int RecognizeFace(std::vector<float> &input_vec);
int DeleteLabel(std::string label_name);
int GetLabel(const char **out_label);
- mv_face_recognition_result_s &GetResult();
+ mv_face_recognition_result_s &result();
};
} // machine_learning
void prepare();
void preprocess(mv_source_h &mv_src);
void inference(mv_source_h source);
- facenet_output_s &getResult();
+ facenet_output_s &result();
};
} // machine_learning
return MEDIA_VISION_ERROR_NONE;
}
-mv_face_recognition_result_s &FaceRecognition::GetResult()
+mv_face_recognition_result_s &FaceRecognition::result()
{
if (!_result.is_valid)
throw NoData("Inference result not ready yet.");
template<typename T, typename V> V &FaceRecognitionAdapter<T, V>::getOutput()
{
- return _face_recognition->GetResult();
+ return _face_recognition->result();
}
template class FaceRecognitionAdapter<mv_face_recognition_input_s, mv_face_recognition_result_s>;
LOGI("LEAVE");
}
-facenet_output_s &Facenet::getResult()
+facenet_output_s &Facenet::result()
{
TensorBuffer &tensor_buffer_obj = _inference->GetOutputTensorBuffer();
template<typename T, typename V> V &FacenetAdapter<T, V>::getOutput()
{
- return _facenet->getResult();
+ return _facenet->result();
}
template class FacenetAdapter<facenet_input_s, facenet_output_s>;
void prepare();
void preprocess(mv_source_h &mv_src);
void inference(mv_source_h source);
- virtual image_classification_result_s &getResult() = 0;
+ virtual image_classification_result_s &result() = 0;
};
} // machine_learning
public:
ImageClassificationDefault();
~ImageClassificationDefault();
- image_classification_result_s &getResult() override;
+ image_classification_result_s &result() override;
};
} // machine_learning
template<typename T, typename V> V &ImageClassificationAdapter<T, V>::getOutput()
{
- return _image_classification->getResult();
+ return _image_classification->result();
}
template class ImageClassificationAdapter<image_classification_input_s, image_classification_result_s>;
ImageClassificationDefault::~ImageClassificationDefault()
{}
-image_classification_result_s &ImageClassificationDefault::getResult()
+image_classification_result_s &ImageClassificationDefault::result()
{
vector<string> names;
void prepare();
void preprocess(mv_source_h &mv_src);
void inference(mv_source_h source);
- virtual object_detection_result_s &getResult() = 0;
+ virtual object_detection_result_s &result() = 0;
};
} // machine_learning
public:
Objectron();
~Objectron();
- object_detection_result_s &getResult() override;
+ object_detection_result_s &result() override;
};
} // machine_learning
template<typename T, typename V> V &ObjectDetectionAdapter<T, V>::getOutput()
{
- return _object_detection->getResult();
+ return _object_detection->result();
}
template class ObjectDetectionAdapter<object_detection_input_s, object_detection_result_s>;
Objectron::~Objectron()
{}
-object_detection_result_s &Objectron::getResult()
+object_detection_result_s &Objectron::result()
{
vector<string> names;