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Code Issues Actions 2 Packages Projects Releases Wiki Activity

Add PaddleOCRv3 & PaddleOCRv2 Support (#169)

Browse Source 
* 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
This commit is contained in:
yunyaoXYY
2022-08-29 19:19:36 +08:00
committed by GitHub
parent cab8e408fa
commit 00e3a4ad99
15 changed files with 91 additions and 109 deletions
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14
csrc/fastdeploy/vision/common/result.cc
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@@ -319,11 +319,11 @@ std::string OCRResult::Str() {
out = out + "]"; out = out + "]";
if (rec_scores.size() > 0) { if (rec_scores.size() > 0) {
out = out + "rec text: " + text[n] + " rec scores:" + out = out + "rec text: " + text[n] + " rec score:" +
std::to_string(rec_scores[n]) + " "; std::to_string(rec_scores[n]) + " ";
} }
if (cls_label.size() > 0) { if (cls_labels.size() > 0) {
out = out + "cls label: " + std::to_string(cls_label[n]) + out = out + "cls label: " + std::to_string(cls_labels[n]) +
" cls score: " + std::to_string(cls_scores[n]); " cls score: " + std::to_string(cls_scores[n]);
} }
out = out + "\n"; out = out + "\n";
@@ -334,9 +334,9 @@ std::string OCRResult::Str() {
cls_scores.size() > 0) { cls_scores.size() > 0) {
std::string out; std::string out;
for (int i = 0; i < rec_scores.size(); i++) { for (int i = 0; i < rec_scores.size(); i++) {
out = out + "rec text: " + text[i] + " rec scores:" + out = out + "rec text: " + text[i] + " rec score:" +
std::to_string(rec_scores[i]) + " "; std::to_string(rec_scores[i]) + " ";
out = out + "cls label: " + std::to_string(cls_label[i]) + out = out + "cls label: " + std::to_string(cls_labels[i]) +
" cls score: " + std::to_string(cls_scores[i]); " cls score: " + std::to_string(cls_scores[i]);
out = out + "\n"; out = out + "\n";
} }
@@ -345,7 +345,7 @@ std::string OCRResult::Str() {
cls_scores.size() > 0) { cls_scores.size() > 0) {
std::string out; std::string out;
for (int i = 0; i < cls_scores.size(); i++) { for (int i = 0; i < cls_scores.size(); i++) {
out = out + "cls label: " + std::to_string(cls_label[i]) + out = out + "cls label: " + std::to_string(cls_labels[i]) +
" cls score: " + std::to_string(cls_scores[i]); " cls score: " + std::to_string(cls_scores[i]);
out = out + "\n"; out = out + "\n";
} }
@@ -354,7 +354,7 @@ std::string OCRResult::Str() {
cls_scores.size() == 0) { cls_scores.size() == 0) {
std::string out; std::string out;
for (int i = 0; i < rec_scores.size(); i++) { for (int i = 0; i < rec_scores.size(); i++) {
out = out + "rec text: " + text[i] + " rec scores:" + out = out + "rec text: " + text[i] + " rec score:" +
std::to_string(rec_scores[i]) + " "; std::to_string(rec_scores[i]) + " ";
out = out + "\n"; out = out + "\n";
} }

2
csrc/fastdeploy/vision/common/result.h
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@@ -67,7 +67,7 @@ struct FASTDEPLOY_DECL OCRResult : public BaseResult {
std::vector<float> rec_scores; std::vector<float> rec_scores;
std::vector<float> cls_scores; std::vector<float> cls_scores;
std::vector<int32_t> cls_label; std::vector<int32_t> cls_labels;
ResultType type = ResultType::OCR; ResultType type = ResultType::OCR;

