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[CVCUDA] PP-OCR Cls & Rec preprocessor support CV-CUDA (#1470)

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* ppocr cls preprocessor use manager

* hwc2chw cvcuda

* ppocr rec preproc use manager

* ocr rec preproc cvcuda

* fix rec preproc bug

* ppocr cls&rec preproc set normalize

* fix pybind

* address comment
This commit is contained in:
Wang Xinyu
2023-03-02 10:50:44 +08:00
committed by GitHub
parent fe2882a1ef
commit 044ab993d2
19 changed files with 424 additions and 306 deletions
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63
fastdeploy/vision/ocr/ppocr/cls_preprocessor.cc
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@@ -22,8 +22,20 @@ namespace fastdeploy {
namespace vision {
namespace ocr {
void OcrClassifierResizeImage(FDMat* mat,
const std::vector<int>& cls_image_shape) {
ClassifierPreprocessor::ClassifierPreprocessor() {
resize_op_ = std::make_shared<Resize>(-1, -1);
std::vector<float> value = {0, 0, 0};
pad_op_ = std::make_shared<Pad>(0, 0, 0, 0, value);
normalize_op_ =
std::make_shared<Normalize>(std::vector<float>({0.5f, 0.5f, 0.5f}),
std::vector<float>({0.5f, 0.5f, 0.5f}), true);
hwc2chw_op_ = std::make_shared<HWC2CHW>();
}
void ClassifierPreprocessor::OcrClassifierResizeImage(
FDMat* mat, const std::vector<int>& cls_image_shape) {
int img_c = cls_image_shape[0];
int img_h = cls_image_shape[1];
int img_w = cls_image_shape[2];
@@ -36,12 +48,8 @@ void OcrClassifierResizeImage(FDMat* mat,
else
resize_w = int(ceilf(img_h * ratio));
Resize::Run(mat, resize_w, img_h);
}
bool ClassifierPreprocessor::Run(std::vector<FDMat>* images,
std::vector<FDTensor>* outputs) {
return Run(images, outputs, 0, images->size());
resize_op_->SetWidthAndHeight(resize_w, img_h);
(*resize_op_)(mat);
}
bool ClassifierPreprocessor::Run(std::vector<FDMat>* images,
@@ -55,36 +63,37 @@ bool ClassifierPreprocessor::Run(std::vector<FDMat>* images,
return false;
}
std::vector<FDMat> mats(end_index - start_index);
for (size_t i = start_index; i < end_index; ++i) {
FDMat* mat = &(images->at(i));
mats[i - start_index] = images->at(i);
}
return Run(&mats, outputs);
}
bool ClassifierPreprocessor::Apply(FDMatBatch* image_batch,
std::vector<FDTensor>* outputs) {
for (size_t i = 0; i < image_batch->mats->size(); ++i) {
FDMat* mat = &(image_batch->mats->at(i));
OcrClassifierResizeImage(mat, cls_image_shape_);
if (!disable_normalize_) {
Normalize::Run(mat, mean_, scale_, is_scale_);
(*normalize_op_)(mat);
}
std::vector<float> value = {0, 0, 0};
if (mat->Width() < cls_image_shape_[2]) {
Pad::Run(mat, 0, 0, 0, cls_image_shape_[2] - mat->Width(), value);
pad_op_->SetPaddingSize(0, 0, 0, cls_image_shape_[2] - mat->Width());
(*pad_op_)(mat);
}
if (!disable_permute_) {
HWC2CHW::Run(mat);
Cast::Run(mat, "float");
(*hwc2chw_op_)(mat);
}
}
// Only have 1 output Tensor.
// Only have 1 output tensor.
outputs->resize(1);
// Concat all the preprocessed data to a batch tensor
size_t tensor_size = end_index - start_index;
std::vector<FDTensor> tensors(tensor_size);
for (size_t i = 0; i < tensor_size; ++i) {
(*images)[i + start_index].ShareWithTensor(&(tensors[i]));
tensors[i].ExpandDim(0);
}
if (tensors.size() == 1) {
(*outputs)[0] = std::move(tensors[0]);
} else {
function::Concat(tensors, &((*outputs)[0]), 0);
}
// Get the NCHW tensor
FDTensor* tensor = image_batch->Tensor();
(*outputs)[0].SetExternalData(tensor->Shape(), tensor->Dtype(),
tensor->Data(), tensor->device,
tensor->device_id);
return true;
}