// Attempts to recognize the plate. Returns a confidence level. Updates teh "stateCode" variable
// with the value of the country/state
int StateIdentifier::recognize(Mat img, char* stateCode)
{
timespec startTime;
getTime(&startTime);
cvtColor(img, img, CV_BGR2GRAY);
resize(img, img, getSizeMaintainingAspect(img, config->stateIdImageWidthPx, config->stateIdimageHeightPx));
Mat plateImg(img.size(), img.type());
//plateImg = equalizeBrightness(img);
img.copyTo(plateImg);
Mat debugImg(plateImg.size(), plateImg.type());
plateImg.copyTo(debugImg);
vector<int> matchesArray(featureMatcher->numTrainingElements());
RecognitionResult result = featureMatcher->recognize(plateImg, true, &debugImg, true, matchesArray );
if (this->config->debugStateId)
{
displayImage(config, "State Identifier1", plateImg);
displayImage(config, "State Identifier", debugImg);
cout << result.haswinner << " : " << result.confidence << " : " << result.winner << endl;
}
if (config->debugTiming)
{
timespec endTime;
getTime(&endTime);
cout << "State Identification Time: " << diffclock(startTime, endTime) << "ms." << endl;
}
if (result.haswinner == false)
return 0;
strcpy(stateCode, result.winner.c_str());
return result.confidence;
}
// Attempts to recognize the plate. Returns a confidence level. Updates the region code and confidence
// If region is found, returns true.
bool StateIdentifier::recognize(PipelineData* pipeline_data)
{
timespec startTime;
getTime(&startTime);
Mat plateImg = Mat(pipeline_data->grayImg, pipeline_data->regionOfInterest);
resize(plateImg, plateImg, getSizeMaintainingAspect(plateImg, config->stateIdImageWidthPx, config->stateIdimageHeightPx));
Mat debugImg(plateImg.size(), plateImg.type());
plateImg.copyTo(debugImg);
vector<int> matchesArray(featureMatcher->numTrainingElements());
RecognitionResult result = featureMatcher->recognize(plateImg, true, &debugImg, true, matchesArray );
if (this->config->debugStateId)
{
displayImage(config, "State Identifier1", plateImg);
displayImage(config, "State Identifier", debugImg);
cout << result.haswinner << " : " << result.confidence << " : " << result.winner << endl;
}
if (config->debugTiming)
{
timespec endTime;
getTime(&endTime);
cout << "State Identification Time: " << diffclock(startTime, endTime) << "ms." << endl;
}
if (result.haswinner == false)
return 0;
pipeline_data->region_code = result.winner;
pipeline_data->region_confidence = result.confidence;
if (result.confidence >= 10)
return true;
return false;
}
bool FaceDetector::DetectFaces(const cv::Mat& cropped_img,
std::vector<cv::Rect>& faces_front,
std::vector<cv::Rect>& faces_profile) const{
cv::Mat cascade_img;
std::vector<cv::Rect>::iterator face_it;
// create a copy of the image
cropped_img.copyTo(cascade_img);
// increase contrast of the image
normalize(cascade_img, cascade_img, 0, 255, cv::NORM_MINMAX, CV_8UC1);
// detect frontal faces
classifier_front_.detectMultiScale(cascade_img,
faces_front,
classifier_front_scale_factor_,
classifier_front_min_neighbours_,
0|CV_HAAR_SCALE_IMAGE,
classif_front_min_size_);
// discard face if its not close to the top of the region, false positive
face_it = faces_front.begin();
for ( ; face_it != faces_front.end(); ) {
// allowed area is the full width and three times the size of the detected face
cv::Rect allowed_area (0, 0, cropped_img.cols, face_it->height * 3);
// test if the rectangles intersect
if ( !(allowed_area & *face_it).area()) {
face_it = faces_front.erase(face_it);
}else
++face_it;
}
// only search profile faces if the frontal face detection failed
if (faces_front.empty())
{
classifier_profile_.detectMultiScale(cascade_img,
faces_profile,
classifier_profile_scale_factor_,
classifier_profile_min_neighbours_,
0|CV_HAAR_SCALE_IMAGE,
classif_profile_min_size_);
// discard face if its not close to the top of the region, false positive
face_it = faces_profile.begin();
for ( ; face_it != faces_profile.end(); ) {
// allowed area is the full width and three times the size of the detected face
cv::Rect allowed_area (0, 0, cropped_img.cols, face_it->height * 3);
// test if the rectangles intersect
if ( !(allowed_area & *face_it).area()) {
face_it = faces_profile.erase(face_it);
}else
++face_it;
}
}
// if debug mode is active and faces were found
if (debug_mode_)
{
cv::Mat debugImg(cropped_img);
for (uint j = 0; j < faces_front.size(); j++)
cv::rectangle(debugImg, faces_front[j], cv::Scalar(0, 255, 0), 2, CV_AA);
for (uint j = 0; j < faces_profile.size(); j++)
cv::rectangle(debugImg, faces_profile[j], cv::Scalar(0, 0, 255), 2, CV_AA);
cv::imwrite(debug_folder_ + ed::Entity::generateID().c_str() + "_face_detector.png", debugImg);
cv::imshow("Face Detector Output", debugImg);
}
// return true if a face was found
return (!faces_front.empty() || !faces_profile.empty());
}
