mirror of
https://github.com/kerberos-io/openalpr-base.git
synced 2025-10-06 14:07:39 +08:00
153 lines
4.5 KiB
C++
153 lines
4.5 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 "detectormask.h"
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#include "prewarp.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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DetectorMask::DetectorMask(Config* config, PreWarp* prewarp) {
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mask_loaded = false;
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resized_mask_loaded = false;
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this->config = config;
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this->prewarp = prewarp;
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last_prewarp_hash = "";
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}
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DetectorMask::~DetectorMask() {
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}
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void DetectorMask::setMask(Mat orig_mask) {
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this->mask = orig_mask;
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if (orig_mask.channels() > 2)
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cvtColor( orig_mask, this->mask, CV_BGR2GRAY );
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else
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this->mask = orig_mask;
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// Threshold the mask so that the values are either 0 or 255 (no shades of gray))
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threshold(this->mask, this->mask, 1, 255, cv::THRESH_BINARY);
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// Calculate the biggest rectangle that covers all the whitespace
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// Rather than using contours, go row by row, column by column until you hit
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// a white pixel and stop. Should be faster and a little simpler
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unsigned int top_bound = 0, bottom_bound = 0, left_bound = 0, right_bound = 0;
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cout << mask.col(20).cols << " - " << mask.col(20).rows << endl;
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for (top_bound = 0; top_bound < mask.rows; top_bound++)
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if (countNonZero(mask.row(top_bound)) > 0) break;
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for (bottom_bound = mask.rows - 1; bottom_bound >= 0; bottom_bound--)
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if (countNonZero(mask.row(bottom_bound)) > 0) break;
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for (left_bound = 0; left_bound < mask.cols; left_bound++)
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if (countNonZero(mask.col(left_bound)) > 0) break;
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for (right_bound = mask.rows - 1; right_bound >= 0; right_bound--)
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if (countNonZero(mask.col(right_bound)) > 0) break;
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if (left_bound >= right_bound || top_bound >= bottom_bound)
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{
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cerr << "Invalid mask" << endl;
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return;
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}
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scan_area.x = left_bound;
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scan_area.y = top_bound;
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scan_area.width = right_bound - left_bound;
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scan_area.height = bottom_bound - top_bound;
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// Mat debug(this->mask.size(), mask.type());
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// this->mask.copyTo(debug);
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// cvtColor(debug, debug, CV_GRAY2BGR);
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// rectangle(debug, scan_area, Scalar(0,255,0), 2);
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// drawAndWait(debug);
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mask_loaded = true;
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}
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cv::Size DetectorMask::mask_size() {
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return mask.size();
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}
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// Provided a region of interest, truncate it if the mask cuts off a portion of it.
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// No reason to analyze extra content
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cv::Rect DetectorMask::getRoiInsideMask(cv::Rect roi) {
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if (prewarp->valid)
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{
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cv::Rect warped_scan_area = prewarp->projectRect(scan_area, mask.cols, mask.rows, false);
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Rect roi_intersection = roi & scan_area;
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return roi_intersection;
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}
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else
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{
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Rect roi_intersection = roi & scan_area;
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return roi_intersection;
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}
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}
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// Checks if the provided region is partially covered by the mask
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// If so, it is disqualified
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bool DetectorMask::region_is_masked(cv::Rect region) {
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int MIN_WHITENESS = 253;
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// If the mean pixel value over the crop is very white (e.g., > 253 out of 255)
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// then this is in the white area of the mask and we'll use it
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Mat mask_crop = mask(region);
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double mean_value = mean(mask_crop)[0];
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return mean_value >= MIN_WHITENESS;
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}
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Mat DetectorMask::apply_mask(Mat image) {
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if (!mask_loaded)
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return image;
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if (!resized_mask_loaded || last_prewarp_hash != prewarp->toString())
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{
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resize(mask, resized_mask, image.size());
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if (prewarp->valid)
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{
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resized_mask = prewarp->warpImage(resized_mask);
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}
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last_prewarp_hash = prewarp->toString();
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resized_mask_loaded = true;
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}
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if (image.size() != resized_mask.size())
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{
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return image;
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}
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Mat response(image.size(), image.type());
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image.copyTo(response, resized_mask);
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return response;
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}
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} |