AlprImpl::AlprImpl(const std::string country, const std::string configFile, const std::string runtimeDir)
{
timespec startTime;
getTimeMonotonic(&startTime);
config = new Config(country, configFile, runtimeDir);
plateDetector = ALPR_NULL_PTR;
stateDetector = ALPR_NULL_PTR;
ocr = ALPR_NULL_PTR;
prewarp = ALPR_NULL_PTR;
// Config file or runtime dir not found. Don't process any further.
if (config->loaded == false)
{
return;
}
plateDetector = createDetector(config);
ocr = new OCR(config);
setNumThreads(0);
setDetectRegion(DEFAULT_DETECT_REGION);
this->topN = DEFAULT_TOPN;
setDefaultRegion("");
prewarp = new PreWarp(config);
timespec endTime;
getTimeMonotonic(&endTime);
if (config->debugTiming)
cout << "OpenALPR Initialization Time: " << diffclock(startTime, endTime) << "ms." << endl;
}
ColorFilter::ColorFilter(Mat image, Mat characterMask, Config* config)
{
timespec startTime;
getTimeMonotonic(&startTime);
this->config = config;
this->debug = config->debugColorFiler;
this->grayscale = imageIsGrayscale(image);
if (this->debug)
cout << "ColorFilter: isGrayscale = " << grayscale << endl;
this->hsv = Mat(image.size(), image.type());
cvtColor( image, this->hsv, CV_BGR2HSV );
preprocessImage();
this->charMask = characterMask;
this->colorMask = Mat(image.size(), CV_8U);
findCharColors();
if (config->debugTiming)
{
timespec endTime;
getTimeMonotonic(&endTime);
cout << " -- ColorFilter Time: " << diffclock(startTime, endTime) << "ms." << endl;
}
}
vector<Rect> DetectorCPU::find_plates(Mat frame, cv::Size min_plate_size, cv::Size max_plate_size)
{
vector<Rect> plates;
//-- Detect plates
timespec startTime;
getTimeMonotonic(&startTime);
equalizeHist( frame, frame );
plate_cascade.detectMultiScale( frame, plates, config->detection_iteration_increase, config->detectionStrictness,
CV_HAAR_DO_CANNY_PRUNING,
//0|CV_HAAR_SCALE_IMAGE,
min_plate_size, max_plate_size );
if (config->debugTiming)
{
timespec endTime;
getTimeMonotonic(&endTime);
cout << "LBP Time: " << diffclock(startTime, endTime) << "ms." << endl;
}
return plates;
}
Boolean
_setupClockDriver_unix(ClockDriver* self)
{
if((self->type == SYSTEM_CLOCK_TYPE) && (_instanceCount > 0)) {
WARNING(THIS_COMPONENT"Only one instance of the system clock driver is allowed\n");
return FALSE;
}
INIT_INTERFACE(self);
INIT_DATA_CLOCKDRIVER(self, linuxphc);
INIT_CONFIG_CLOCKDRIVER(self, linuxphc);
_instanceCount++;
self->_instanceCount = &_instanceCount;
self->systemClock = TRUE;
resetIntPermanentAdev(&self->_adev);
getTimeMonotonic(self, &self->_initTime);
strncpy(self->name, SYSTEM_CLOCK_NAME, CLOCKDRIVER_NAME_MAX);
INFO(THIS_COMPONENT"Started Unix clock driver %s\n", self->name);
return TRUE;
}
void AlprImpl::setDetectRegion(bool detectRegion)
{
this->detectRegion = detectRegion;
if (detectRegion && this->stateDetector == NULL)
{
timespec startTime;
getTimeMonotonic(&startTime);
this->stateDetector = new StateDetector(this->config->country, this->config->runtimeBaseDir);
timespec endTime;
getTimeMonotonic(&endTime);
if (config->debugTiming)
cout << "State Identification Initialization Time: " << diffclock(startTime, endTime) << "ms." << endl;
}
}
// 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;
getTimeMonotonic(&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;
getTimeMonotonic(&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;
}
void OCR::performOCR(PipelineData* pipeline_data)
{
const int SPACE_CHAR_CODE = 32;
timespec startTime;
getTimeMonotonic(&startTime);
postProcessor.clear();
// Don't waste time on OCR processing if it is impossible to get sufficient characters
int total_char_spaces = 0;
for (unsigned int i = 0; i < pipeline_data->charRegions.size(); i++)
total_char_spaces += pipeline_data->charRegions[i].size();
if (total_char_spaces < config->postProcessMinCharacters)
