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Code Issues Actions 2 Packages Projects Releases Wiki Activity

Fix Diff & Improve OCR readme (#184)

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* Add PaddleOCR Support

* Add PaddleOCR Support

* Add PaddleOCRv3 Support

* Add PaddleOCRv3 Support

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* Add PaddleOCRv3 Support

* Add PaddleOCRv3 Supports

* Add PaddleOCRv3 Suport

* Fix Rec diff

* Remove useless functions

* Remove useless comments

* Add PaddleOCRv2 Support

* Add PaddleOCRv3 & PaddleOCRv2 Support

* remove useless parameters

* Add utils of sorting det boxes

* Fix code naming convention

* Fix code naming convention

* Fix code naming convention

* Fix bug in the Classify process

* Imporve OCR Readme

* Fix diff in Cls model

* Update Model Download Link in Readme
This commit is contained in:
yunyaoXYY
2022-09-05 09:36:06 +08:00
committed by GitHub
parent 5f880dcdd0
commit fad82b4e5d
9 changed files with 46 additions and 53 deletions
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54
csrc/fastdeploy/vision/ocr/ppocr/utils/ocr_postprocess_op.cc
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@@ -250,9 +250,8 @@ float PostProcessor::BoxScoreFast(std::vector<std::vector<float>> box_array,
//这个应该是DB（差分二值化）相关的内容，方法从 Bitmap 图中获取检测框
//涉及到box_thresh（低于这个阈值的boxs不予显示）和det_db_unclip_ratio（文本框扩张的系数，关系到文本框的大小）
void PostProcessor::BoxesFromBitmap(
const cv::Mat pred, std::vector<std::vector<std::vector<int>>> *boxes,
const cv::Mat bitmap, const float &box_thresh,
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 std::string &det_db_score_mode) {
const int min_size = 3;
const int max_candidates = 1000;
@@ -269,6 +268,8 @@ void PostProcessor::BoxesFromBitmap(
int num_contours =
contours.size() >= max_candidates ? max_candidates : contours.size();
std::vector<std::vector<std::vector<int>>> boxes;
for (int _i = 0; _i < num_contours; _i++) {
if (contours[_i].size() <= 2) {
continue;
@@ -318,45 +319,42 @@ void PostProcessor::BoxesFromBitmap(
0, float(dest_height)))};
intcliparray.push_back(a);
}
boxes->push_back(intcliparray);
boxes.push_back(intcliparray);
} // end for
// return true;
return boxes;
}
//方法根据识别结果获取目标框位置
void PostProcessor::FilterTagDetRes(
std::vector<std::vector<std::vector<int>>> *boxes, const float ratio_h,
const float ratio_w,
const std::map<std::string, std::array<float, 2>> &im_info) {
std::vector<std::vector<std::vector<int>>> PostProcessor::FilterTagDetRes(
std::vector<std::vector<std::vector<int>>> boxes, float ratio_h,
float ratio_w, const std::map<std::string, std::array<float, 2>> &im_info) {
int oriimg_h = im_info.at("input_shape")[0];
int oriimg_w = im_info.at("input_shape")[1];
for (int n = 0; n < boxes->size(); n++) {
(*boxes)[n] = OrderPointsClockwise((*boxes)[n]);
for (int m = 0; m < (*boxes)[0].size(); m++) {
(*boxes)[n][m][0] /= ratio_w;
(*boxes)[n][m][1] /= ratio_h;
std::vector<std::vector<std::vector<int>>> root_points;
for (int n = 0; n < boxes.size(); n++) {
boxes[n] = OrderPointsClockwise(boxes[n]);
for (int m = 0; m < boxes[0].size(); m++) {
boxes[n][m][0] /= ratio_w;
boxes[n][m][1] /= ratio_h;
(*boxes)[n][m][0] = int(_min(_max((*boxes)[n][m][0], 0), oriimg_w - 1));
(*boxes)[n][m][1] = int(_min(_max((*boxes)[n][m][1], 0), oriimg_h - 1));
boxes[n][m][0] = int(_min(_max(boxes[n][m][0], 0), oriimg_w - 1));
boxes[n][m][1] = int(_min(_max(boxes[n][m][1], 0), oriimg_h - 1));
}
}
//此时已经拿到所有的点. 再进行下面的筛选
for (int n = (*boxes).size() - 1; n >= 0; n--) {
for (int n = 0; n < boxes.size(); n++) {
int rect_width, rect_height;
rect_width = int(sqrt(pow((*boxes)[n][0][0] - (*boxes)[n][1][0], 2) +
pow((*boxes)[n][0][1] - (*boxes)[n][1][1], 2)));
rect_height = int(sqrt(pow((*boxes)[n][0][0] - (*boxes)[n][3][0], 2) +
pow((*boxes)[n][0][1] - (*boxes)[n][3][1], 2)));
//小于4的删除掉. erase配合逆序遍历.
if (rect_width <= 4 || rect_height <= 4) {
boxes->erase(boxes->begin() + n);
}
rect_width = int(sqrt(pow(boxes[n][0][0] - boxes[n][1][0], 2) +
pow(boxes[n][0][1] - boxes[n][1][1], 2)));
rect_height = int(sqrt(pow(boxes[n][0][0] - boxes[n][3][0], 2) +
pow(boxes[n][0][1] - boxes[n][3][1], 2)));
if (rect_width <= 4 || rect_height <= 4) continue;
root_points.push_back(boxes[n]);
}
return root_points;
}
} // namespace ocr
} // namespace vision
} // namespace fastdeploy

14
csrc/fastdeploy/vision/ocr/ppocr/utils/ocr_postprocess_op.h
View File

@@ -52,15 +52,13 @@ class PostProcessor {
float BoxScoreFast(std::vector<std::vector<float>> box_array, cv::Mat pred);
float PolygonScoreAcc(std::vector<cv::Point> contour, cv::Mat pred);
void BoxesFromBitmap(const cv::Mat pred,
std::vector<std::vector<std::vector<int>>> *boxes,
const cv::Mat bitmap, const float &box_thresh,
const float &det_db_unclip_ratio,
const std::string &det_db_score_mode);
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 std::string &det_db_score_mode);
void FilterTagDetRes(
std::vector<std::vector<std::vector<int>>> *boxes, const float ratio_h,
const float ratio_w,
std::vector<std::vector<std::vector<int>>> FilterTagDetRes(
std::vector<std::vector<std::vector<int>>> boxes, float ratio_h,
float ratio_w,
const std::map<std::string, std::array<float, 2>> &im_info);
private: