mirror of
https://github.com/kerberos-io/openalpr-base.git
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149 lines
4.3 KiB
C++
149 lines
4.3 KiB
C++
/*
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* Copyright (c) 2015 OpenALPR Technology, Inc.
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* Open source Automated License Plate Recognition [http://www.openalpr.com]
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*
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* This file is part of OpenALPR.
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*
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* OpenALPR is free software: you can redistribute it and/or modify
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* it under the terms of the GNU Affero General Public License
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* version 3 as published by the Free Software Foundation
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*
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* This program is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU Affero General Public License for more details.
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*
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* You should have received a copy of the GNU Affero General Public License
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* along with this program. If not, see <http://www.gnu.org/licenses/>.
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*/
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#include "detectorcpu.h"
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using namespace cv;
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using namespace std;
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namespace alpr
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{
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DetectorCPU::DetectorCPU(Config* config, PreWarp* prewarp) : Detector(config, prewarp) {
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if( this->plate_cascade.load( get_detector_file() ) )
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{
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this->loaded = true;
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}
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else
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{
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this->loaded = false;
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printf("--(!)Error loading CPU classifier %s\n", get_detector_file().c_str());
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}
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}
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DetectorCPU::~DetectorCPU() {
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}
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vector<PlateRegion> DetectorCPU::detect(Mat frame, std::vector<cv::Rect> regionsOfInterest)
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{
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Mat frame_gray;
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if (frame.channels() > 2)
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{
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cvtColor( frame, frame_gray, CV_BGR2GRAY );
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}
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else
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{
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frame.copyTo(frame_gray);
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}
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// Apply the detection mask if it has been specified by the user
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if (detector_mask.mask_loaded)
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frame_gray = detector_mask.apply_mask(frame_gray);
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vector<PlateRegion> detectedRegions;
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for (int i = 0; i < regionsOfInterest.size(); i++)
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{
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Rect roi = regionsOfInterest[i];
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// Adjust the ROI to be inside the detection mask (if it exists)
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if (detector_mask.mask_loaded)
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roi = detector_mask.getRoiInsideMask(roi);
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// Sanity check. If roi width or height is less than minimum possible plate size,
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// then skip it
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if ((roi.width < config->minPlateSizeWidthPx) ||
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(roi.height < config->minPlateSizeHeightPx))
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continue;
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Mat cropped = frame_gray(roi);
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vector<PlateRegion> subRegions = doCascade(cropped, roi.x, roi.y);
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for (int j = 0; j < subRegions.size(); j++)
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detectedRegions.push_back(subRegions[j]);
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}
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return detectedRegions;
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}
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vector<PlateRegion> DetectorCPU::doCascade(Mat frame, int offset_x, int offset_y)
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{
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int w = frame.size().width;
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int h = frame.size().height;
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float scale_factor = computeScaleFactor(w, h);
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vector<Rect> plates;
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equalizeHist( frame, frame );
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if (scale_factor != 1.0)
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resize(frame, frame, Size(w * scale_factor, h * scale_factor));
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//-- Detect plates
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timespec startTime;
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getTimeMonotonic(&startTime);
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float maxWidth = ((float) w) * (config->maxPlateWidthPercent / 100.0f) * scale_factor;
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float maxHeight = ((float) h) * (config->maxPlateHeightPercent / 100.0f) * scale_factor;
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Size minSize(config->minPlateSizeWidthPx * scale_factor, config->minPlateSizeHeightPx * scale_factor);
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Size maxSize(maxWidth, maxHeight);
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plate_cascade.detectMultiScale( frame, plates, config->detection_iteration_increase, config->detectionStrictness,
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CV_HAAR_DO_CANNY_PRUNING,
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//0|CV_HAAR_SCALE_IMAGE,
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minSize, maxSize );
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if (config->debugTiming)
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{
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timespec endTime;
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getTimeMonotonic(&endTime);
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cout << "LBP Time: " << diffclock(startTime, endTime) << "ms." << endl;
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}
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for( unsigned int i = 0; i < plates.size(); i++ )
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{
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plates[i].x = (plates[i].x / scale_factor);
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plates[i].y = (plates[i].y / scale_factor);
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plates[i].width = plates[i].width / scale_factor;
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plates[i].height = plates[i].height / scale_factor;
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// Ensure that the rectangle isn't < 0 or > maxWidth/Height
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plates[i] = expandRect(plates[i], 0, 0, w, h);
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plates[i].x = plates[i].x + offset_x;
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plates[i].y = plates[i].y + offset_y;
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}
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vector<PlateRegion> orderedRegions = aggregateRegions(plates);
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return orderedRegions;
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}
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}
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