{
pipeline_data->disqualify_reason = "Insufficient character boxes detected. No OCR performed.";
pipeline_data->disqualified = true;
return;
}
for (unsigned int i = 0; i < pipeline_data->thresholds.size(); i++)
{
// Make it black text on white background
bitwise_not(pipeline_data->thresholds[i], pipeline_data->thresholds[i]);
tesseract.SetImage((uchar*) pipeline_data->thresholds[i].data,
pipeline_data->thresholds[i].size().width, pipeline_data->thresholds[i].size().height,
pipeline_data->thresholds[i].channels(), pipeline_data->thresholds[i].step1());
int absolute_charpos = 0;
for (unsigned int line_idx = 0; line_idx < pipeline_data->charRegions.size(); line_idx++)
{
for (unsigned int j = 0; j < pipeline_data->charRegions[line_idx].size(); j++)
{
Rect expandedRegion = expandRect( pipeline_data->charRegions[line_idx][j], 2, 2, pipeline_data->thresholds[i].cols, pipeline_data->thresholds[i].rows) ;
tesseract.SetRectangle(expandedRegion.x, expandedRegion.y, expandedRegion.width, expandedRegion.height);
tesseract.Recognize(NULL);
tesseract::ResultIterator* ri = tesseract.GetIterator();
tesseract::PageIteratorLevel level = tesseract::RIL_SYMBOL;
do
{
const char* symbol = ri->GetUTF8Text(level);
float conf = ri->Confidence(level);
bool dontcare;
int fontindex = 0;
int pointsize = 0;
const char* fontName = ri->WordFontAttributes(&dontcare, &dontcare, &dontcare, &dontcare, &dontcare, &dontcare, &pointsize, &fontindex);
// Ignore NULL pointers, spaces, and characters that are way too small to be valid
if(symbol != 0 && symbol[0] != SPACE_CHAR_CODE && pointsize >= config->ocrMinFontSize)
{
postProcessor.addLetter(string(symbol), line_idx, absolute_charpos, conf);
if (this->config->debugOcr)
printf("charpos%d line%d: threshold %d: symbol %s, conf: %f font: %s (index %d) size %dpx\n", absolute_charpos, line_idx, i, symbol, conf, fontName, fontindex, pointsize);
bool indent = false;
tesseract::ChoiceIterator ci(*ri);
do
{
const char* choice = ci.GetUTF8Text();
//1/17/2016 adt adding check to avoid double adding same character if ci is same as symbol. Otherwise first choice will get doubled boost when choiceIterator run.
if (string(symbol) != string(choice))
postProcessor.addLetter(string(choice), line_idx, absolute_charpos, ci.Confidence());
if (this->config->debugOcr)
{
if (indent) printf("\t\t ");
printf("\t- ");
printf("%s conf: %f\n", choice, ci.Confidence());
}
indent = true;
}
while(ci.Next());
}
if (this->config->debugOcr)
printf("---------------------------------------------\n");
delete[] symbol;
}
while((ri->Next(level)));
delete ri;
absolute_charpos++;
}
}
}
if (config->debugTiming)
{
timespec endTime;
getTimeMonotonic(&endTime);
cout << "OCR Time: " << diffclock(startTime, endTime) << "ms." << endl;
}
}
void PlateLines::processImage(Mat inputImage, vector<TextLine> textLines, float sensitivity)
{
if (this->debug)
cout << "PlateLines findLines" << endl;
timespec startTime;
getTimeMonotonic(&startTime);
// Ignore input images that are pure white or pure black
Scalar avgPixelIntensity = mean(inputImage);
if (avgPixelIntensity[0] >= 252)
return;
else if (avgPixelIntensity[0] <= 3)
return;
// Do a bilateral filter to clean the noise but keep edges sharp
Mat smoothed(inputImage.size(), inputImage.type());
adaptiveBilateralFilter(inputImage, smoothed, Size(3,3), 45, 45);
int morph_elem = 2;
int morph_size = 2;
Mat element = getStructuringElement( morph_elem, Size( 2*morph_size + 1, 2*morph_size+1 ), Point( morph_size, morph_size ) );
Mat edges(inputImage.size(), inputImage.type());
Canny(smoothed, edges, 66, 133);
// Create a mask that is dilated based on the detected characters
Mat mask = Mat::zeros(inputImage.size(), CV_8U);
for (unsigned int i = 0; i < textLines.size(); i++)
{
