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/**
* Copyright (c) 2023 Samsung Electronics Co., Ltd All Rights Reserved
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include "machine_learning_exception.h"
#include "selfie_segmentation_adapter.h"
#include "image_segmentation_external.h"
#include "mv_image_segmentation_config.h"
using namespace std;
using namespace MediaVision::Common;
using namespace mediavision::machine_learning;
using namespace mediavision::machine_learning::exception;
namespace mediavision
{
namespace machine_learning
{
ImageSegmentationAdapter::ImageSegmentationAdapter()
{
_config = make_shared<MachineLearningConfig>();
// If the model type needs external plugin then bypass to load the meta file and just create the external plugin.
// In this case, external plugin will use its own meta file approach regardless of Mediavision's one.
_config->parsePluginConfigFile(_plugin_config_file_name);
if (!_config->isPluginUsed())
_config->parseConfigFile(_config_file_name);
create(_config->getDefaultModelName());
}
ImageSegmentationAdapter::~ImageSegmentationAdapter()
{
_selfie_segmentation->preDestroy();
}
template<typename U> void ImageSegmentationAdapter::create(ImageSegmentationTaskType task_type)
{
// TODO. add switch-case statement here for Mediavision own task types.
}
void ImageSegmentationAdapter::create(std::string model_name)
{
if (model_name.empty())
model_name = _config->getDefaultModelName();
auto task_type = convertToTaskType(model_name);
if (_config->isPluginUsed()) {
const auto &plugin_name = _config->getPluginFileName();
_selfie_segmentation = make_unique<ImageSegmentationExternal>(task_type, plugin_name.c_str());
return;
}
_config->loadMetaFile(make_unique<ImageSegmentationParser>(static_cast<int>(task_type)));
mv_inference_data_type_e dataType = _config->getInputMetaMap().begin()->second->dataType;
switch (dataType) {
case MV_INFERENCE_DATA_UINT8:
create<unsigned char>(task_type);
break;
case MV_INFERENCE_DATA_FLOAT32:
create<float>(task_type);
break;
default:
throw InvalidOperation("Invalid image segmentation data type.");
}
}
ImageSegmentationTaskType ImageSegmentationAdapter::convertToTaskType(string model_name)
{
if (model_name.empty())
throw InvalidParameter("model name is empty.");
transform(model_name.begin(), model_name.end(), model_name.begin(), ::toupper);
if (model_name == "SELFIE_SEGMENTATION")
return ImageSegmentationTaskType::SELFIE_SEGMENTATION;
throw InvalidParameter("Invalid selfie segmentation model name.");
}
void ImageSegmentationAdapter::setModelInfo(const string &model_file, const string &meta_file, const string &label_file,
const string &model_name)
{
try {
_config->setUserModel(model_file, meta_file, label_file);
create(model_name);
} catch (const BaseException &e) {
LOGW("A given model name is invalid so default task type will be used.");
}
if (model_file.empty() && meta_file.empty()) {
LOGW("Given model info is invalid so default model info will be used instead.");
return;
}
_selfie_segmentation->setUserModel(model_file, meta_file, label_file);
}
void ImageSegmentationAdapter::setEngineInfo(const string &engine_type, const string &device_type)
{
_selfie_segmentation->setEngineInfo(engine_type, device_type);
}
void ImageSegmentationAdapter::configure()
{
_selfie_segmentation->configure();
}
unsigned int ImageSegmentationAdapter::getNumberOfEngines()
{
return _selfie_segmentation->getNumberOfEngines();
}
const string &ImageSegmentationAdapter::getEngineType(unsigned int engine_index)
{
return _selfie_segmentation->getEngineType(engine_index);
}
unsigned int ImageSegmentationAdapter::getNumberOfDevices(const string &engine_type)
{
return _selfie_segmentation->getNumberOfDevices(engine_type);
}
const string &ImageSegmentationAdapter::getDeviceType(const string &engine_type, unsigned int device_index)
{
return _selfie_segmentation->getDeviceType(engine_type, device_index);
}
void ImageSegmentationAdapter::prepare()
{
_selfie_segmentation->prepare();
}
void ImageSegmentationAdapter::perform(InputBaseType &input)
{
_selfie_segmentation->perform(input.inference_src);
}
OutputBaseType &ImageSegmentationAdapter::getOutput()
{
return _selfie_segmentation->getOutput();
}
OutputBaseType &ImageSegmentationAdapter::getOutputCache()
{
return _selfie_segmentation->getOutputCache();
}
void ImageSegmentationAdapter::performAsync(InputBaseType &input)
{
_selfie_segmentation->performAsync(static_cast<ImageSegmentationInput &>(input));
}
}
}
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