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* minor changes * support windows * fix GCC build * fix lint * reformat * fix Windows build * fix GCC build * search backend ops for onnxruntime * fix lint * fix lint * code clean-up * code clean-up * fix clang build * fix trt support * fix cmake for ncnn * fix cmake for openvino * fix SDK Python API * handle ops for other backends (ncnn, trt) * handle SDK Python API library location * robustify linkage * fix cuda * minor fix for openvino & ncnn * use CMAKE_CUDA_ARCHITECTURES if set * fix cuda preprocessor * fix misc * fix pplnn & pplcv, drop support for pplcv<0.6.0 * robustify cmake * update build.md (#2) * build dynamic modules as module library & fix demo (partially) * fix candidate path for mmdeploy_python * move "enable CUDA" to cmake config for demo * refine demo cmake * add comment * fix ubuntu build * revert docs/en/build.md * fix C API * fix lint * Windows build doc (#3) * check in docs related to mmdeploy build on windows * update build guide on windows platform * update build guide on windows platform * make path of thirdparty libraries consistent * make path consistency * correct build command for custom ops * correct build command for sdk * update sdk build instructions * update doc * correct build command * fix lint * correct build command and fix lint Co-authored-by: lvhan <lvhan@pjlab.org> * trailing whitespace (#4) * minor fix * fix sr sdk model * fix type deduction * fix cudaFree after driver shutting down * update ppl.cv installation warning (#5) * fix device allocator threshold & fix lint * update doc (#6) * update ppl.cv installation warning * missing 'git clone' Co-authored-by: chenxin <chenxin2@sensetime.com> Co-authored-by: zhangli <zhangli@sensetime.com> Co-authored-by: lvhan028 <lvhan_028@163.com> Co-authored-by: lvhan <lvhan@pjlab.org>
58 lines
1.7 KiB
C++
58 lines
1.7 KiB
C++
// Copyright (c) OpenMMLab. All rights reserved.
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#include "image2tensor.h"
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#include <cassert>
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#include "archive/json_archive.h"
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#include "core/tensor.h"
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namespace mmdeploy {
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ImageToTensorImpl::ImageToTensorImpl(const Value& args) : TransformImpl(args) {
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for (auto& key : args["keys"]) {
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arg_.keys.push_back(key.get<std::string>());
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}
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}
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Result<Value> ImageToTensorImpl::Process(const Value& input) {
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MMDEPLOY_DEBUG("input: {}", to_json(input).dump(2));
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Value output = input;
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for (auto& key : arg_.keys) {
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assert(input.contains(key));
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Tensor src_tensor = input[key].get<Tensor>();
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auto& shape = src_tensor.desc().shape;
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assert(shape.size() == 4);
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assert(shape[3] == 1 || shape[3] == 3);
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OUTCOME_TRY(output[key], HWC2CHW(src_tensor));
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} // for key
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MMDEPLOY_DEBUG("output: {}", to_json(output).dump(2));
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return output;
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}
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ImageToTensor::ImageToTensor(const Value& args, int version) : Transform(args) {
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auto impl_creator = Registry<ImageToTensorImpl>::Get().GetCreator(specified_platform_, version);
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if (nullptr == impl_creator) {
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MMDEPLOY_ERROR("'ImageToTensor' is not supported on '{}' platform", specified_platform_);
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throw std::domain_error("'ImageToTensor' is not supported on specified platform");
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}
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impl_ = impl_creator->Create(args);
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}
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class ImageToTensorCreator : public Creator<Transform> {
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public:
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const char* GetName() const override { return "ImageToTensor"; }
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int GetVersion() const override { return version_; }
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ReturnType Create(const Value& args) override {
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return std::make_unique<ImageToTensor>(args, version_);
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}
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private:
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int version_{1};
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};
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REGISTER_MODULE(Transform, ImageToTensorCreator);
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MMDEPLOY_DEFINE_REGISTRY(ImageToTensorImpl);
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} // namespace mmdeploy
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