mmdeploy/csrc/preprocess/cpu/default_format_bundle_impl.cpp

65 lines
2.0 KiB
C++

// Copyright (c) OpenMMLab. All rights reserved.
#include "core/utils/device_utils.h"
#include "opencv_utils.h"
#include "preprocess/transform/default_format_bundle.h"
namespace mmdeploy {
namespace cpu {
class DefaultFormatBundleImpl : public ::mmdeploy::DefaultFormatBundleImpl {
public:
explicit DefaultFormatBundleImpl(const Value& args) : ::mmdeploy::DefaultFormatBundleImpl(args) {}
protected:
Result<Tensor> ToFloat32(const Tensor& tensor, const bool& img_to_float) override {
OUTCOME_TRY(auto src_tensor, MakeAvailableOnDevice(tensor, device_, stream_));
SyncOnScopeExit(stream_, src_tensor.buffer() != tensor.buffer(), src_tensor);
auto data_type = src_tensor.desc().data_type;
if (img_to_float && data_type == DataType::kINT8) {
auto cvmat = Tensor2CVMat(src_tensor);
cvmat.convertTo(cvmat, CV_32FC(cvmat.channels()));
auto dst_tensor = CVMat2Tensor(cvmat);
return dst_tensor;
}
return src_tensor;
}
Result<Tensor> HWC2CHW(const Tensor& tensor) override {
OUTCOME_TRY(auto src_tensor, MakeAvailableOnDevice(tensor, device_, stream_));
SyncOnScopeExit(stream_, src_tensor.buffer() != tensor.buffer(), src_tensor);
auto shape = src_tensor.shape();
int height = shape[1];
int width = shape[2];
int channels = shape[3];
auto dst_mat = Transpose(Tensor2CVMat(src_tensor));
auto dst_tensor = CVMat2Tensor(dst_mat);
dst_tensor.Reshape({1, channels, height, width});
return dst_tensor;
}
};
class DefaultFormatBundleImplCreator : public Creator<::mmdeploy::DefaultFormatBundleImpl> {
public:
const char* GetName() const override { return "cpu"; }
int GetVersion() const override { return 1; }
ReturnType Create(const Value& args) override {
return std::make_unique<DefaultFormatBundleImpl>(args);
}
};
} // namespace cpu
} // namespace mmdeploy
using mmdeploy::DefaultFormatBundleImpl;
using mmdeploy::cpu::DefaultFormatBundleImplCreator;
REGISTER_MODULE(DefaultFormatBundleImpl, DefaultFormatBundleImplCreator);