m53297601
/
EasyPR
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

add slide windows and mser- method

Browse Source
v1.6alpha
liuruoze 10 years ago
parent ad45ffac85
commit cf33fca08b
11 changed files with 138 additions and 100 deletions
Show Stats Download Patch File Download Diff File

24
accuracy.txt
Unescape View File

@ -1593,3 +1593,27 @@
总图片数:200, 未识出图片:7, 定位率:96.5%
平均字符差距:0.689119, 完全匹配数:132, 完全匹配率:68.3938%
总时间:178秒, 平均执行时间:0.89秒
2016-06-17 12:59:08
总图片数:50, 未识出图片:27, 定位率:46%
平均字符差距:2.43478, 完全匹配数:6, 完全匹配率:26.087%
总时间:587秒, 平均执行时间:11.74秒
2016-06-17 14:17:02
总图片数:50, 未识出图片:50, 定位率:0%
平均字符差距:0, 完全匹配数:0, 完全匹配率:0%
总时间:342秒, 平均执行时间:6.84秒
2016-06-17 14:35:54
总图片数:50, 未识出图片:50, 定位率:0%
平均字符差距:0, 完全匹配数:0, 完全匹配率:0%
总时间:424秒, 平均执行时间:8.48秒
2016-06-17 14:41:32
总图片数:50, 未识出图片:50, 定位率:0%
平均字符差距:0, 完全匹配数:0, 完全匹配率:0%
总时间:234秒, 平均执行时间:4.68秒
2016-06-17 15:00:50
总图片数:50, 未识出图片:50, 定位率:0%
平均字符差距:0, 完全匹配数:0, 完全匹配率:0%
总时间:331秒, 平均执行时间:6.62秒
2016-06-17 15:16:31
总图片数:200, 未识出图片:7, 定位率:96.5%
平均字符差距:0.689119, 完全匹配数:132, 完全匹配率:68.3938%
总时间:289秒, 平均执行时间:1.445秒

7
include/easypr/core/character.hpp
Unescape View File

@ -54,21 +54,20 @@ namespace easypr {
private:
//! character mat
Mat m_characterMat;
//! character rect
Rect m_characterPos;
//! character str
String m_characterStr;
//! character likely
double m_score;
//! weather is chinese
bool isChinese;
};
} /*! \namespace easypr*/

2
include/easypr/core/core_func.h
Unescape View File

@ -57,7 +57,7 @@ Color getPlateType(const Mat& src, const bool adaptive_minsv);
//! 直方图均衡
Mat histeq(Mat in);
Mat features(Mat in, int sizeData);
Mat charFeatures(Mat in, int sizeData);
Rect GetCenterRect(Mat& in);
Mat CutTheRect(Mat& in, Rect& rect);
int ThresholdOtsu(Mat mat);

2
include/easypr/core/feature.h
Unescape View File

@ -7,7 +7,7 @@ namespace easypr {
//! 获得车牌的特征数
cv::Mat getTheFeatures(cv::Mat in);
cv::Mat getHistogram(cv::Mat in);
//! EasyPR的getFeatures回调函数
//! 用于从车牌的image生成svm的训练特征features

BIN
resources/image/test.jpg
View File

Binary file not shown.
Side by Side Swipe Overlay

Before

Width:  |  Height:  |  Size: 26 KiB

After

Width:  |  Height:  |  Size: 270 KiB

2
src/core/better_mser.cpp
Unescape View File

@ -778,7 +778,7 @@ namespace cv
// dont need when plate is blue
preprocess1(src, level_size);
if (!params.pass2Only)
//pass(src, msers, bboxes, size, level_size, 0);
pass(src, msers, bboxes, size, level_size, 0);
// brighter to darker (MSER-)
preprocess2(src, level_size);

