mirror of
https://github.com/open-mmlab/mmdeploy.git
synced 2025-01-14 08:09:43 +08:00
* hold async data and wait only at the end of the pipeline * fix use-after-free bugs * fix wording * bypass trivial cases for Pad to avoid ppl.cv's bug * fix pad * fix lint * cleanup * fix DefaultFormatBundle * fix all cpu preprocess impl * suppress log * fix dynamic library build & add comments for SyncOnScopeExit
76 lines
2.4 KiB
C++
76 lines
2.4 KiB
C++
// Copyright (c) OpenMMLab. All rights reserved.
|
|
|
|
#include "default_format_bundle.h"
|
|
|
|
#include <cassert>
|
|
|
|
#include "archive/json_archive.h"
|
|
#include "core/tensor.h"
|
|
|
|
namespace mmdeploy {
|
|
|
|
DefaultFormatBundleImpl::DefaultFormatBundleImpl(const Value& args) : TransformImpl(args) {
|
|
if (args.contains("img_to_float") && args["img_to_float"].is_boolean()) {
|
|
arg_.img_to_float = args["img_to_float"].get<bool>();
|
|
}
|
|
}
|
|
|
|
Result<Value> DefaultFormatBundleImpl::Process(const Value& input) {
|
|
MMDEPLOY_DEBUG("DefaultFormatBundle input: {}", to_json(input).dump(2));
|
|
Value output = input;
|
|
if (input.contains("img")) {
|
|
Tensor in_tensor = input["img"].get<Tensor>();
|
|
OUTCOME_TRY(auto tensor, ToFloat32(in_tensor, arg_.img_to_float));
|
|
|
|
// set default meta keys
|
|
if (!output.contains("pad_shape")) {
|
|
for (auto v : tensor.shape()) {
|
|
output["pad_shape"].push_back(v);
|
|
}
|
|
}
|
|
if (!output.contains("scale_factor")) {
|
|
output["scale_factor"].push_back(1.0);
|
|
}
|
|
if (!output.contains("img_norm_cfg")) {
|
|
int channel = tensor.shape()[3];
|
|
for (int i = 0; i < channel; i++) {
|
|
output["img_norm_cfg"]["mean"].push_back(0.0);
|
|
output["img_norm_cfg"]["std"].push_back(1.0);
|
|
}
|
|
output["img_norm_cfg"]["to_rgb"] = false;
|
|
}
|
|
|
|
// transpose
|
|
OUTCOME_TRY(tensor, HWC2CHW(tensor));
|
|
SetTransformData(output, "img", std::move(tensor));
|
|
}
|
|
|
|
MMDEPLOY_DEBUG("DefaultFormatBundle output: {}", to_json(output).dump(2));
|
|
return output;
|
|
}
|
|
|
|
DefaultFormatBundle::DefaultFormatBundle(const Value& args, int version) : Transform(args) {
|
|
auto impl_creator =
|
|
Registry<DefaultFormatBundleImpl>::Get().GetCreator(specified_platform_, version);
|
|
if (nullptr == impl_creator) {
|
|
MMDEPLOY_ERROR("'DefaultFormatBundle' is not supported on '{}' platform", specified_platform_);
|
|
throw std::domain_error("'DefaultFormatBundle' is not supported on specified platform");
|
|
}
|
|
impl_ = impl_creator->Create(args);
|
|
}
|
|
|
|
class DefaultFormatBundleCreator : public Creator<Transform> {
|
|
public:
|
|
const char* GetName() const override { return "DefaultFormatBundle"; }
|
|
int GetVersion() const override { return version_; }
|
|
ReturnType Create(const Value& args) override {
|
|
return std::make_unique<DefaultFormatBundle>(args, version_);
|
|
}
|
|
|
|
private:
|
|
int version_{1};
|
|
};
|
|
REGISTER_MODULE(Transform, DefaultFormatBundleCreator);
|
|
MMDEPLOY_DEFINE_REGISTRY(DefaultFormatBundleImpl);
|
|
} // namespace mmdeploy
|