh_ = det_db_box_thresh;
this->det_db_unclip_ratio_ = det_db_unclip_ratio;
this->use_polygon_score_ = use_polygon_score;
this->visualize_ = visualize;
this->use_tensorrt_ = use_tensorrt;
......@@ -85,6 +87,7 @@ private:
double det_db_thresh_ = 0.3;
double det_db_box_thresh_ = 0.5;
double det_db_unclip_ratio_ = 2.0;
bool use_polygon_score_ = false;
bool visualize_ = true;
bool use_tensorrt_ = false;
......
......@@ -55,7 +55,8 @@ public:
std::vector<std::vector<std::vector<int>>>
BoxesFromBitmap(const cv::Mat pred, const cv::Mat bitmap,
const float &box_thresh, const float &det_db_unclip_ratio);
const float &box_thresh, const float &det_db_unclip_ratio,
const bool &use_polygon_score);
std::vector<std::vector<std::vector<int>>>
FilterTagDetRes(std::vector<std::vector<std::vector<int>>> boxes,
......
......@@ -59,7 +59,8 @@ int main(int argc, char **argv) {
config.gpu_mem, config.cpu_math_library_num_threads,
config.use_mkldnn, config.max_side_len, config.det_db_thresh,
config.det_db_box_thresh, config.det_db_unclip_ratio,
config.visualize, config.use_tensorrt, config.use_fp16);
config.use_polygon_score, config.visualize,
config.use_tensorrt, config.use_fp16);
Classifier *cls = nullptr;
if (config.use_angle_cls == true) {
......
......@@ -109,9 +109,9 @@ void DBDetector::Run(cv::Mat &img,
cv::Mat dilation_map;
cv::Mat dila_ele = cv::getStructuringElement(cv::MORPH_RECT, cv::Size(2, 2));
cv::dilate(bit_map, dilation_map, dila_ele);
boxes = post_processor_.BoxesFromBitmap(pred_map, dilation_map,
this->det_db_box_thresh_,
this->det_db_unclip_ratio_);
boxes = post_processor_.BoxesFromBitmap(
pred_map, dilation_map, this->det_db_box_thresh_,
this->det_db_unclip_ratio_, this->use_polygon_score_);
boxes = post_processor_.FilterTagDetRes(boxes, ratio_h, ratio_w, srcimg);
......
......@@ -160,26 +160,34 @@ std::vector<std::vector<float>> PostProcessor::GetMiniBoxes(cv::RotatedRect box,
}
float PostProcessor::PolygonScoreAcc(std::vector<cv::Point> contour,
cv::Mat pred){
cv::Mat pred) {
int width = pred.cols;
int height = pred.rows;
std::vector<float> box_x;
std::vector<float> box_y;
for(int i=0; i<contour.size(); ++i){
for (int i = 0; i < contour.size(); ++i) {
box_x.push_back(contour[i].x);
box_y.push_back(contour[i].y);
}
int xmin = clamp(int(std::floor(*(std::min_element(box_x.begin(), box_x.end())))), 0, width - 1);
int xmax = clamp(int(std::ceil(*(std::max_element(box_x.begin(), box_x.end())))), 0, width - 1);
int ymin = clamp(int(std::floor(*(std::min_element(box_y.begin(), box_y.end())))), 0, height - 1);
int ymax = clamp(int(std::ceil(*(std::max_element(box_y.begin(), box_y.end())))), 0, height - 1);
int xmin =
clamp(int(std::floor(*(std::min_element(box_x.begin(), box_x.end())))), 0,
width - 1);
int xmax =
clamp(int(std::ceil(*(std::max_element(box_x.begin(), box_x.end())))), 0,
width - 1);
int ymin =
clamp(int(std::floor(*(std::min_element(box_y.begin(), box_y.end())))), 0,
height - 1);
int ymax =
clamp(int(std::ceil(*(std::max_element(box_y.begin(), box_y.end())))), 0,
height - 1);
cv::Mat mask;
mask = cv::Mat::zeros(ymax - ymin + 1, xmax - xmin + 1, CV_8UC1);
cv::Point rook_point[contour.size()];
for(int i=0; i<contour.size(); ++i){
for (int i = 0; i < contour.size(); ++i) {
rook_point[i] = cv::Point(int(box_x[i]) - xmin, int(box_y[i]) - ymin);
}
const cv::Point *ppt[1] = {rook_point};
......@@ -187,7 +195,8 @@ float PostProcessor::PolygonScoreAcc(std::vector<cv::Point> contour,
cv::fillPoly(mask, ppt, npt, 1, cv::Scalar(1));
cv::Mat croppedImg;
pred(cv::Rect(xmin, ymin, xmax - xmin + 1, ymax - ymin + 1)).copyTo(croppedImg);
pred(cv::Rect(xmin, ymin, xmax - xmin + 1, ymax - ymin + 1))
.copyTo(croppedImg);
float score = cv::mean(croppedImg, mask)[0];
return score;
}
......@@ -230,10 +239,9 @@ float PostProcessor::BoxScoreFast(std::vector<std::vector<float>> box_array,
return score;
}
std::vector<std::vector<std::vector<int>>>
PostProcessor::BoxesFromBitmap(const cv::Mat pred, const cv::Mat bitmap,
const float &box_thresh,
const float &det_db_unclip_ratio) {
std::vector<std::vector<std::vector<int>>> PostProcessor::BoxesFromBitmap(
const cv::Mat pred, const cv::Mat bitmap, const float &box_thresh,
const float &det_db_unclip_ratio, const bool &use_polygon_score) {
const int min_size = 3;
const int max_candidates = 1000;
......@@ -267,9 +275,12 @@ PostProcessor::BoxesFromBitmap(const cv::Mat pred, const cv::Mat bitmap,
}
float score;
score = BoxScoreFast(array, pred);
/* compute using polygon*/
// score = PolygonScoreAcc(contours[_i], pred);
if (use_polygon_score)
/* compute using polygon*/
score = PolygonScoreAcc(contours[_i], pred);
else
score = BoxScoreFast(array, pred);
if (score < box_thresh)
continue;
......
......@@ -10,6 +10,7 @@ max_side_len 960
det_db_thresh 0.3
det_db_box_thresh 0.5
det_db_unclip_ratio 1.6
use_polygon_score 1
det_model_dir ./inference/ch_ppocr_mobile_v2.0_det_infer/
# cls config
......
Markdown is supported
0% .
You are about to add 0 people to the discussion. Proceed with caution.
先完成此消息的编辑!
想要评论请 注册