117 lines
4.5 KiB
C++
117 lines
4.5 KiB
C++
// Copyright (c) OpenMMLab. All rights reserved.
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#include "core/utils/device_utils.h"
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#include "core/utils/formatter.h"
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#include "ppl/cv/cuda/copymakeborder.h"
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#include "preprocess/transform/pad.h"
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using namespace std;
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using namespace ppl::cv::cuda;
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namespace mmdeploy {
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namespace cuda {
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class PadImpl : public ::mmdeploy::PadImpl {
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public:
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explicit PadImpl(const Value& args) : ::mmdeploy::PadImpl(args) {
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#if PPLCV_VERSION_MAJOR >= 0 && PPLCV_VERSION_MINOR >= 6 && PPLCV_VERSION_PATCH >= 2
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map<string, ppl::cv::BorderType> border_map{{"constant", ppl::cv::BORDER_CONSTANT},
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{"edge", ppl::cv::BORDER_REPLICATE},
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{"reflect", ppl::cv::BORDER_REFLECT_101},
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{ "symmetric",
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ppl::cv::BORDER_REFLECT }};
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#else
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map<string, ppl::cv::BorderType> border_map{{"constant", ppl::cv::BORDER_TYPE_CONSTANT},
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{"edge", ppl::cv::BORDER_TYPE_REPLICATE},
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{"reflect", ppl::cv::BORDER_TYPE_REFLECT_101},
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{"symmetric", ppl::cv::BORDER_TYPE_REFLECT}};
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#endif
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if (border_map.find(arg_.padding_mode) == border_map.end()) {
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MMDEPLOY_ERROR("unsupported padding_mode '{}'", arg_.padding_mode);
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throw_exception(eNotSupported);
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}
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padding_mode_ = border_map[arg_.padding_mode];
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}
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protected:
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Result<Tensor> PadImage(const Tensor& img, const array<int, 4>& padding) override {
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OUTCOME_TRY(auto src_tensor, MakeAvailableOnDevice(img, device_, stream_));
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auto desc = src_tensor.desc();
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int height = desc.shape[1];
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int width = desc.shape[2];
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int c = desc.shape[3];
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auto dst_height = height + padding[1] + padding[3];
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auto dst_width = width + padding[0] + padding[2];
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TensorShape dst_shape{1, dst_height, dst_width, c};
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TensorDesc dst_desc{device_, desc.data_type, dst_shape, ""};
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Tensor dst_tensor(dst_desc);
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ppl::common::RetCode ret = 0;
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cudaStream_t stream = ::mmdeploy::GetNative<cudaStream_t>(stream_);
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if (desc.data_type == DataType::kFLOAT) {
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auto src_buffer = src_tensor.data<float>();
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auto dst_buffer = dst_tensor.data<float>();
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if (3 == c) {
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ret = CopyMakeBorder<float, 3>(stream, height, width, width * c, src_buffer, dst_width * c,
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dst_buffer, padding[1], padding[3], padding[0], padding[2],
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padding_mode_, arg_.pad_val);
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} else if (1 == c) {
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ret = CopyMakeBorder<float, 1>(stream, height, width, width * c, src_buffer, dst_width * c,
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dst_buffer, padding[1], padding[3], padding[0], padding[2],
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padding_mode_, arg_.pad_val);
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} else {
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MMDEPLOY_ERROR("unsupported channels {}", c);
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assert(0);
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return Status(eNotSupported);
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}
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} else if (desc.data_type == DataType::kINT8) {
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auto src_buffer = src_tensor.data<uint8_t>();
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auto dst_buffer = dst_tensor.data<uint8_t>();
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if (3 == c) {
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ret = CopyMakeBorder<ppl::cv::uchar, 3>(
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stream, height, width, width * c, src_buffer, dst_width * c, dst_buffer, padding[1],
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padding[3], padding[0], padding[2], padding_mode_, (ppl::cv::uchar)arg_.pad_val);
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} else if (1 == c) {
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ret = CopyMakeBorder<ppl::cv::uchar, 1>(
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stream, height, width, width * c, src_buffer, dst_width * c, dst_buffer, padding[1],
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padding[3], padding[0], padding[2], padding_mode_, (ppl::cv::uchar)arg_.pad_val);
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} else {
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MMDEPLOY_ERROR("unsupported channels {}", c);
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assert(0);
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return Status(eNotSupported);
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}
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} else {
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MMDEPLOY_ERROR("unsupported data type {}", desc.data_type);
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assert(0);
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return Status(eNotSupported);
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}
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if (ret != 0) {
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MMDEPLOY_ERROR("unexpected exception happened");
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assert(0);
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return Status(eNotSupported);
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}
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return dst_tensor;
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}
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private:
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ppl::cv::BorderType padding_mode_;
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};
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class PadCreator : public Creator<::mmdeploy::PadImpl> {
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public:
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const char* GetName() const override { return "cuda"; }
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int GetVersion() const override { return 1; }
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ReturnType Create(const Value& args) override { return make_unique<PadImpl>(args); }
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};
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} // namespace cuda
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} // namespace mmdeploy
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using ::mmdeploy::PadImpl;
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using mmdeploy::cuda::PadCreator;
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REGISTER_MODULE(PadImpl, PadCreator);
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