31
src/core/chars_identify.cpp
Unescape View File

@ -1,4 +1,5 @@
#include "easypr/core/chars_identify.h"
#include "easypr/core/character.hpp"
#include "easypr/config.h"
#include "easypr/core/core_func.h"
@ -96,7 +97,7 @@ namespace easypr {
}
bool CharsIdentify::isCharacter(cv::Mat input, std::string& label, float& maxVal, bool isChinese) {
cv::Mat feature = features(input, kPredictSize);
cv::Mat feature = charFeatures(input, kPredictSize);
auto index = static_cast<int>(classify(feature, maxVal, isChinese));
if (isChinese)
@ -118,8 +119,32 @@ namespace easypr {
return false;
}
/*bool CharsIdentify::charsJudge(std::vector<CCharacter>& charVec) {
cv::Mat feature = charFeatures(input, kPredictSize);
auto index = static_cast<int>(classify(feature, maxVal, isChinese));
if (isChinese)
std::cout << "maxVal:" << maxVal << std::endl;
if (maxVal >= 0.9) {
if (index < kCharactersNumber) {
label = std::make_pair(kChars[index], kChars[index]).second;
}
else {
const char* key = kChars[index];
std::string s = key;
std::string province = kv_->get(s);
label = std::make_pair(s, province).second;
}
return true;
}
else
return false;
}*/
std::pair<std::string, std::string> CharsIdentify::identify(cv::Mat input, bool isChinese) {
cv::Mat feature = features(input, kPredictSize);
cv::Mat feature = charFeatures(input, kPredictSize);
float maxVal = -2;
auto index = static_cast<int>(classify(feature, maxVal, isChinese));
if (index < kCharactersNumber) {
@ -139,7 +164,7 @@ namespace easypr {
size_t input_size = inputs.size();
for (size_t i = 0; i < input_size; i++) {
Mat input = inputs[i];
cv::Mat feature = features(input, kPredictSize);
cv::Mat feature = charFeatures(input, kPredictSize);
featureRows.push_back(feature);
}