12
csrc/fastdeploy/vision/ocr/ppocr/classifier.cc
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@@ -99,8 +99,8 @@ bool Classifier::Preprocess(Mat* mat, FDTensor* output) {
} }
//后处理 //后处理
bool Classifier::Postprocess(FDTensor& infer_result, int& cls_labels, bool Classifier::Postprocess(FDTensor& infer_result,
float& cls_scores) { std::tuple<int, float>* cls_result) {
std::vector<int64_t> output_shape = infer_result.shape; std::vector<int64_t> output_shape = infer_result.shape;
FDASSERT(output_shape[0] == 1, "Only support batch =1 now."); FDASSERT(output_shape[0] == 1, "Only support batch =1 now.");
@@ -112,14 +112,14 @@ bool Classifier::Postprocess(FDTensor& infer_result, int& cls_labels,
float score = float score =
float(*std::max_element(&out_data[0], &out_data[output_shape[1]])); float(*std::max_element(&out_data[0], &out_data[output_shape[1]]));
cls_labels = label; std::get<0>(*cls_result) = label;
cls_scores = score; std::get<1>(*cls_result) = score;
return true; return true;
} }
//预测 //预测
bool Classifier::Predict(cv::Mat* img, int& cls_labels, float& cls_socres) { bool Classifier::Predict(cv::Mat* img, std::tuple<int, float>* cls_result) {
Mat mat(*img); Mat mat(*img);
std::vector<FDTensor> input_tensors(1); std::vector<FDTensor> input_tensors(1);
@@ -135,7 +135,7 @@ bool Classifier::Predict(cv::Mat* img, int& cls_labels, float& cls_socres) {
return false; return false;
} }
if (!Postprocess(output_tensors[0], cls_labels, cls_socres)) { if (!Postprocess(output_tensors[0], cls_result)) {
FDERROR << "Failed to post process." << std::endl; FDERROR << "Failed to post process." << std::endl;
return false; return false;
} }

4
csrc/fastdeploy/vision/ocr/ppocr/classifier.h
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@@ -35,7 +35,7 @@ class FASTDEPLOY_DECL Classifier : public FastDeployModel {
std::string ModelName() const { return "ppocr/ocr_cls"; } std::string ModelName() const { return "ppocr/ocr_cls"; }
// 模型预测接口，即用户调用的接口 // 模型预测接口，即用户调用的接口
virtual bool Predict(cv::Mat* img, int& cls_labels, float& cls_socres); virtual bool Predict(cv::Mat* img, std::tuple<int, float>* result);
// pre & post parameters // pre & post parameters
float cls_thresh; float cls_thresh;
@@ -56,7 +56,7 @@ class FASTDEPLOY_DECL Classifier : public FastDeployModel {
// 后端推理结果后处理，输出给用户 // 后端推理结果后处理，输出给用户
// infer_result 为后端推理后的输出Tensor // infer_result 为后端推理后的输出Tensor
bool Postprocess(FDTensor& infer_result, int& cls_labels, float& cls_scores); bool Postprocess(FDTensor& infer_result, std::tuple<int, float>* result);
}; };
} // namespace ocr } // namespace ocr

