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test_lite_efficientnet_lite4.cpp
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//
// Created by DefTruth on 2021/6/26.
//
#include "lite/lite.h"
static void test_default()
{
std::string onnx_path = "../../../examples/hub/onnx/cv/efficientnet-lite4-11.onnx";
std::string test_img_path = "../../../examples/lite/resources/test_lite_efficientnet_lite4.jpg";
lite::cv::classification::EfficientNetLite4 *efficientnet_lite4 =
new lite::cv::classification::EfficientNetLite4(onnx_path);
lite::types::ImageNetContent content;
cv::Mat img_bgr = cv::imread(test_img_path);
efficientnet_lite4->detect(img_bgr, content);
if (content.flag)
{
const unsigned int top_k = content.scores.size();
if (top_k > 0)
{
for (unsigned int i = 0; i < top_k; ++i)
std::cout << i + 1
<< ": " << content.labels.at(i)
<< ": " << content.texts.at(i)
<< ": " << content.scores.at(i)
<< std::endl;
}
std::cout << "Default Version Done!" << std::endl;
}
delete efficientnet_lite4;
}
static void test_onnxruntime()
{
#ifdef ENABLE_ONNXRUNTIME
std::string onnx_path = "../../../examples/hub/onnx/cv/efficientnet-lite4-11.onnx";
std::string test_img_path = "../../../examples/lite/resources/test_lite_efficientnet_lite4.jpg";
lite::onnxruntime::cv::classification::EfficientNetLite4 *efficientnet_lite4 =
new lite::onnxruntime::cv::classification::EfficientNetLite4(onnx_path);
lite::types::ImageNetContent content;
cv::Mat img_bgr = cv::imread(test_img_path);
efficientnet_lite4->detect(img_bgr, content);
if (content.flag)
{
const unsigned int top_k = content.scores.size();
if (top_k > 0)
{
for (unsigned int i = 0; i < top_k; ++i)
std::cout << i + 1
<< ": " << content.labels.at(i)
<< ": " << content.texts.at(i)
<< ": " << content.scores.at(i)
<< std::endl;
}
std::cout << "ONNXRuntime Version Done!" << std::endl;
}
delete efficientnet_lite4;
#endif
}
static void test_mnn()
{
#ifdef ENABLE_MNN
std::string mnn_path = "../../../examples/hub/mnn/cv/efficientnet-lite4-11.mnn";
std::string test_img_path = "../../../examples/lite/resources/test_lite_efficientnet_lite4.jpg";
lite::mnn::cv::classification::EfficientNetLite4 *efficientnet_lite4 =
new lite::mnn::cv::classification::EfficientNetLite4(mnn_path);
lite::types::ImageNetContent content;
cv::Mat img_bgr = cv::imread(test_img_path);
efficientnet_lite4->detect(img_bgr, content);
if (content.flag)
{
const unsigned int top_k = content.scores.size();
if (top_k > 0)
{
for (unsigned int i = 0; i < top_k; ++i)
std::cout << i + 1
<< ": " << content.labels.at(i)
<< ": " << content.texts.at(i)
<< ": " << content.scores.at(i)
<< std::endl;
}
std::cout << "MNN Version Done!" << std::endl;
}
delete efficientnet_lite4;
#endif
}
static void test_ncnn()
{
#ifdef ENABLE_NCNN
std::string param_path = "../../../examples/hub/ncnn/cv/efficientnet-lite4-11.opt.param";
std::string bin_path = "../../../examples/hub/ncnn/cv/efficientnet-lite4-11.opt.bin";
std::string test_img_path = "../../../examples/lite/resources/test_lite_efficientnet_lite4.jpg";
lite::ncnn::cv::classification::EfficientNetLite4 *efficientnet_lite4 =
new lite::ncnn::cv::classification::EfficientNetLite4(param_path, bin_path);
lite::types::ImageNetContent content;
cv::Mat img_bgr = cv::imread(test_img_path);
efficientnet_lite4->detect(img_bgr, content);
if (content.flag)
{
const unsigned int top_k = content.scores.size();
if (top_k > 0)
{
for (unsigned int i = 0; i < top_k; ++i)
std::cout << i + 1
<< ": " << content.labels.at(i)
<< ": " << content.texts.at(i)
<< ": " << content.scores.at(i)
<< std::endl;
}
std::cout << "NCNN Version Done!" << std::endl;
}
delete efficientnet_lite4;
#endif
}
static void test_tnn()
{
#ifdef ENABLE_TNN
std::string proto_path = "../../../examples/hub/tnn/cv/efficientnet-lite4-11.opt.tnnproto";
std::string model_path = "../../../examples/hub/tnn/cv/efficientnet-lite4-11.opt.tnnmodel";
std::string test_img_path = "../../../examples/lite/resources/test_lite_efficientnet_lite4.jpg";
lite::tnn::cv::classification::EfficientNetLite4 *efficientnet_lite4 =
new lite::tnn::cv::classification::EfficientNetLite4(proto_path, model_path);
lite::types::ImageNetContent content;
cv::Mat img_bgr = cv::imread(test_img_path);
efficientnet_lite4->detect(img_bgr, content);
if (content.flag)
{
const unsigned int top_k = content.scores.size();
if (top_k > 0)
{
for (unsigned int i = 0; i < top_k; ++i)
std::cout << i + 1
<< ": " << content.labels.at(i)
<< ": " << content.texts.at(i)
<< ": " << content.scores.at(i)
<< std::endl;
}
std::cout << "TNN Version Done!" << std::endl;
}
delete efficientnet_lite4;
#endif
}
static void test_lite()
{
test_default();
test_onnxruntime();
test_mnn();
// test_ncnn();
test_tnn();
}
int main(__unused int argc, __unused char *argv[])
{
test_lite();
return 0;
}