lzhangzz a494a6f6ff
[SDK] sync changes according to performance benchmarks (#297)
* sync SDK changes according to performance benchmarks

* fix end-of-file lint

* fix clang-format issue

* fix clang-format by adding 'clang-format off'

* remove useless casts

* remove 'data' argument of 'operator()'

* change 'Tensor2Img' to 'TensorToImg' according to spec

* correct tensor's name according spec

Co-authored-by: lvhan028 <lvhan_028@163.com>
2021-12-16 13:51:22 +08:00

52 lines
1.4 KiB
C++

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