apps/FastDeploy
1
0
Fork 0
mirror of https://github.com/PaddlePaddle/FastDeploy.git synced 2025-10-06 17:17:14 +08:00
Code Issues Actions 2 Packages Projects Releases Wiki Activity

[Other] Add detection, segmentation and OCR examples for Ascend deploy. (#983)

Browse Source 
* Add Huawei Ascend NPU deploy through PaddleLite CANN

* Add NNAdapter interface for paddlelite

* Modify Huawei Ascend Cmake

* Update way for compiling Huawei Ascend NPU deployment

* remove UseLiteBackend in UseCANN

* Support compile python whlee

* Change names of nnadapter API

* Add nnadapter pybind and remove useless API

* Support Python deployment on Huawei Ascend NPU

* Add models suppor for ascend

* Add PPOCR rec reszie for ascend

* fix conflict for ascend

* Rename CANN to Ascend

* Rename CANN to Ascend

* Improve ascend

* fix ascend bug

* improve ascend docs

* improve ascend docs

* improve ascend docs

* Improve Ascend

* Improve Ascend

* Move ascend python demo

* Imporve ascend

* Improve ascend

* Improve ascend

* Improve ascend

* Improve ascend

* Imporve ascend

* Imporve ascend

* Improve ascend

* acc eval script

* acc eval

* remove acc_eval from branch huawei

* Add detection and segmentation examples for Ascend deployment

* Add detection and segmentation examples for Ascend deployment

* Add PPOCR example for ascend deploy

* Imporve paddle lite compiliation

* Add FlyCV doc

* Add FlyCV doc

* Add FlyCV doc

* Imporve Ascend docs

* Imporve Ascend docs
This commit is contained in:
yunyaoXYY
2023-01-04 10:01:23 +08:00
committed by GitHub
parent 2cfd331889
commit 58d63f3e90
57 changed files with 694 additions and 93 deletions
Download Patch File Download Diff File Expand all files Collapse all files

15
examples/vision/ocr/PP-OCRv3/cpp/infer.cc
View File

@@ -34,7 +34,7 @@ void InitAndInfer(const std::string& det_model_dir, const std::string& cls_model
auto rec_option = option;
// The cls and rec model can inference a batch of images now.
// User could initialize the inference batch size and set them after create PPOCR model.
// User could initialize the inference batch size and set them after create PP-OCR model.
int cls_batch_size = 1;
int rec_batch_size = 6;
@@ -56,6 +56,10 @@ void InitAndInfer(const std::string& det_model_dir, const std::string& cls_model
auto cls_model = fastdeploy::vision::ocr::Classifier(cls_model_file, cls_params_file, cls_option);
auto rec_model = fastdeploy::vision::ocr::Recognizer(rec_model_file, rec_params_file, rec_label_file, rec_option);
// Users could enable static shape infer for rec model when deploy PP-OCR on hardware
// which can not support dynamic shape infer well, like Huawei Ascend series.
// rec_model.GetPreprocessor().SetStaticShapeInfer(true);
assert(det_model.Initialized());
assert(cls_model.Initialized());
assert(rec_model.Initialized());
@@ -66,9 +70,12 @@ void InitAndInfer(const std::string& det_model_dir, const std::string& cls_model
// Set inference batch size for cls model and rec model, the value could be -1 and 1 to positive infinity.
// When inference batch size is set to -1, it means that the inference batch size
// of the cls and rec models will be the same as the number of boxes detected by the det model.
// of the cls and rec models will be the same as the number of boxes detected by the det model.
// When users enable static shape infer for rec model, the batch size of cls and rec model needs to be set to 1.
// ppocr_v3.SetClsBatchSize(1);
// ppocr_v3.SetRecBatchSize(1);
ppocr_v3.SetClsBatchSize(cls_batch_size);
ppocr_v3.SetRecBatchSize(rec_batch_size);
ppocr_v3.SetRecBatchSize(rec_batch_size);
if(!ppocr_v3.Initialized()){
std::cerr << "Failed to initialize PP-OCR." << std::endl;
@@ -123,6 +130,8 @@ int main(int argc, char* argv[]) {
option.EnablePaddleToTrt();
} else if (flag == 4) {
option.UseKunlunXin();
} else if (flag == 5) {
option.UseAscend();
}
std::string det_model_dir = argv[1];