mnn_deeplabv3_resnet101.h
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//
// Created by DefTruth on 2021/11/29.
//
#ifndef LITE_AI_TOOLKIT_MNN_CV_MNN_DEEPLABV3_RESNET101_H
#define LITE_AI_TOOLKIT_MNN_CV_MNN_DEEPLABV3_RESNET101_H
#include "lite/mnn/core/mnn_core.h"
namespace mnncv
{
class LITE_EXPORTS MNNDeepLabV3ResNet101
{
public:
explicit MNNDeepLabV3ResNet101(const std::string &_mnn_path,
unsigned int _num_threads = 8); //
~MNNDeepLabV3ResNet101();
private:
std::shared_ptr<MNN::Interpreter> mnn_interpreter;
MNN::Session *mnn_session = nullptr;
MNN::ScheduleConfig schedule_config;
std::shared_ptr<MNN::CV::ImageProcess> pretreat; // init at runtime
const char *log_id = nullptr;
const char *mnn_path = nullptr;
MNN::Tensor *input_tensor = nullptr;
private:
const float norm_vals[3] = {(1.f / 0.229f) * (1.f / 255.f),
(1.f / 0.224f) * (1.f / 255.f),
(1.f / 0.225f) * (1.f / 255.f)};
const float mean_vals[3] = {0.485f * 255.f, 0.456f * 255.f, 0.406f * 255.f}; // RGB
private:
const unsigned int num_threads; // initialize at runtime.
int dynamic_input_height = 512; // init only, will change according to input mat.
int dynamic_input_width = 512; // init only, will change according to input mat.
int dimension_type; // hint only
const char *class_names[20] = {
"aeroplane", "bicycle", "bird", "boat", "bottle", "bus", "car", "cat", "chair", "cow",
"diningtable", "dog", "horse", "motorbike", "person", "pottedplant", "sheep", "sofa",
"train", "tvmonitor"
}; // 20 classes
// un-copyable
protected:
MNNDeepLabV3ResNet101(const MNNDeepLabV3ResNet101 &) = delete; //
MNNDeepLabV3ResNet101(MNNDeepLabV3ResNet101 &&) = delete; //
MNNDeepLabV3ResNet101 &operator=(const MNNDeepLabV3ResNet101 &) = delete; //
MNNDeepLabV3ResNet101 &operator=(MNNDeepLabV3ResNet101 &&) = delete; //
private:
void print_debug_string();
private:
void transform(const cv::Mat &mat);
void initialize_pretreat(); //
void initialize_interpreter();
public:
void detect(const cv::Mat &mat, types::SegmentContent &content);
};
}
#endif //LITE_AI_TOOLKIT_MNN_CV_MNN_DEEPLABV3_RESNET101_H