147 lines
6.1 KiB
C++
147 lines
6.1 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/resize.h"
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#include "preprocess/transform/resize.h"
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using namespace std;
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namespace mmdeploy {
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namespace cuda {
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class ResizeImpl final : public ::mmdeploy::ResizeImpl {
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public:
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explicit ResizeImpl(const Value& args) : ::mmdeploy::ResizeImpl(args) {}
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~ResizeImpl() override = default;
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protected:
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Result<Tensor> ResizeImage(const Tensor& tensor, int dst_h, int dst_w) override {
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OUTCOME_TRY(auto src_tensor, MakeAvailableOnDevice(tensor, device_, stream_));
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TensorDesc dst_desc{
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device_, src_tensor.data_type(), {1, dst_h, dst_w, src_tensor.shape(3)}, src_tensor.name()};
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Tensor dst_tensor(dst_desc);
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auto stream = GetNative<cudaStream_t>(stream_);
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if (arg_.interpolation == "bilinear") {
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OUTCOME_TRY(ResizeLinear(src_tensor, dst_tensor, stream));
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} else if (arg_.interpolation == "nearest") {
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OUTCOME_TRY(ResizeNearest(src_tensor, dst_tensor, stream));
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} else {
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ERROR("{} interpolation is not supported", arg_.interpolation);
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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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Result<void> ResizeLinear(const Tensor& src, Tensor& dst, cudaStream_t stream) {
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int h = (int)src.shape(1);
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int w = (int)src.shape(2);
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int c = (int)src.shape(3);
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int dst_h = (int)dst.shape()[1];
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int dst_w = (int)dst.shape()[2];
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ppl::common::RetCode ret = 0;
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auto data_type = src.data_type();
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if (data_type == DataType::kINT8) {
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auto input = src.data<uint8_t>();
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auto output = dst.data<uint8_t>();
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if (1 == c) {
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ret = ppl::cv::cuda::Resize<uint8_t, 1>(stream, h, w, w * c, input, dst_h, dst_w, dst_w * c,
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output, ppl::cv::INTERPOLATION_TYPE_LINEAR);
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} else if (3 == c) {
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ret = ppl::cv::cuda::Resize<uint8_t, 3>(stream, h, w, w * c, input, dst_h, dst_w, dst_w * c,
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output, ppl::cv::INTERPOLATION_TYPE_LINEAR);
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} else if (4 == c) {
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ret = ppl::cv::cuda::Resize<uint8_t, 4>(stream, h, w, w * c, input, dst_h, dst_w, dst_w * c,
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output, ppl::cv::INTERPOLATION_TYPE_LINEAR);
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} else {
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ERROR("unsupported channels {}", c);
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return Status(eNotSupported);
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}
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} else if (data_type == DataType::kFLOAT) {
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auto input = src.data<float>();
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auto output = dst.data<float>();
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if (1 == c) {
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ret = ppl::cv::cuda::Resize<float, 1>(stream, h, w, w * c, input, dst_h, dst_w, dst_w * c,
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output, ppl::cv::INTERPOLATION_TYPE_LINEAR);
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} else if (3 == c) {
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ret = ppl::cv::cuda::Resize<float, 3>(stream, h, w, w * c, input, dst_h, dst_w, dst_w * c,
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output, ppl::cv::INTERPOLATION_TYPE_LINEAR);
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} else if (4 == c) {
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ret = ppl::cv::cuda::Resize<float, 4>(stream, h, w, w * c, input, dst_h, dst_w, dst_w * c,
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output, ppl::cv::INTERPOLATION_TYPE_LINEAR);
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} else {
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ERROR("unsupported channels {}", c);
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return Status(eNotSupported);
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}
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} else {
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ERROR("unsupported data type {}", src.data_type());
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return Status(eNotSupported);
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}
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return ret == 0 ? success() : Result<void>(Status(eFail));
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}
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Result<void> ResizeNearest(const Tensor& src, Tensor& dst, cudaStream_t stream) {
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int h = (int)src.shape(1);
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int w = (int)src.shape(2);
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int c = (int)src.shape(3);
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int dst_h = (int)dst.shape(1);
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int dst_w = (int)dst.shape(2);
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ppl::common::RetCode ret = 0;
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auto data_type = src.data_type();
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if (DataType::kINT8 == data_type) {
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auto input = src.data<uint8_t>();
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auto output = dst.data<uint8_t>();
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if (1 == c) {
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ret = ppl::cv::cuda::Resize<uint8_t, 1>(stream, h, w, w * c, input, dst_h, dst_w, dst_w * c,
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output, ppl::cv::INTERPOLATION_TYPE_NEAREST_POINT);
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} else if (3 == c) {
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ret = ppl::cv::cuda::Resize<uint8_t, 3>(stream, h, w, w * c, input, dst_h, dst_w, dst_w * c,
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output, ppl::cv::INTERPOLATION_TYPE_NEAREST_POINT);
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} else if (4 == c) {
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ret = ppl::cv::cuda::Resize<uint8_t, 4>(stream, h, w, w * c, input, dst_h, dst_w, dst_w * c,
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output, ppl::cv::INTERPOLATION_TYPE_NEAREST_POINT);
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} else {
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ERROR("unsupported channel {}", c);
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return Status(eNotSupported);
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}
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} else if (data_type == DataType::kFLOAT) {
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auto input = src.data<float>();
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auto output = dst.data<float>();
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if (1 == c) {
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ret = ppl::cv::cuda::Resize<float, 1>(stream, h, w, w * c, input, dst_h, dst_w, dst_w * c,
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output, ppl::cv::INTERPOLATION_TYPE_NEAREST_POINT);
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} else if (3 == c) {
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ret = ppl::cv::cuda::Resize<float, 3>(stream, h, w, w * c, input, dst_h, dst_w, dst_w * c,
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output, ppl::cv::INTERPOLATION_TYPE_NEAREST_POINT);
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} else if (4 == c) {
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ret = ppl::cv::cuda::Resize<float, 4>(stream, h, w, w * c, input, dst_h, dst_w, dst_w * c,
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output, ppl::cv::INTERPOLATION_TYPE_NEAREST_POINT);
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} else {
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ERROR("unsupported channel {}", c);
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return Status(eNotSupported);
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}
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} else {
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ERROR("unsupported data type {}", src.data_type());
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return Status(eNotSupported);
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}
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return ret == 0 ? success() : Result<void>(Status(eFail));
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}
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};
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class ResizeImplCreator : public Creator<::mmdeploy::ResizeImpl> {
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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<ResizeImpl>(args); }
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};
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} // namespace cuda
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} // namespace mmdeploy
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using ::mmdeploy::ResizeImpl;
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using ::mmdeploy::cuda::ResizeImplCreator;
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REGISTER_MODULE(ResizeImpl, ResizeImplCreator);
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