dockerfile/openalpr-base
1
0
Fork 0
mirror of https://github.com/kerberos-io/openalpr-base.git synced 2025-10-07 01:52:45 +08:00
Code Issues Packages Projects Releases Wiki Activity

Rearranged threshold data to be contained in pipeline_data

Browse Source
This commit is contained in:
Matt Hill
2014-07-01 18:52:53 -04:00
parent a0af4093d6
commit 7e12ca1500
13 changed files with 82 additions and 75 deletions
Download Patch File Download Diff File Expand all files Collapse all files

37
src/openalpr/characteranalysis.cpp
View File

@@ -36,29 +36,26 @@ CharacterAnalysis::CharacterAnalysis(PipelineData* pipeline_data)
CharacterAnalysis::~CharacterAnalysis()
{
for (int i = 0; i < thresholds.size(); i++)
{
thresholds[i].release();
}
thresholds.clear();
}
void CharacterAnalysis::analyze()
{
thresholds = produceThresholds(pipeline_data->crop_gray, config);
pipeline_data->clearThresholds();
pipeline_data->thresholds = produceThresholds(pipeline_data->crop_gray, config);
timespec startTime;
getTime(&startTime);
for (int i = 0; i < thresholds.size(); i++)
for (int i = 0; i < pipeline_data->thresholds.size(); i++)
{
vector<vector<Point> > contours;
vector<Vec4i> hierarchy;
Mat tempThreshold(thresholds[i].size(), CV_8U);
thresholds[i].copyTo(tempThreshold);
Mat tempThreshold(pipeline_data->thresholds[i].size(), CV_8U);
pipeline_data->thresholds[i].copyTo(tempThreshold);
findContours(tempThreshold,
contours, // a vector of contours
hierarchy,
@@ -79,9 +76,9 @@ void CharacterAnalysis::analyze()
getTime(&startTime);
for (int i = 0; i < thresholds.size(); i++)
for (int i = 0; i < pipeline_data->thresholds.size(); i++)
{
vector<bool> goodIndices = this->filter(thresholds[i], allContours[i], allHierarchy[i]);
vector<bool> goodIndices = this->filter(pipeline_data->thresholds[i], allContours[i], allHierarchy[i]);
charSegments.push_back(goodIndices);
if (config->debugCharAnalysis)
@@ -100,7 +97,7 @@ void CharacterAnalysis::analyze()
if (hasPlateMask)
{
// Filter out bad contours now that we have an outer box mask...
for (int i = 0; i < thresholds.size(); i++)
for (int i = 0; i < pipeline_data->thresholds.size(); i++)
{
charSegments[i] = filterByOuterMask(allContours[i], allHierarchy[i], charSegments[i]);
}
@@ -108,7 +105,7 @@ void CharacterAnalysis::analyze()
int bestFitScore = -1;
int bestFitIndex = -1;
for (int i = 0; i < thresholds.size(); i++)
for (int i = 0; i < pipeline_data->thresholds.size(); i++)
{
//vector<bool> goodIndices = this->filter(thresholds[i], allContours[i], allHierarchy[i]);
//charSegments.push_back(goodIndices);
@@ -120,7 +117,7 @@ void CharacterAnalysis::analyze()
bestFitScore = segmentCount;
bestFitIndex = i;
bestCharSegments = charSegments[i];
bestThreshold = thresholds[i];
bestThreshold = pipeline_data->thresholds[i];
bestContours = allContours[i];
bestHierarchy = allHierarchy[i];
bestCharSegmentsCount = segmentCount;
@@ -272,7 +269,7 @@ Mat CharacterAnalysis::findOuterBoxMask()
}
}
Mat mask = Mat::zeros(thresholds[winningIndex].size(), CV_8U);
Mat mask = Mat::zeros(pipeline_data->thresholds[winningIndex].size(), CV_8U);
// get rid of the outline by drawing a 1 pixel width black line
drawContours(mask, allContours[winningIndex],
@@ -316,7 +313,7 @@ Mat CharacterAnalysis::findOuterBoxMask()
if (biggestContourIndex != -1)
{
mask = Mat::zeros(thresholds[winningIndex].size(), CV_8U);
mask = Mat::zeros(pipeline_data->thresholds[winningIndex].size(), CV_8U);
vector<Point> smoothedMaskPoints;
approxPolyDP(contoursSecondRound[biggestContourIndex], smoothedMaskPoints, 2, true);
@@ -337,12 +334,12 @@ Mat CharacterAnalysis::findOuterBoxMask()
if (this->config->debugCharAnalysis)
{
vector<Mat> debugImgs;
Mat debugImgMasked = Mat::zeros(thresholds[winningIndex].size(), CV_8U);
Mat debugImgMasked = Mat::zeros(pipeline_data->thresholds[winningIndex].size(), CV_8U);
thresholds[winningIndex].copyTo(debugImgMasked, mask);
pipeline_data->thresholds[winningIndex].copyTo(debugImgMasked, mask);
debugImgs.push_back(mask);
debugImgs.push_back(thresholds[winningIndex]);
debugImgs.push_back(pipeline_data->thresholds[winningIndex]);
debugImgs.push_back(debugImgMasked);
Mat dashboard = drawImageDashboard(debugImgs, CV_8U, 1);
@@ -354,7 +351,7 @@ Mat CharacterAnalysis::findOuterBoxMask()
}
hasPlateMask = false;
Mat fullMask = Mat::zeros(thresholds[0].size(), CV_8U);
Mat fullMask = Mat::zeros(pipeline_data->thresholds[0].size(), CV_8U);
bitwise_not(fullMask, fullMask);
return fullMask;
}