vector<vector<Point> > polygons;
polygons.push_back(textLines[i].textArea);
fillPoly(mask, polygons, Scalar(255,255,255));
}
dilate(mask, mask, getStructuringElement( 1, Size( 1 + 1, 2*1+1 ), Point( 1, 1 ) ));
bitwise_not(mask, mask);
// AND canny edges with the character mask
bitwise_and(edges, mask, edges);
vector<PlateLine> hlines = this->getLines(edges, sensitivity, false);
vector<PlateLine> vlines = this->getLines(edges, sensitivity, true);
for (unsigned int i = 0; i < hlines.size(); i++)
this->horizontalLines.push_back(hlines[i]);
for (unsigned int i = 0; i < vlines.size(); i++)
this->verticalLines.push_back(vlines[i]);
// if debug is enabled, draw the image
if (this->debug)
{
Mat debugImgHoriz(edges.size(), edges.type());
Mat debugImgVert(edges.size(), edges.type());
edges.copyTo(debugImgHoriz);
edges.copyTo(debugImgVert);
cvtColor(debugImgHoriz,debugImgHoriz,CV_GRAY2BGR);
cvtColor(debugImgVert,debugImgVert,CV_GRAY2BGR);
for( size_t i = 0; i < this->horizontalLines.size(); i++ )
{
line( debugImgHoriz, this->horizontalLines[i].line.p1, this->horizontalLines[i].line.p2, Scalar(0,0,255), 1, CV_AA);
}
for( size_t i = 0; i < this->verticalLines.size(); i++ )
{
line( debugImgVert, this->verticalLines[i].line.p1, this->verticalLines[i].line.p2, Scalar(0,0,255), 1, CV_AA);
}
vector<Mat> images;
images.push_back(debugImgHoriz);
images.push_back(debugImgVert);
Mat dashboard = drawImageDashboard(images, debugImgVert.type(), 1);
displayImage(pipelineData->config, "Hough Lines", dashboard);
}
if (pipelineData->config->debugTiming)
{
timespec endTime;
getTimeMonotonic(&endTime);
cout << "Plate Lines Time: " << diffclock(startTime, endTime) << "ms." << endl;
}
}
AlprFullDetails AlprImpl::recognizeFullDetails(cv::Mat img, std::vector<cv::Rect> regionsOfInterest)
{
timespec startTime;
getTimeMonotonic(&startTime);
AlprFullDetails response;
response.results.epoch_time = getEpochTimeMs();
response.results.img_width = img.cols;
response.results.img_height = img.rows;
// Fix regions of interest in case they extend beyond the bounds of the image
for (unsigned int i = 0; i < regionsOfInterest.size(); i++)
regionsOfInterest[i] = expandRect(regionsOfInterest[i], 0, 0, img.cols, img.rows);
for (unsigned int i = 0; i < regionsOfInterest.size(); i++)
{
response.results.regionsOfInterest.push_back(AlprRegionOfInterest(regionsOfInterest[i].x, regionsOfInterest[i].y,
regionsOfInterest[i].width, regionsOfInterest[i].height));
}
if (!img.data)
{
// Invalid image
if (this->config->debugGeneral)
std::cerr << "Invalid image" << std::endl;
return response;
}
// Convert image to grayscale if required
Mat grayImg = img;
if (img.channels() > 2)
cvtColor( img, grayImg, CV_BGR2GRAY );
// Prewarp the image and ROIs if configured]
std::vector<cv::Rect> warpedRegionsOfInterest = regionsOfInterest;
// Warp the image if prewarp is provided
grayImg = prewarp->warpImage(grayImg);
warpedRegionsOfInterest = prewarp->projectRects(regionsOfInterest, grayImg.cols, grayImg.rows, false);
vector<PlateRegion> warpedPlateRegions;
// Find all the candidate regions
if (config->skipDetection == false)
{
warpedPlateRegions = plateDetector->detect(grayImg, warpedRegionsOfInterest);
}
else
{
// They have elected to skip plate detection. Instead, return a list of plate regions
// based on their regions of interest
for (unsigned int i = 0; i < warpedRegionsOfInterest.size(); i++)
{
PlateRegion pr;
pr.rect = cv::Rect(warpedRegionsOfInterest[i]);
warpedPlateRegions.push_back(pr);
}
}
queue<PlateRegion> plateQueue;
for (unsigned int i = 0; i < warpedPlateRegions.size(); i++)
plateQueue.push(warpedPlateRegions[i]);
int platecount = 0;
while(!plateQueue.empty())
{
PlateRegion plateRegion = plateQueue.front();
plateQueue.pop();
PipelineData pipeline_data(img, grayImg, plateRegion.rect, config);