36
csrc/fastdeploy/vision/ocr/ppocr/dbdetector.cc
View File

@@ -63,8 +63,8 @@ bool DBDetector::Initialize() {
return true; return true;
} }
void OcrDetectorResizeImage(Mat* img, int max_size_len, float& ratio_h, void OcrDetectorResizeImage(Mat* img, int max_size_len, float* ratio_h,
float& ratio_w) { float* ratio_w) {
int w = img->Width(); int w = img->Width();
int h = img->Height(); int h = img->Height();
@@ -86,8 +86,8 @@ void OcrDetectorResizeImage(Mat* img, int max_size_len, float& ratio_h,
Resize::Run(img, resize_w, resize_h); Resize::Run(img, resize_w, resize_h);
ratio_h = float(resize_h) / float(h); *ratio_h = float(resize_h) / float(h);
ratio_w = float(resize_w) / float(w); *ratio_w = float(resize_w) / float(w);
} }
//预处理 //预处理
@@ -95,7 +95,7 @@ bool DBDetector::Preprocess(
Mat* mat, FDTensor* output, Mat* mat, FDTensor* output,
std::map<std::string, std::array<float, 2>>* im_info) { std::map<std::string, std::array<float, 2>>* im_info) {
// Resize // Resize
OcrDetectorResizeImage(mat, max_side_len, ratio_h, ratio_w); OcrDetectorResizeImage(mat, max_side_len, &ratio_h, &ratio_w);
// Normalize // Normalize
Normalize::Run(mat, mean, scale, true); Normalize::Run(mat, mean, scale, true);
@@ -112,7 +112,7 @@ bool DBDetector::Preprocess(
//后处理 //后处理
bool DBDetector::Postprocess( bool DBDetector::Postprocess(
FDTensor& infer_result, std::vector<std::vector<std::vector<int>>>* boxes, FDTensor& infer_result, std::vector<std::array<int, 8>>* boxes_result,
const std::map<std::string, std::array<float, 2>>& im_info) { const std::map<std::string, std::array<float, 2>>& im_info) {
std::vector<int64_t> output_shape = infer_result.shape; std::vector<int64_t> output_shape = infer_result.shape;
FDASSERT(output_shape[0] == 1, "Only support batch =1 now."); FDASSERT(output_shape[0] == 1, "Only support batch =1 now.");
@@ -142,17 +142,33 @@ bool DBDetector::Postprocess(
cv::dilate(bit_map, bit_map, dila_ele); cv::dilate(bit_map, bit_map, dila_ele);
} }
post_processor_.BoxesFromBitmap(pred_map, boxes, bit_map, det_db_box_thresh, // boxes_result 的value，传给boxes
std::vector<std::vector<std::vector<int>>> boxes;
post_processor_.BoxesFromBitmap(pred_map, &boxes, bit_map, det_db_box_thresh,
det_db_unclip_ratio, det_db_score_mode); det_db_unclip_ratio, det_db_score_mode);
post_processor_.FilterTagDetRes(boxes, ratio_h, ratio_w, im_info); post_processor_.FilterTagDetRes(&boxes, ratio_h, ratio_w, im_info);
// boxes to boxes_result
for (int i = 0; i < boxes.size(); i++) {
std::array<int, 8> new_box;
int k = 0;
for (auto& vec : boxes[i]) {
for (auto& e : vec) {
new_box[k++] = e;
}
}
boxes_result->push_back(new_box);
}
return true; return true;
} }
//预测 //预测
bool DBDetector::Predict( bool DBDetector::Predict(cv::Mat* img,
cv::Mat* img, std::vector<std::vector<std::vector<int>>>* boxes_result) { std::vector<std::array<int, 8>>* boxes_result) {
Mat mat(*img); Mat mat(*img);
std::vector<FDTensor> input_tensors(1); std::vector<FDTensor> input_tensors(1);

4
csrc/fastdeploy/vision/ocr/ppocr/dbdetector.h
View File

@@ -35,7 +35,7 @@ class FASTDEPLOY_DECL DBDetector : public FastDeployModel {
// 模型预测接口，即用户调用的接口 // 模型预测接口，即用户调用的接口
virtual bool Predict(cv::Mat* im, virtual bool Predict(cv::Mat* im,
std::vector<std::vector<std::vector<int>>>* boxes); std::vector<std::array<int, 8>>* boxes_result);
// pre&post process parameters // pre&post process parameters
int max_side_len; int max_side_len;
@@ -64,7 +64,7 @@ class FASTDEPLOY_DECL DBDetector : public FastDeployModel {
// 后端推理结果后处理，输出给用户 // 后端推理结果后处理，输出给用户
bool Postprocess(FDTensor& infer_result, bool Postprocess(FDTensor& infer_result,
std::vector<std::vector<std::vector<int>>>* boxes, std::vector<std::array<int, 8>>* boxes_result,
const std::map<std::string, std::array<float, 2>>& im_info); const std::map<std::string, std::array<float, 2>>& im_info);
// OCR后处理类 // OCR后处理类

