br-enroll.cpp
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/* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *
* Copyright 2014 Noblis *
* *
* Licensed under the Apache License, Version 2.0 (the "License"); *
* you may not use this file except in compliance with the License. *
* You may obtain a copy of the License at *
* *
* http://www.apache.org/licenses/LICENSE-2.0 *
* *
* Unless required by applicable law or agreed to in writing, software *
* distributed under the License is distributed on an "AS IS" BASIS, *
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. *
* See the License for the specific language governing permissions and *
* limitations under the License. *
* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */
#include <QtCore>
#include <opencv2/highgui/highgui.hpp>
#include <cstdio>
#include <cstring>
#include <openbr/openbr_plugin.h>
#include <openbr/universal_template.h>
using namespace br;
using namespace cv;
static void help()
{
printf("br-enroll [args]\n"
"================\n"
"* __stdin__ - Templates (raw data)\n"
"* __stdout__ - Templates (feature vectors)\n"
"\n"
"_br-enroll_ is an application that creates feature vector template(s) from images.\n"
"For every input image template in _stdin_, enroll writes zero or more templates to _stdout_.\n"
"\n"
"Enroll may choose to store metadata in the feature vector in an algorithm-specific manner.\n"
"For example, a face recognition algorithm may devote the first 16-bytes of the feature vector to saving four 4-byte integers representing the face bounding box (X, Y, Width, Height).\n"
"It is expected that _br-search_ will understand and output algorithm-specific metadata for the top matching templates.\n");
}
static QSharedPointer<Transform> algorithm;
static void enroll_utemplate(br_const_utemplate utemplate)
{
if (utemplate->algorithmID != 3)
qFatal("Expected an encoded image.");
TemplateList templates;
templates.append(Template(imdecode(Mat(1, utemplate->size, CV_8UC1, (void*) utemplate->data), IMREAD_UNCHANGED)));
templates >> *algorithm;
foreach (const Template &t, templates) {
const Mat &m = t.m();
const uint32_t size = m.rows * m.cols * m.elemSize();
const QByteArray templateID = QCryptographicHash::hash(QByteArray((const char*) m.data, size), QCryptographicHash::Md5);
br_append_utemplate_contents(stdout, utemplate->imageID, (const int8_t*) templateID.data(), -1, size, (const int8_t*) m.data);
}
}
int main(int argc, char *argv[])
{
for (int i=1; i<argc; i++)
if (!strcmp(argv[i], "-help")) { help(); exit(EXIT_SUCCESS); }
Context::initialize(argc, argv, "", false);
Globals->quiet = true;
algorithm = Transform::fromAlgorithm("FaceRecognition");
br_iterate_utemplates_file(stdin, enroll_utemplate);
Context::finalize();
return EXIT_SUCCESS;
}