pipeline_data.prewarp = prewarp;
timespec platestarttime;
getTimeMonotonic(&platestarttime);
LicensePlateCandidate lp(&pipeline_data);
lp.recognize();
bool plateDetected = false;
if (!pipeline_data.disqualified)
{
AlprPlateResult plateResult;
plateResult.region = defaultRegion;
plateResult.regionConfidence = 0;
plateResult.plate_index = platecount++;
// If using prewarp, remap the plate corners to the original image
vector<Point2f> cornerPoints = pipeline_data.plate_corners;
cornerPoints = prewarp->projectPoints(cornerPoints, true);
for (int pointidx = 0; pointidx < 4; pointidx++)
{
plateResult.plate_points[pointidx].x = (int) cornerPoints[pointidx].x;
plateResult.plate_points[pointidx].y = (int) cornerPoints[pointidx].y;
}
if (detectRegion)
{
std::vector<StateCandidate> state_candidates = stateDetector->detect(pipeline_data.color_deskewed.data,
pipeline_data.color_deskewed.elemSize(),
pipeline_data.color_deskewed.cols,
pipeline_data.color_deskewed.rows);
if (state_candidates.size() > 0)
{
plateResult.region = state_candidates[0].state_code;
plateResult.regionConfidence = (int) state_candidates[0].confidence;
}
}
if (plateResult.region.length() > 0 && ocr->postProcessor.regionIsValid(plateResult.region) == false)
{
std::cerr << "Invalid pattern provided: " << plateResult.region << std::endl;
std::cerr << "Valid patterns are located in the " << config->country << ".patterns file" << std::endl;
}
ocr->performOCR(&pipeline_data);
ocr->postProcessor.analyze(plateResult.region, topN);
timespec resultsStartTime;
getTimeMonotonic(&resultsStartTime);
const vector<PPResult> ppResults = ocr->postProcessor.getResults();
int bestPlateIndex = 0;
cv::Mat charTransformMatrix = getCharacterTransformMatrix(&pipeline_data);
for (unsigned int pp = 0; pp < ppResults.size(); pp++)
{
// Set our "best plate" match to either the first entry, or the first entry with a postprocessor template match
if (bestPlateIndex == 0 && ppResults[pp].matchesTemplate)
bestPlateIndex = plateResult.topNPlates.size();
AlprPlate aplate;
aplate.characters = ppResults[pp].letters;
aplate.overall_confidence = ppResults[pp].totalscore;
aplate.matches_template = ppResults[pp].matchesTemplate;
// Grab detailed results for each character
for (unsigned int c_idx = 0; c_idx < ppResults[pp].letter_details.size(); c_idx++)
{
AlprChar character_details;
character_details.character = ppResults[pp].letter_details[c_idx].letter;
character_details.confidence = ppResults[pp].letter_details[c_idx].totalscore;
cv::Rect char_rect = pipeline_data.charRegions[ppResults[pp].letter_details[c_idx].charposition];
std::vector<AlprCoordinate> charpoints = getCharacterPoints(char_rect, charTransformMatrix );
for (int cpt = 0; cpt < 4; cpt++)
character_details.corners[cpt] = charpoints[cpt];
aplate.character_details.push_back(character_details);
}
plateResult.topNPlates.push_back(aplate);
}
if (plateResult.topNPlates.size() > bestPlateIndex)
{
AlprPlate bestPlate;
bestPlate.characters = plateResult.topNPlates[bestPlateIndex].characters;
bestPlate.matches_template = plateResult.topNPlates[bestPlateIndex].matches_template;
bestPlate.overall_confidence = plateResult.topNPlates[bestPlateIndex].overall_confidence;
bestPlate.character_details = plateResult.topNPlates[bestPlateIndex].character_details;
plateResult.bestPlate = bestPlate;
}
timespec plateEndTime;
getTimeMonotonic(&plateEndTime);
plateResult.processing_time_ms = diffclock(platestarttime, plateEndTime);
if (config->debugTiming)
{
cout << "Result Generation Time: " << diffclock(resultsStartTime, plateEndTime) << "ms." << endl;
}
if (plateResult.topNPlates.size() > 0)
{
plateDetected = true;
response.results.plates.push_back(plateResult);
}
}
if (!plateDetected)
{
// Not a valid plate