41
csrc/fastdeploy/vision/ocr/ppocr/ppocr_system_v2.cc
View File

@@ -26,45 +26,31 @@ PPOCRSystemv2::PPOCRSystemv2(fastdeploy::vision::ocr::DBDetector* ocr_det,
void PPOCRSystemv2::Detect(cv::Mat* img, void PPOCRSystemv2::Detect(cv::Mat* img,
fastdeploy::vision::OCRResult* result) { fastdeploy::vision::OCRResult* result) {
std::vector<std::vector<std::vector<int>>> boxes; std::vector<std::array<int, 8>> boxes;
this->detector->Predict(img, &boxes); this->detector->Predict(img, &boxes);
// vector<vector>转array result->boxes = boxes;
for (int i = 0; i < boxes.size(); i++) {
std::array<int, 8> new_box;
int k = 0;
for (auto& vec : boxes[i]) {
for (auto& e : vec) {
new_box[k++] = e;
}
}
(result->boxes).push_back(new_box);
}
} }
void PPOCRSystemv2::Recognize(cv::Mat* img, void PPOCRSystemv2::Recognize(cv::Mat* img,
fastdeploy::vision::OCRResult* result) { fastdeploy::vision::OCRResult* result) {
std::string rec_texts = ""; std::tuple<std::string, float> rec_result;
float rec_text_scores = 0;
this->recognizer->rec_image_shape[1] = this->recognizer->Predict(img, &rec_result);
32; // OCRv2模型此处需要设置为32，其他与OCRv3一致
this->recognizer->Predict(img, rec_texts, rec_text_scores);
result->text.push_back(rec_texts); result->text.push_back(std::get<0>(rec_result));
result->rec_scores.push_back(rec_text_scores); result->rec_scores.push_back(std::get<1>(rec_result));
} }
void PPOCRSystemv2::Classify(cv::Mat* img, void PPOCRSystemv2::Classify(cv::Mat* img,
fastdeploy::vision::OCRResult* result) { fastdeploy::vision::OCRResult* result) {
int cls_label = 0; std::tuple<int, float> cls_result;
float cls_scores = 0;
this->classifier->Predict(img, cls_label, cls_scores); this->classifier->Predict(img, &cls_result);
result->cls_label.push_back(cls_label); result->cls_labels.push_back(std::get<0>(cls_result));
result->cls_scores.push_back(cls_scores); result->cls_scores.push_back(std::get<1>(cls_result));
} }
bool PPOCRSystemv2::Predict(cv::Mat* img, bool PPOCRSystemv2::Predict(cv::Mat* img,
@@ -74,7 +60,7 @@ bool PPOCRSystemv2::Predict(cv::Mat* img,
if (this->classifier->initialized != 0) { if (this->classifier->initialized != 0) {
this->Classify(img, result); this->Classify(img, result);
//摆正单张图像 //摆正单张图像
if ((result->cls_label)[0] % 2 == 1 && if ((result->cls_labels)[0] % 2 == 1 &&
(result->cls_scores)[0] > this->classifier->cls_thresh) { (result->cls_scores)[0] > this->classifier->cls_thresh) {
cv::rotate(*img, *img, 1); cv::rotate(*img, *img, 1);
} }
@@ -88,7 +74,6 @@ bool PPOCRSystemv2::Predict(cv::Mat* img,
//从DET模型开始 //从DET模型开始
//一张图,会输出多个“小图片”，送给后续模型 //一张图,会输出多个“小图片”，送给后续模型
this->Detect(img, result); this->Detect(img, result);
std::cout << "Finish Det Prediction!" << std::endl;
// crop image // crop image
std::vector<cv::Mat> img_list; std::vector<cv::Mat> img_list;
@@ -105,20 +90,18 @@ bool PPOCRSystemv2::Predict(cv::Mat* img,
} }
for (int i = 0; i < img_list.size(); i++) { for (int i = 0; i < img_list.size(); i++) {
if ((result->cls_label)[i] % 2 == 1 && if ((result->cls_labels)[i] % 2 == 1 &&
(result->cls_scores)[i] > this->classifier->cls_thresh) { (result->cls_scores)[i] > this->classifier->cls_thresh) {
std::cout << "Rotate this image " << std::endl; std::cout << "Rotate this image " << std::endl;
cv::rotate(img_list[i], img_list[i], 1); cv::rotate(img_list[i], img_list[i], 1);
} }
} }
std::cout << "Finish Cls Prediction!" << std::endl;
} }
// rec // rec
if (this->recognizer->initialized != 0) { if (this->recognizer->initialized != 0) {
for (int i = 0; i < img_list.size(); i++) { for (int i = 0; i < img_list.size(); i++) {
this->Recognize(&img_list[i], result); this->Recognize(&img_list[i], result);
} }
std::cout << "Finish Rec Prediction!" << std::endl;
} }
} }

