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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>
54 lines
1.4 KiB
C++
54 lines
1.4 KiB
C++
// Copyright (c) OpenMMLab. All rights reserved.
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#include "transform.h"
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#include "core/registry.h"
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#include "core/utils/formatter.h"
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namespace mmdeploy {
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TransformImpl::TransformImpl(const Value &args) {
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if (args.contains("context")) {
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args["context"]["device"].get_to(device_);
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args["context"]["stream"].get_to(stream_);
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} else {
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throw_exception(eNotSupported);
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}
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}
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std::vector<std::string> TransformImpl::GetImageFields(const Value &input) {
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if (input.contains("img_fields")) {
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if (input["img_fields"].is_string()) {
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return {input["img_fields"].get<std::string>()};
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} else if (input["img_fields"].is_array()) {
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std::vector<std::string> img_fields;
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for (auto &v : input["img_fields"]) {
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img_fields.push_back(v.get<std::string>());
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}
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return img_fields;
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}
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} else {
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return {"img"};
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}
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throw_exception(eInvalidArgument);
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}
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Transform::Transform(const Value &args) {
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Device device{"cpu"};
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if (args.contains("context")) {
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device = args["context"].value("device", device);
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}
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Platform platform(device.platform_id());
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specified_platform_ = platform.GetPlatformName();
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if (!(specified_platform_ == "cpu")) {
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// add cpu platform, so that a transform op can fall back to its cpu
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// version if it hasn't implementation on the specific platform
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candidate_platforms_.push_back("cpu");
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}
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}
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MMDEPLOY_DEFINE_REGISTRY(Transform);
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} // namespace mmdeploy
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