103
src/core/core_func.cpp
Unescape View File

@ -685,7 +685,7 @@ Rect GetCenterRect(Mat &in) {
return _rect;
}
Mat features(Mat in, int sizeData) {
Mat charFeatures(Mat in, int sizeData) {
//抠取中间区域
@ -720,8 +720,7 @@ Mat features(Mat in, int sizeData) {
}
for (int x = 0; x < lowData.cols; x++) {
for (int y = 0; y < lowData.rows; y++) {
out.at<float>(j) += (float) lowData.at < unsigned
char > (x, y);
out.at<float>(j) += (float) lowData.at <unsigned char> (x, y);
j++;
}
}
@ -952,99 +951,56 @@ bool verifyRotatedPlateSizes(RotatedRect mr) {
return true;
}
//! use verify size to first generate candidates
Mat mserMatch(const Mat &src, Mat &match, const Color r,
std::vector<RotatedRect>& out_plateRect, std::vector<Rect>& out_charRect) {
std::vector<Mat> channelImages;
std::vector<int> flags;
Mat image = src;
std::vector<RotatedRect> plateRects;
std::vector<Rect> charRects;
// only conside blue plate
if (1) {
Mat grayImage;
cvtColor(src, grayImage, COLOR_BGR2GRAY);
channelImages.push_back(grayImage);
flags.push_back(0);
//Mat singleChannelImage;
//extractChannel(src, singleChannelImage, 2);
//channelImages.push_back(singleChannelImage);
//flags.push_back(0);
}
std::vector<std::vector<std::vector<Point>>> all_contours;
std::vector<std::vector<Rect>> all_boxes;
all_contours.resize(channelImages.size());
all_boxes.resize(channelImages.size());
std::vector<std::vector<Point>> all_contours;
std::vector<Rect> all_boxes;
for (int i = 0; i < (int)channelImages.size(); ++i)
{
Ptr<MSER> mser;
std::vector<CCharacter> charVec;
Mat channelImage = channelImages[i];
//int scale_size = 1600;
//double scale_ratio = 1;
//Mat image = scaleImage(channelImage, Size(scale_size, scale_size), scale_ratio);
Mat image = channelImage;
match = Mat::zeros(image.rows, image.cols, image.type());
Mat result = image.clone();
cvtColor(result, result, COLOR_GRAY2BGR);
int imageArea = image.rows * image.cols;
mser = MSER::create(1, 30, int(0.05 * imageArea));
mser->detectRegions(image, all_contours, all_boxes);
if (3 == flags[i]) {
mser = MSER::create(3, 30, int(0.05 * imageArea));
}
else {
mser = MSER::create(1, 30, int(0.05 * imageArea));
}
mser->detectRegions(image, all_contours[i], all_boxes[i]);
size_t size = all_contours[i].size();
size_t size = all_contours.size();
int char_index = 0;
for (size_t index = 0; index < size; index++) {
Rect rect = all_boxes[i][index];
std::vector<Point> contour = all_contours[i][index];
Rect rect = all_boxes[index];
std::vector<Point> contour = all_contours[index];
RotatedRect rrect = minAreaRect(Mat(contour));
if (verifyRotatedPlateSizes(rrect)) {
//cv::rectangle(result, rrect.boundingRect(), Scalar(0, 255, 0));
Point2f rect_points[4];
rrect.points(rect_points);
for (int j = 0; j < 4; j++)
line(result, rect_points[j], rect_points[(j + 1) % 4], Scalar(0, 255, 0), 1, 8);
plateRects.push_back(rrect);
}
if (verifyCharSizes(rect)) {
float aspect = float(rect.width) / float(rect.height);
Mat region = image(rect);
Mat binary_region;
threshold(region, binary_region, 0, 255, CV_THRESH_BINARY | CV_THRESH_OTSU);
Mat charInput = preprocessChar(binary_region, 20);
std::string label = "";
float maxVal = -2.f;
// use mserMat
Mat mserMat = adaptive_image_from_points(contour, rect, Size(20, 20));
// use charMat
bool isCharacter = CharsIdentify::instance()->isCharacter(charInput, label, maxVal);
if (1)
{
std::stringstream ss(std::stringstream::in | std::stringstream::out);
ss << "resources/image/tmp/character" << char_index++ << ".jpg";
imwrite(ss.str(), mserMat);
}
//if (0)
//{
// std::stringstream ss(std::stringstream::in | std::stringstream::out);
// ss << "resources/image/tmp/character" << char_index++ << ".jpg";
// imwrite(ss.str(), mserMat);
//}
if (1) {
//match(rect) = min(max(0, int(maxVal * 255)),255);
@ -1053,7 +1009,7 @@ Mat mserMatch(const Mat &src, Mat &match, const Color r,
cv::rectangle(result, rect, Scalar(255, 0, 0));
Point center(rect.tl().x + rect.width / 2, rect.tl().y + rect.height / 2);
cv::circle(result, center, 3, Scalar(0, 255, 0), 2);
//cv::circle(result, center, 3, Scalar(0, 255, 0), 2);
charRects.push_back(rect);
out_charRect.push_back(rect);
@ -1066,9 +1022,7 @@ Mat mserMatch(const Mat &src, Mat &match, const Color r,
}
}
}
for (auto prect : plateRects) {
float areasum = 0.f;
int count = 0;
@ -1106,7 +1060,7 @@ Mat mserMatch(const Mat &src, Mat &match, const Color r,
if (ratio - 0.5f > 0 && count >= 5) {
std::cout << "ratio:" << ratio << std::endl;
std::cout << "count:" << count << std::endl;
cv::rectangle(result, prect.boundingRect(), Scalar(0, 255, 0));
//cv::rectangle(result, prect.boundingRect(), Scalar(0, 255, 0));
out_plateRect.push_back(prect);
}
}
@ -1115,7 +1069,6 @@ Mat mserMatch(const Mat &src, Mat &match, const Color r,
imshow("result", result);
waitKey(0);
}
}
return match;

4
src/core/feature.cpp
Unescape View File

@ -9,7 +9,7 @@ namespace easypr {
//! 获取垂直和水平的直方图图值
Mat getTheFeatures(Mat in) {
Mat getHistogram(Mat in) {
const int VERTICAL = 0;
const int HORIZONTAL = 1;
@ -49,7 +49,7 @@ void getHistogramFeatures(const Mat& image, Mat& features) {
Mat img_threshold;
threshold(grayImage, img_threshold, 0, 255,
CV_THRESH_OTSU + CV_THRESH_BINARY);
features = getTheFeatures(img_threshold);
features = getHistogram(img_threshold);
}
//! EasyPR的getFeatures回调函数

