int Argument_main(Argument *arg){
Match_ArgumentSet_create(arg);
Affine_ArgumentSet_create(arg);
Argument_process(arg, "affine.test", NULL, NULL);
test_model(Affine_Model_Type_GLOBAL, -151);
test_model(Affine_Model_Type_BESTFIT, 18);
test_model(Affine_Model_Type_LOCAL, 32);
test_model(Affine_Model_Type_OVERLAP, 18);
return 0;
}
int main()
{
int Error = 0;
Error += test_compiler();
Error += test_model();
Error += test_operators();
return Error;
}
int main()
{
//Class<vec, float> C;
int Error = 0;
Error += test_cpp_version();
Error += test_compiler();
Error += test_model();
Error += test_operators();
return Error;
}
vector<Scores> eval_on_dirs(shared_ptr<Model>model, vector<string> testDirs)
{
// setup parameters
vector<Scores> scores;
map<string,Scores> scoresByPose;
// default values
scores = vector<Scores>(testDirs.size());
// open the output file
FileStorage best_detections(params::out_dir() + "best_detections.yml",FileStorage::WRITE);
TaskBlock test_each_directory("eval_model");
for(int iter = 0; iter < testDirs.size(); iter++)
{
test_each_directory.add_callee([&,iter]()
{
test_model(*model,testDirs[iter],scores[iter],
scoresByPose,
[&](string filename,DetectorResult&det,DetectorResult&closest,bool correct)
{
write_best_det(best_detections,filename,det,closest,correct);
});
//if(POSE == "")
//eval_pose_estimation(*model,testDirs[iter],scores[iter]);
});
}
test_each_directory.execute();
// release the output directory
best_detections.release();
// log the results
for(int iter = 0; iter < testDirs.size(); iter++)
eval_log_result(testDirs[iter],scores[iter]);
// by pose
for(auto pose_score : scoresByPose)
eval_log_result(pose_score.first,pose_score.second);
// total
eval_log_result("TOTAL",Scores(scores));
return scores;
}
