【米尔FZ3深度学习计算卡】鼠标检测源码 + 视频

robe.zhang · 发表于 2020-12-27 01:38:53

本帖最后由 robe.zhang 于 2020-12-27 01:38 编辑

鼠标检测视频：

百度 EasyDL 训练数据集采集视频：

鼠标检测视频源码：

/***************************************************************************
*
*
**************************************************************************/
/**
* @author: Robe
* @brief: video detection.
* suit for SDK V1.0.0. and add comments.
*
**/
#include <iostream>
#include <sstream>
#include "easyedge/easyedge.h"
using namespace easyedge;
int main(int argc, char *argv[]) {
if (argc != 2) { /* " Usage: demo {model_dir}." */
std::cerr << "Usage: demo {model_dir}." << std::endl;
exit(-1);
}
cv::VideoCapture capture("/dev/video2"); /* camera */
capture.set(cv::CAP_PROP_FRAME_WIDTH, 1280);
capture.set(cv::CAP_PROP_FRAME_HEIGHT, 720);
capture.set(cv::CAP_PROP_FPS, 30);
cv::Mat img;
capture.read(img);
EdgePredictorConfig config; /* use EdgePredictorConfig in SDK V1.0.0 instead of EdgePredictorConfig in SDK V0.5 and below. */
config.model_dir = argv[1];
global_controller()->set_licence_key("set your owner licence_key"); /* set your owner licence_key */
EdgeLogConfig log_config;
log_config.enable_debug = false;
global_controller()->set_log_config(log_config);
auto predictor = global_controller()->CreateEdgePredictor<EdgePredictorConfig>(config);
if (predictor->init() != EDGE_OK) {
std::cerr << "predictor initial ERROR.please check again." << std::endl;
exit(-2);
}
std::vector<EdgeResultData> result; /* predict result <result:temp not use> <result2:predict result> <result_set_zero:use to set zero>*/
std::vector<EdgeResultData> result2;
std::vector<EdgeResultData> result_set_zero;
while(1)
{
capture.read(img); /* grab one frame image */
result2 = result_set_zero; /* set result to clean */
predictor->infer(img, result2); /* predict */
for (auto &v : result2) {
if (v.prob < 0.2) { /* set the model's threshold */
continue;
}
std::cout << v.index << ", " << v.label << ", p:" << v.prob; /* print result to console */
if (predictor->model_kind() == EdgeModelKind::kObjectDetection) {
std::cout << " loc: "
<< v.x1 << ", " << v.y1 << ", " << v.x2 << ", " << v.y2;
auto p1 = cv::Point(static_cast<int>(v.x1 * img.cols),
static_cast<int>(v.y1 * img.rows));
auto p2 = cv::Point(static_cast<int>(v.x2 * img.cols),
static_cast<int>((v.y2) * img.rows));
cv::rectangle(img, p1, p2, RED, 3); /* rect the object */
cv::putText(img, v.label, p1, cv::FONT_HERSHEY_PLAIN, 3, BLUE, 4); /* lable the object */
}
std::cout << std::endl;
}
std::cout << "Done" << std::endl;
cv::imshow("MYIR FZ3 baidu brain board. DEMO.", img); /* show the predict image */
if(cv::waitKey(1)==27) break; /* enter the "ESC" key to exit this program */
}
capture.release(); /* prepare to exit. */
cv::destroyWindow("MYIR FZ3 baidu brain board. DEMO.");
return 0;
}

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【米尔FZ3深度学习计算卡】鼠标检测源码 + 视频

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