41
csrc/fastdeploy/vision/ocr/ppocr/ppocr_system_v3.cc
View File

@@ -26,43 +26,31 @@ PPOCRSystemv3::PPOCRSystemv3(fastdeploy::vision::ocr::DBDetector* ocr_det,
void PPOCRSystemv3::Detect(cv::Mat* img, void PPOCRSystemv3::Detect(cv::Mat* img,
fastdeploy::vision::OCRResult* result) { fastdeploy::vision::OCRResult* result) {
std::vector<std::vector<std::vector<int>>> boxes; std::vector<std::array<int, 8>> boxes_result;
this->detector->Predict(img, &boxes); this->detector->Predict(img, &boxes_result);
// vector<vector>转array result->boxes = boxes_result;
for (int i = 0; i < boxes.size(); i++) {
std::array<int, 8> new_box;
int k = 0;
for (auto& vec : boxes[i]) {
for (auto& e : vec) {
new_box[k++] = e;
}
}
(result->boxes).push_back(new_box);
}
} }
void PPOCRSystemv3::Recognize(cv::Mat* img, void PPOCRSystemv3::Recognize(cv::Mat* img,
fastdeploy::vision::OCRResult* result) { fastdeploy::vision::OCRResult* result) {
std::string rec_texts = ""; std::tuple<std::string, float> rec_result;
float rec_text_scores = 0;
this->recognizer->Predict(img, rec_texts, rec_text_scores); this->recognizer->Predict(img, &rec_result);
result->text.push_back(rec_texts); result->text.push_back(std::get<0>(rec_result));
result->rec_scores.push_back(rec_text_scores); result->rec_scores.push_back(std::get<1>(rec_result));
} }
void PPOCRSystemv3::Classify(cv::Mat* img, void PPOCRSystemv3::Classify(cv::Mat* img,
fastdeploy::vision::OCRResult* result) { fastdeploy::vision::OCRResult* result) {
int cls_label = 0; std::tuple<int, float> cls_result;
float cls_scores = 0;
this->classifier->Predict(img, cls_label, cls_scores); this->classifier->Predict(img, &cls_result);
result->cls_label.push_back(cls_label); result->cls_labels.push_back(std::get<0>(cls_result));
result->cls_scores.push_back(cls_scores); result->cls_scores.push_back(std::get<1>(cls_result));
} }
bool PPOCRSystemv3::Predict(cv::Mat* img, bool PPOCRSystemv3::Predict(cv::Mat* img,
@@ -72,7 +60,7 @@ bool PPOCRSystemv3::Predict(cv::Mat* img,
if (this->classifier->initialized != 0) { if (this->classifier->initialized != 0) {
this->Classify(img, result); this->Classify(img, result);
//摆正单张图像 //摆正单张图像
if ((result->cls_label)[0] % 2 == 1 && if ((result->cls_labels)[0] % 2 == 1 &&
(result->cls_scores)[0] > this->classifier->cls_thresh) { (result->cls_scores)[0] > this->classifier->cls_thresh) {
cv::rotate(*img, *img, 1); cv::rotate(*img, *img, 1);
} }
@@ -86,7 +74,6 @@ bool PPOCRSystemv3::Predict(cv::Mat* img,
//从DET模型开始 //从DET模型开始
//一张图,会输出多个“小图片”，送给后续模型 //一张图,会输出多个“小图片”，送给后续模型
this->Detect(img, result); this->Detect(img, result);
std::cout << "Finish Det Prediction!" << std::endl;
// crop image // crop image
std::vector<cv::Mat> img_list; std::vector<cv::Mat> img_list;
@@ -103,20 +90,18 @@ bool PPOCRSystemv3::Predict(cv::Mat* img,
} }
for (int i = 0; i < img_list.size(); i++) { for (int i = 0; i < img_list.size(); i++) {
if ((result->cls_label)[i] % 2 == 1 && if ((result->cls_labels)[i] % 2 == 1 &&
(result->cls_scores)[i] > this->classifier->cls_thresh) { (result->cls_scores)[i] > this->classifier->cls_thresh) {
std::cout << "Rotate this image " << std::endl; std::cout << "Rotate this image " << std::endl;
cv::rotate(img_list[i], img_list[i], 1); cv::rotate(img_list[i], img_list[i], 1);
} }
} }
std::cout << "Finish Cls Prediction!" << std::endl;
} }
// rec // rec
if (this->recognizer->initialized != 0) { if (this->recognizer->initialized != 0) {
for (int i = 0; i < img_list.size(); i++) { for (int i = 0; i < img_list.size(); i++) {
this->Recognize(&img_list[i], result); this->Recognize(&img_list[i], result);
} }
std::cout << "Finish Rec Prediction!" << std::endl;
} }
} }