// Check if this plate has any children, if so, send them back up for processing
for (unsigned int childidx = 0; childidx < plateRegion.children.size(); childidx++)
{
plateQueue.push(plateRegion.children[childidx]);
}
}
}
// Unwarp plate regions if necessary
prewarp->projectPlateRegions(warpedPlateRegions, grayImg.cols, grayImg.rows, true);
response.plateRegions = warpedPlateRegions;
timespec endTime;
getTimeMonotonic(&endTime);
response.results.total_processing_time_ms = diffclock(startTime, endTime);
if (config->debugTiming)
{
cout << "Total Time to process image: " << diffclock(startTime, endTime) << "ms." << endl;
}
if (config->debugGeneral && config->debugShowImages)
{
for (unsigned int i = 0; i < regionsOfInterest.size(); i++)
{
rectangle(img, regionsOfInterest[i], Scalar(0,255,0), 2);
}
for (unsigned int i = 0; i < response.plateRegions.size(); i++)
{
rectangle(img, response.plateRegions[i].rect, Scalar(0, 0, 255), 2);
}
for (unsigned int i = 0; i < response.results.plates.size(); i++)
{
// Draw a box around the license plate
for (int z = 0; z < 4; z++)
{
AlprCoordinate* coords = response.results.plates[i].plate_points;
Point p1(coords[z].x, coords[z].y);
Point p2(coords[(z + 1) % 4].x, coords[(z + 1) % 4].y);
line(img, p1, p2, Scalar(255,0,255), 2);
}
// Draw the individual character boxes
for (int q = 0; q < response.results.plates[i].bestPlate.character_details.size(); q++)
{
AlprChar details = response.results.plates[i].bestPlate.character_details[q];
line(img, Point(details.corners[0].x, details.corners[0].y), Point(details.corners[1].x, details.corners[1].y), Scalar(0,255,0), 1);
line(img, Point(details.corners[1].x, details.corners[1].y), Point(details.corners[2].x, details.corners[2].y), Scalar(0,255,0), 1);
line(img, Point(details.corners[2].x, details.corners[2].y), Point(details.corners[3].x, details.corners[3].y), Scalar(0,255,0), 1);
line(img, Point(details.corners[3].x, details.corners[3].y), Point(details.corners[0].x, details.corners[0].y), Scalar(0,255,0), 1);
}
}
displayImage(config, "Main Image", img);
// Sleep 1ms
sleep_ms(1);
}
if (config->debugPauseOnFrame)
{
// Pause indefinitely until they press a key
while ((char) cv::waitKey(50) == -1)
{}
}
return response;
}
void CharacterAnalysis::analyze()
{
timespec startTime;
getTimeMonotonic(&startTime);
pipeline_data->clearThresholds();
pipeline_data->thresholds = produceThresholds(pipeline_data->crop_gray, config);
timespec contoursStartTime;
getTimeMonotonic(&contoursStartTime);
pipeline_data->textLines.clear();
for (unsigned int i = 0; i < pipeline_data->thresholds.size(); i++)
{
TextContours tc(pipeline_data->thresholds[i]);
allTextContours.push_back(tc);
}
if (config->debugTiming)
{
timespec contoursEndTime;
getTimeMonotonic(&contoursEndTime);
cout << " -- Character Analysis Find Contours Time: " << diffclock(contoursStartTime, contoursEndTime) << "ms." << endl;
}
//Mat img_equalized = equalizeBrightness(img_gray);
timespec filterStartTime;
getTimeMonotonic(&filterStartTime);
for (unsigned int i = 0; i < pipeline_data->thresholds.size(); i++)
{
this->filter(pipeline_data->thresholds[i], allTextContours[i]);
if (config->debugCharAnalysis)
cout << "Threshold " << i << " had " << allTextContours[i].getGoodIndicesCount() << " good indices." << endl;
}
if (config->debugTiming)
{
timespec filterEndTime;
getTimeMonotonic(&filterEndTime);
cout << " -- Character Analysis Filter Time: " << diffclock(filterStartTime, filterEndTime) << "ms." << endl;
}
PlateMask plateMask(pipeline_data);
plateMask.findOuterBoxMask(allTextContours);
pipeline_data->hasPlateBorder = plateMask.hasPlateMask;
pipeline_data->plateBorderMask = plateMask.getMask();
if (plateMask.hasPlateMask)
{
// Filter out bad contours now that we have an outer box mask...