61
src/core/plate_locate.cpp
Unescape View File

@ -85,9 +85,7 @@ int CPlateLocate::mserSearch(const Mat &src, const Color r, Mat &out,
vector<RotatedRect> &outRects, int index) {
Mat match_grey;
Mat result = src.clone();
// width值对最终结果影响很大，可以考虑进行多次colorSerch，每次不同的值
// 另一种解决方案就是在结果输出到SVM之前，进行线与角的再纠正
cvtColor(result, result, COLOR_GRAY2BGR);
const int color_morph_width = 20;
const int color_morph_height = 5;
@ -179,6 +177,7 @@ int CPlateLocate::mserSearch(const Mat &src, const Color r, Mat &out,
Point center(charRect.tl().x + charRect.width / 2, charRect.tl().y + charRect.height / 2);
points.push_back(center);
cv::circle(result, center, 3, Scalar(0, 255, 0), 2);
if (charRect.area() - maxarea > 0.1f) {
maxrect = charRect;
maxarea = charRect.area();
@ -206,10 +205,24 @@ int CPlateLocate::mserSearch(const Mat &src, const Color r, Mat &out,
Rect rightRect(Point2f(rightPoint.x, rightPoint.y - maxrect.height / 2), maxrect.size());
cv::rectangle(result, leftRect, Scalar(255, 255, 0));
cv::rectangle(result, rightRect, Scalar(255, 255, 0));
/*vector<Mat> slideMat;
cv::rectangle(result, rightRect, Scalar(255, 255, 0));
int steplength = maxrect.width;
for (int step = - steplength / 2; step < steplength / 2; step++) {
int rightx = right + step;
Point2f rightPoint((float)rightx, k * (rightx - line[2]) + line[3]);
Rect slideRightRect(Point2f(rightPoint.x, rightPoint.y - maxrect.height / 2), maxrect.size());
Mat region = grayImage(slideRightRect);
Mat binary_region;
threshold(region, binary_region, 0, 255, CV_THRESH_BINARY | CV_THRESH_OTSU);
Mat charInput = preprocessChar(binary_region, 20);
slideMat.push_back(charInput);
}*/
}
@ -962,21 +975,45 @@ int CPlateLocate::plateColorLocate(Mat src, vector<CPlate> &candPlates,
//! MSER plate locate
int CPlateLocate::plateMserLocate(Mat src, vector<CPlate> &candPlates, int index) {
std::vector<Mat> channelImages;
std::vector<int> flags;
// only conside blue plate
if (1) {
Mat grayImage;
cvtColor(src, grayImage, COLOR_BGR2GRAY);
channelImages.push_back(grayImage);
flags.push_back(0);
//Mat singleChannelImage;
//extractChannel(src, singleChannelImage, 2);
//channelImages.push_back(singleChannelImage);
//flags.push_back(0);
//channelImages.push_back(255 - grayImage);
//flags.push_back(1);
}
vector<RotatedRect> rects_mser_blue;
vector<CPlate> plates;
Mat src_b;
//// 查找蓝色车牌
//// 查找颜色匹配车牌
mserSearch(src, BLUE, src_b, rects_mser_blue, index);
for (size_t i = 0; i < channelImages.size(); ++i)
{
Mat channelImage = channelImages[i];
int scale_size = 1024;
double scale_ratio = 1;
Mat image = scaleImage(channelImage, Size(scale_size, scale_size), scale_ratio);
//// 进行抗扭斜处理
deskew(src, src_b, rects_mser_blue, plates);
for (size_t i = 0; i < plates.size(); i++) {
candPlates.push_back(plates[i]);
mserSearch(image, BLUE, src_b, rects_mser_blue, index);
}
//deskew(src, src_b, rects_mser_blue, plates);
//for (size_t i = 0; i < plates.size(); i++) {
// candPlates.push_back(plates[i]);
//}
return 0;
}

2
src/train/ann_train.cpp
Unescape View File

@ -101,7 +101,7 @@ cv::Ptr<cv::ml::TrainData> AnnTrain::tdata() {
auto chars_files = utils::getFiles(sub_folder);
for (auto file : chars_files) {
auto img = cv::imread(file, 0); // a grayscale image
auto fps = features(img, kPredictSize);
auto fps = charFeatures(img, kPredictSize);
samples.push_back(fps);
labels.push_back(i);

Write Preview
Loading…
Cancel
Save