16
csrc/fastdeploy/vision/ocr/ppocr/recognizer.cc
View File

@@ -89,7 +89,7 @@ bool Recognizer::Initialize() {
return true; return true;
} }
void OcrRecognizerResizeImage(Mat* mat, float wh_ratio, void OcrRecognizerResizeImage(Mat* mat, const float& wh_ratio,
const std::vector<int>& rec_image_shape) { const std::vector<int>& rec_image_shape) {
int imgC, imgH, imgW; int imgC, imgH, imgW;
imgC = rec_image_shape[0]; imgC = rec_image_shape[0];
@@ -135,8 +135,8 @@ bool Recognizer::Preprocess(Mat* mat, FDTensor* output,
} }
//后处理 //后处理
bool Recognizer::Postprocess(FDTensor& infer_result, std::string& rec_texts, bool Recognizer::Postprocess(FDTensor& infer_result,
float& rec_text_scores) { std::tuple<std::string, float>* rec_result) {
std::vector<int64_t> output_shape = infer_result.shape; std::vector<int64_t> output_shape = infer_result.shape;
FDASSERT(output_shape[0] == 1, "Only support batch =1 now."); FDASSERT(output_shape[0] == 1, "Only support batch =1 now.");
@@ -168,15 +168,15 @@ bool Recognizer::Postprocess(FDTensor& infer_result, std::string& rec_texts,
score /= count; score /= count;
rec_texts = str_res; std::get<0>(*rec_result) = str_res;
rec_text_scores = score; std::get<1>(*rec_result) = score;
return true; return true;
} }
//预测 //预测
bool Recognizer::Predict(cv::Mat* img, std::string& rec_texts, bool Recognizer::Predict(cv::Mat* img,
float& rec_text_scores) { std::tuple<std::string, float>* rec_result) {
Mat mat(*img); Mat mat(*img);
std::vector<FDTensor> input_tensors(1); std::vector<FDTensor> input_tensors(1);
@@ -194,7 +194,7 @@ bool Recognizer::Predict(cv::Mat* img, std::string& rec_texts,
return false; return false;
} }
if (!Postprocess(output_tensors[0], rec_texts, rec_text_scores)) { if (!Postprocess(output_tensors[0], rec_result)) {
FDERROR << "Failed to post process." << std::endl; FDERROR << "Failed to post process." << std::endl;
return false; return false;
} }

8
csrc/fastdeploy/vision/ocr/ppocr/recognizer.h
View File

@@ -36,8 +36,8 @@ class FASTDEPLOY_DECL Recognizer : public FastDeployModel {
std::string ModelName() const { return "ppocr/ocr_rec"; } std::string ModelName() const { return "ppocr/ocr_rec"; }
// 模型预测接口，即用户调用的接口 // 模型预测接口，即用户调用的接口
virtual bool Predict(cv::Mat* img, std::string& rec_texts, virtual bool Predict(cv::Mat* img,
float& rec_text_scores); std::tuple<std::string, float>* rec_result);
// pre & post parameters // pre & post parameters
std::vector<std::string> label_list; std::vector<std::string> label_list;
@@ -60,8 +60,8 @@ class FASTDEPLOY_DECL Recognizer : public FastDeployModel {
// 后端推理结果后处理，输出给用户 // 后端推理结果后处理，输出给用户
// infer_result 为后端推理后的输出Tensor // infer_result 为后端推理后的输出Tensor
bool Postprocess(FDTensor& infer_result, std::string& rec_texts, bool Postprocess(FDTensor& infer_result,
float& rec_text_scores); std::tuple<std::string, float>* rec_result);
}; };
} // namespace ocr } // namespace ocr