for (unsigned int i = 0; i < pipeline_data->thresholds.size(); i++)
{
filterByOuterMask(allTextContours[i]);
}
}
int bestFitScore = -1;
int bestFitIndex = -1;
for (unsigned int i = 0; i < pipeline_data->thresholds.size(); i++)
{
int segmentCount = allTextContours[i].getGoodIndicesCount();
if (segmentCount > bestFitScore)
{
bestFitScore = segmentCount;
bestFitIndex = i;
bestThreshold = pipeline_data->thresholds[i];
bestContours = allTextContours[i];
}
}
if (this->config->debugCharAnalysis)
cout << "Best fit score: " << bestFitScore << " Index: " << bestFitIndex << endl;
if (bestFitScore <= 1)
{
pipeline_data->disqualified = true;
pipeline_data->disqualify_reason = "Low best fit score in characteranalysis";
return;
}
//getColorMask(img, allContours, allHierarchy, charSegments);
if (this->config->debugCharAnalysis)
{
Mat img_contours = bestContours.drawDebugImage(bestThreshold);
displayImage(config, "Matching Contours", img_contours);
}
LineFinder lf(pipeline_data);
vector<vector<Point> > linePolygons = lf.findLines(pipeline_data->crop_gray, bestContours);
vector<TextLine> tempTextLines;
for (unsigned int i = 0; i < linePolygons.size(); i++)
{
vector<Point> linePolygon = linePolygons[i];
LineSegment topLine = LineSegment(linePolygon[0].x, linePolygon[0].y, linePolygon[1].x, linePolygon[1].y);
LineSegment bottomLine = LineSegment(linePolygon[3].x, linePolygon[3].y, linePolygon[2].x, linePolygon[2].y);
vector<Point> textArea = getCharArea(topLine, bottomLine);
TextLine textLine(textArea, linePolygon, pipeline_data->crop_gray.size());
tempTextLines.push_back(textLine);
}
filterBetweenLines(bestThreshold, bestContours, tempTextLines);
// Sort the lines from top to bottom.
std::sort(tempTextLines.begin(), tempTextLines.end(), sort_text_line);
// Now that we've filtered a few more contours, re-do the text area.
for (unsigned int i = 0; i < tempTextLines.size(); i++)
{
vector<Point> updatedTextArea = getCharArea(tempTextLines[i].topLine, tempTextLines[i].bottomLine);
vector<Point> linePolygon = tempTextLines[i].linePolygon;
if (updatedTextArea.size() > 0 && linePolygon.size() > 0)
{
pipeline_data->textLines.push_back(TextLine(updatedTextArea, linePolygon, pipeline_data->crop_gray.size()));
}
}
pipeline_data->plate_inverted = isPlateInverted();
if (pipeline_data->textLines.size() > 0)
{
int confidenceDrainers = 0;
int charSegmentCount = this->bestContours.getGoodIndicesCount();
if (charSegmentCount == 1)
confidenceDrainers += 91;
else if (charSegmentCount < 5)
confidenceDrainers += (5 - charSegmentCount) * 10;
// Use the angle for the first line -- assume they'll always be parallel for multi-line plates
int absangle = abs(pipeline_data->textLines[0].topLine.angle);
if (absangle > config->maxPlateAngleDegrees)
confidenceDrainers += 91;
else if (absangle > 1)
confidenceDrainers += (config->maxPlateAngleDegrees - absangle) ;
// If a multiline plate has only one line, disqualify
if (pipeline_data->isMultiline && pipeline_data->textLines.size() < 2)
{
if (config->debugCharAnalysis)
std::cout << "Did not detect multiple lines on multi-line plate" << std::endl;
confidenceDrainers += 95;
}
if (confidenceDrainers >= 90)
{
pipeline_data->disqualified = true;
pipeline_data->disqualify_reason = "Low confidence in characteranalysis";
}
else
{
float confidence = 100 - confidenceDrainers;
pipeline_data->confidence_weights.setScore("CHARACTER_ANALYSIS_SCORE", confidence, 1.0);
