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[Model] Add Picodet RKNPU2 (#635)

Browse Source 
* * 更新picodet cpp代码

* * 更新文档
* 更新picodet cpp example

* * 删除无用的debug代码
* 新增python example

* * 修改c++代码

* * 修改python代码

* * 修改postprocess代码

* 修复没有scale_factor导致的bug

* 修复错误

* 更正代码格式

* 更正代码格式
This commit is contained in:
Zheng_Bicheng
2022-11-21 13:44:34 +08:00
committed by GitHub
parent 5ca779ee32
commit 3e1fc69a0c
20 changed files with 340 additions and 195 deletions
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37
fastdeploy/vision/detection/ppdet/preprocessor.cc
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@@ -22,11 +22,13 @@ namespace vision {
namespace detection {
PaddleDetPreprocessor::PaddleDetPreprocessor(const std::string& config_file) {
FDASSERT(BuildPreprocessPipelineFromConfig(config_file), "Failed to create PaddleDetPreprocessor.");
FDASSERT(BuildPreprocessPipelineFromConfig(config_file),
"Failed to create PaddleDetPreprocessor.");
initialized_ = true;
}
bool PaddleDetPreprocessor::BuildPreprocessPipelineFromConfig(const std::string& config_file) {
bool PaddleDetPreprocessor::BuildPreprocessPipelineFromConfig(
const std::string& config_file) {
processors_.clear();
YAML::Node cfg;
try {
@@ -106,8 +108,6 @@ bool PaddleDetPreprocessor::BuildPreprocessPipelineFromConfig(const std::string&
// permute = cast<float> + HWC2CHW
processors_.push_back(std::make_shared<Cast>("float"));
processors_.push_back(std::make_shared<HWC2CHW>());
} else {
processors_.push_back(std::make_shared<HWC2CHW>());
}
// Fusion will improve performance
@@ -116,13 +116,15 @@ bool PaddleDetPreprocessor::BuildPreprocessPipelineFromConfig(const std::string&
return true;
}
bool PaddleDetPreprocessor::Run(std::vector<FDMat>* images, std::vector<FDTensor>* outputs) {
bool PaddleDetPreprocessor::Run(std::vector<FDMat>* images,
std::vector<FDTensor>* outputs) {
if (!initialized_) {
FDERROR << "The preprocessor is not initialized." << std::endl;
return false;
}
if (images->size() == 0) {
FDERROR << "The size of input images should be greater than 0." << std::endl;
FDERROR << "The size of input images should be greater than 0."
<< std::endl;
return false;
}
@@ -140,8 +142,9 @@ bool PaddleDetPreprocessor::Run(std::vector<FDMat>* images, std::vector<FDTensor
// All the tensor will pad to the max size to compose a batched tensor
std::vector<int> max_hw({-1, -1});
float* scale_factor_ptr = reinterpret_cast<float*>((*outputs)[1].MutableData());
float* im_shape_ptr = reinterpret_cast<float*>((*outputs)[2].MutableData());
float* scale_factor_ptr =
reinterpret_cast<float*>((*outputs)[1].MutableData());
float* im_shape_ptr = reinterpret_cast<float*>((*outputs)[2].MutableData());
for (size_t i = 0; i < images->size(); ++i) {
int origin_w = (*images)[i].Width();
int origin_h = (*images)[i].Height();
@@ -149,7 +152,8 @@ bool PaddleDetPreprocessor::Run(std::vector<FDMat>* images, std::vector<FDTensor
scale_factor_ptr[2 * i + 1] = 1.0;
for (size_t j = 0; j < processors_.size(); ++j) {
if (!(*(processors_[j].get()))(&((*images)[i]))) {
FDERROR << "Failed to processs image:" << i << " in " << processors_[i]->Name() << "." << std::endl;
FDERROR << "Failed to processs image:" << i << " in "
<< processors_[i]->Name() << "." << std::endl;
return false;
}
if (processors_[j]->Name().find("Resize") != std::string::npos) {
@@ -166,15 +170,18 @@ bool PaddleDetPreprocessor::Run(std::vector<FDMat>* images, std::vector<FDTensor
im_shape_ptr[2 * i] = max_hw[0];
im_shape_ptr[2 * i + 1] = max_hw[1];
}
// Concat all the preprocessed data to a batch tensor
std::vector<FDTensor> im_tensors(images->size());
std::vector<FDTensor> im_tensors(images->size());
for (size_t i = 0; i < images->size(); ++i) {
if ((*images)[i].Height() < max_hw[0] || (*images)[i].Width() < max_hw[1]) {
// if the size of image less than max_hw, pad to max_hw
FDTensor tensor;
(*images)[i].ShareWithTensor(&tensor);
function::Pad(tensor, &(im_tensors[i]), {0, 0, max_hw[0] - (*images)[i].Height(), max_hw[1] - (*images)[i].Width()}, 0);
function::Pad(tensor, &(im_tensors[i]),
{0, 0, max_hw[0] - (*images)[i].Height(),
max_hw[1] - (*images)[i].Width()},
0);
} else {
// No need pad
(*images)[i].ShareWithTensor(&(im_tensors[i]));
@@ -196,6 +203,6 @@ bool PaddleDetPreprocessor::Run(std::vector<FDMat>* images, std::vector<FDTensor
return true;
}
} // namespace detection
} // namespace vision
} // namespace fastdeploy
} // namespace detection
} // namespace vision
} // namespace fastdeploy