9
csrc/fastdeploy/vision/ocr/ppocr/utils/ocr_postprocess_op.cc
View File

@@ -326,8 +326,9 @@ void PostProcessor::BoxesFromBitmap(
//方法根据识别结果获取目标框位置 //方法根据识别结果获取目标框位置
void PostProcessor::FilterTagDetRes( void PostProcessor::FilterTagDetRes(
std::vector<std::vector<std::vector<int>>> *boxes, float ratio_h, std::vector<std::vector<std::vector<int>>> *boxes, const float ratio_h,
float ratio_w, const std::map<std::string, std::array<float, 2>> &im_info) { const 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_h = im_info.at("input_shape")[0];
int oriimg_w = im_info.at("input_shape")[1]; int oriimg_w = im_info.at("input_shape")[1];
@@ -350,10 +351,6 @@ void PostProcessor::FilterTagDetRes(
rect_height = int(sqrt(pow((*boxes)[n][0][0] - (*boxes)[n][3][0], 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))); pow((*boxes)[n][0][1] - (*boxes)[n][3][1], 2)));
//原始实现，小于4的跳过，只return大于4的
// if (rect_width <= 4 || rect_height <= 4) continue;
// root_points.push_back((*boxes)[n]);
//小于4的删除掉. erase配合逆序遍历. //小于4的删除掉. erase配合逆序遍历.
if (rect_width <= 4 || rect_height <= 4) { if (rect_width <= 4 || rect_height <= 4) {
boxes->erase(boxes->begin() + n); boxes->erase(boxes->begin() + n);

4
csrc/fastdeploy/vision/ocr/ppocr/utils/ocr_postprocess_op.h
View File

@@ -59,8 +59,8 @@ class PostProcessor {
const std::string &det_db_score_mode); const std::string &det_db_score_mode);
void FilterTagDetRes( void FilterTagDetRes(
std::vector<std::vector<std::vector<int>>> *boxes, float ratio_h, std::vector<std::vector<std::vector<int>>> *boxes, const float ratio_h,
float ratio_w, const float ratio_w,
const std::map<std::string, std::array<float, 2>> &im_info); const std::map<std::string, std::array<float, 2>> &im_info);
private: private:

4
csrc/fastdeploy/vision/vision_pybind.cc
View File

@@ -48,8 +48,8 @@ void BindVision(pybind11::module& m) {
.def_readwrite("boxes", &vision::OCRResult::boxes) .def_readwrite("boxes", &vision::OCRResult::boxes)
.def_readwrite("text", &vision::OCRResult::text) .def_readwrite("text", &vision::OCRResult::text)
.def_readwrite("score", &vision::OCRResult::rec_scores) .def_readwrite("score", &vision::OCRResult::rec_scores)
.def_readwrite("cls_score", &vision::OCRResult::cls_scores) .def_readwrite("cls_scores", &vision::OCRResult::cls_scores)
.def_readwrite("cls_label", &vision::OCRResult::cls_label) .def_readwrite("cls_labels", &vision::OCRResult::cls_labels)
.def("__repr__", &vision::OCRResult::Str) .def("__repr__", &vision::OCRResult::Str)
.def("__str__", &vision::OCRResult::Str); .def("__str__", &vision::OCRResult::Str);
pybind11::class_<vision::FaceDetectionResult>(m, "FaceDetectionResult") pybind11::class_<vision::FaceDetectionResult>(m, "FaceDetectionResult")

2
examples/vision/ocr/PPOCRSystemv2/python/infer.py
View File

@@ -105,7 +105,7 @@ rec_params_file = os.path.join(args.rec_model, "inference.pdiparams")
rec_label_file = args.rec_label_file rec_label_file = args.rec_label_file
#默认 #默认
det_model = fd.vision.ocr.DBDetector("") det_model = fd.vision.ocr.DBDetector()
cls_model = fd.vision.ocr.Classifier() cls_model = fd.vision.ocr.Classifier()
rec_model = fd.vision.ocr.Recognizer() rec_model = fd.vision.ocr.Recognizer()

3
examples/vision/ocr/PPOCRSystemv3/python/infer.py
View File

@@ -104,7 +104,7 @@ rec_params_file = os.path.join(args.rec_model, "inference.pdiparams")
rec_label_file = args.rec_label_file rec_label_file = args.rec_label_file
#默认 #默认
det_model = fd.vision.ocr.DBDetector("") det_model = fd.vision.ocr.DBDetector()
cls_model = fd.vision.ocr.Classifier() cls_model = fd.vision.ocr.Classifier()
rec_model = fd.vision.ocr.Recognizer() rec_model = fd.vision.ocr.Recognizer()
@@ -137,6 +137,7 @@ im = cv2.imread(args.image)
#预测并打印结果 #预测并打印结果
result = ppocrsysv3.predict(im) result = ppocrsysv3.predict(im)
print(result) print(result)
# 可视化结果 # 可视化结果