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[Backend] cuda normalize and permute, cuda concat, optimized ppcls, ppdet & ppseg (#546)

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* cuda normalize and permute, cuda concat

* add use cuda option for preprocessor

* ppyoloe use cuda normalize

* ppseg use cuda normalize

* add proclib cuda in processor base

* ppcls add use cuda preprocess api

* ppcls preprocessor set gpu id

* fix pybind

* refine ppcls preprocessing use gpu logic

* fdtensor device id is -1 by default

* refine assert message

Co-authored-by: heliqi <1101791222@qq.com>
This commit is contained in:
Wang Xinyu
2022-11-14 18:44:00 +08:00
committed by GitHub
parent 8dec2115d5
commit a36f5d3396
20 changed files with 204 additions and 26 deletions
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14
fastdeploy/vision/segmentation/ppseg/model.cc
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@@ -39,6 +39,8 @@ PaddleSegModel::PaddleSegModel(const std::string& model_file,
}
bool PaddleSegModel::Initialize() {
reused_input_tensors_.resize(1);
reused_output_tensors_.resize(1);
if (!BuildPreprocessPipelineFromConfig()) {
FDERROR << "Failed to build preprocess pipeline from configuration file."
<< std::endl;
@@ -133,6 +135,9 @@ bool PaddleSegModel::BuildPreprocessPipelineFromConfig() {
if (!(this->disable_normalize_and_permute)) {
processors_.push_back(std::make_shared<HWC2CHW>());
}
// Fusion will improve performance
FuseTransforms(&processors_);
return true;
}
@@ -332,7 +337,6 @@ bool PaddleSegModel::Postprocess(
bool PaddleSegModel::Predict(cv::Mat* im, SegmentationResult* result) {
Mat mat(*im);
std::vector<FDTensor> processed_data(1);
std::map<std::string, std::array<int, 2>> im_info;
@@ -340,18 +344,18 @@ bool PaddleSegModel::Predict(cv::Mat* im, SegmentationResult* result) {
im_info["input_shape"] = {static_cast<int>(mat.Height()),
static_cast<int>(mat.Width())};
if (!Preprocess(&mat, &(processed_data[0]))) {
if (!Preprocess(&mat, &(reused_input_tensors_[0]))) {
FDERROR << "Failed to preprocess input data while using model:"
<< ModelName() << "." << std::endl;
return false;
}
std::vector<FDTensor> infer_result(1);
if (!Infer(processed_data, &infer_result)) {
if (!Infer()) {
FDERROR << "Failed to inference while using model:" << ModelName() << "."
<< std::endl;
return false;
}
if (!Postprocess(&infer_result[0], result, im_info)) {
if (!Postprocess(&reused_output_tensors_[0], result, im_info)) {
FDERROR << "Failed to postprocess while using model:" << ModelName() << "."
<< std::endl;
return false;