}
}
else
{
pipeline_data->disqualified = true;
pipeline_data->disqualify_reason = "No text lines found in characteranalysis";
}
if (config->debugTiming)
{
timespec endTime;
getTimeMonotonic(&endTime);
cout << "Character Analysis Time: " << diffclock(startTime, endTime) << "ms." << endl;
}
// Draw debug dashboard
if (this->pipeline_data->config->debugCharAnalysis && pipeline_data->textLines.size() > 0)
{
vector<Mat> tempDash;
for (unsigned int z = 0; z < pipeline_data->thresholds.size(); z++)
{
Mat tmp(pipeline_data->thresholds[z].size(), pipeline_data->thresholds[z].type());
pipeline_data->thresholds[z].copyTo(tmp);
cvtColor(tmp, tmp, CV_GRAY2BGR);
tempDash.push_back(tmp);
}
Mat bestVal(this->bestThreshold.size(), this->bestThreshold.type());
this->bestThreshold.copyTo(bestVal);
cvtColor(bestVal, bestVal, CV_GRAY2BGR);
for (unsigned int z = 0; z < this->bestContours.size(); z++)
{
Scalar dcolor(255,0,0);
if (this->bestContours.goodIndices[z])
dcolor = Scalar(0,255,0);
drawContours(bestVal, this->bestContours.contours, z, dcolor, 1);
}
tempDash.push_back(bestVal);
displayImage(config, "Character Region Step 1 Thresholds", drawImageDashboard(tempDash, bestVal.type(), 3));
}
}
vector<PlateRegion> DetectorCUDA::doCascade(Mat frame, int offset_x, int offset_y)
{
if (frame.cols > config->maxDetectionInputWidth)
{
// The frame is too wide
this->scale_factor = ((float) config->maxDetectionInputWidth) / ((float) frame.cols);
if (config->debugDetector)
std::cout << "Input detection image is too wide. Resizing with scale: " << this->scale_factor << endl;
}
else if (frame.rows > config->maxDetectionInputHeight)
{
// The frame is too tall
this->scale_factor = ((float) config->maxDetectionInputHeight) / ((float) frame.rows);
if (config->debugDetector)
std::cout << "Input detection image is too tall. Resizing with scale: " << this->scale_factor << endl;
}
int w = frame.size().width;
int h = frame.size().height;
vector<Rect> plates;
equalizeHist( frame, frame );
resize(frame, frame, Size(w * this->scale_factor, h * this->scale_factor));
//-- Detect plates
timespec startTime;
getTimeMonotonic(&startTime);
float maxWidth = ((float) w) * (config->maxPlateWidthPercent / 100.0f) * this->scale_factor;
float maxHeight = ((float) h) * (config->maxPlateHeightPercent / 100.0f) * this->scale_factor;
Size minSize(config->minPlateSizeWidthPx * this->scale_factor, config->minPlateSizeHeightPx * this->scale_factor);
gpu::GpuMat cudaFrame, plateregions_buffer;
Mat plateregions_downloaded;
cudaFrame.upload(frame);
int numdetected = cuda_cascade.detectMultiScale(cudaFrame, plateregions_buffer, (double) config->detection_iteration_increase, config->detectionStrictness, minSize);
plateregions_buffer.colRange(0, numdetected).download(plateregions_downloaded);
for (int i = 0; i < numdetected; ++i)
{
plates.push_back(plateregions_downloaded.ptr<cv::Rect>()[i]);
}
if (config->debugTiming)
{
timespec endTime;
getTimeMonotonic(&endTime);
cout << "LBP Time: " << diffclock(startTime, endTime) << "ms." << endl;
}
for( unsigned int i = 0; i < plates.size(); i++ )
{
plates[i].x = (plates[i].x / scale_factor) + offset_x;
plates[i].y = (plates[i].y / scale_factor) + offset_y;
plates[i].width = plates[i].width / scale_factor;
plates[i].height = plates[i].height / scale_factor;
}
vector<PlateRegion> orderedRegions = aggregateRegions(plates);
return orderedRegions;
}
