跟进:开篇/第157期
我正试图将dlib正面检测器中的五层梯级分解为三层(前、前看但左转,前看但右转一)。
叶夫根尼建议在C++中拆分检测器。我不熟悉C++。当我查看detector.h时,get_serialized_frontal_faces返回一个base64编码的对象。
我学习了如何将现有的检测器保存到.svm文件中:
#include <dlib/image_processing/frontal_face_detector.h>
#include <iostream>
using namespace dlib;
using namespace std;
int main()
{
frontal_face_detector detector = get_frontal_face_detector();
dlib::serialize("new_detector.svm") << detector;
std::cout<<"End of the Program"<<endl;
return 0;
}那么,如何拆分级联并将新的检测器保存到.svm文件中呢?
此外,通过将金字塔级别从<6>降低到detector.h中的较低值,检测器的性能会提高吗?
发布于 2016-07-22 13:41:31
只要读一读目标检测器文档,你就能找到解释。下面的代码将检测器分成几个部分,重建原始的金字塔级和限制金字塔级别:
#include <dlib/image_processing/frontal_face_detector.h>
#include <iostream>
#include <string>
using namespace dlib;
using namespace std;
int main()
{
frontal_face_detector detector = get_frontal_face_detector();
dlib::serialize("current.svm") << detector;
std::vector<frontal_face_detector> parts;
// Split into parts and serialize to disk
for (unsigned long i = 0; i < detector.num_detectors(); ++i)
{
dlib::frontal_face_detector part(detector.get_scanner(), detector.get_overlap_tester(), detector.get_w(i));
dlib::serialize("part" + std::to_string(i) + ".svm") << part;
parts.push_back(part);
}
// Reconstruct original detector
frontal_face_detector reconstructed(parts);
dlib::serialize("reconstructed.svm") << reconstructed;
// Create detector that will work only on one level of pyramid
typedef dlib::scan_fhog_pyramid<dlib::pyramid_down<6> > image_scanner_type;
image_scanner_type scanner;
scanner.copy_configuration(detector.get_scanner());
scanner.set_max_pyramid_levels(1); //try setting to 2, 3...
frontal_face_detector one_level_detector = dlib::object_detector<image_scanner_type>(scanner, detector.get_overlap_tester(), detector.get_w());
std::cout<<"End of the Program"<<endl;
return 0;
}不,将金字塔级别从<6>转换为任何其他值都不会有多大帮助,因为6不是金字塔级别的限制,而是金字塔中比例的比例:
6= 5/6
5= 4/5
..。
https://stackoverflow.com/questions/38525007
复制相似问题