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/*
* Copyright (c) 2019 Stephane Lenclud
*
* Permission to use, copy, modify, and/or distribute this software for any
* purpose with or without fee is hereby granted, provided that the above
* copyright notice and this permission notice appear in all copies.
*/
#include "point-extractor.h"
#include "preview.h"
#include "tracker-easy.h"
#include "cv/numeric.hpp"
#include "compat/math.hpp"
#include <opencv2/imgproc/types_c.h>
#include <cmath>
#include <algorithm>
#include <cinttypes>
#include <memory>
#include <QDebug>
using namespace numeric_types;
namespace EasyTracker
{
PointExtractor::PointExtractor() : s(KModuleName)
{
}
void PointExtractor::extract_points(const cv::Mat& aFrame, cv::Mat* aPreview, std::vector<vec2>& aPoints)
{
//TODO: Assert if channel size is neither one nor two
// Make sure our frame channel is 8 bit
size_t channelSize = aFrame.elemSize1();
if (channelSize == 2)
{
// We have a 16 bits single channel. Typically coming from Kinect V2 IR sensor
// Resample to 8-bits
double min = std::numeric_limits<uint16_t>::min();
double max = std::numeric_limits<uint16_t>::max();
//cv::minMaxLoc(raw, &min, &max); // Should we use 16bit min and max instead?
// For scalling to have more precission in the range we are interrested in
min = max - 255;
// See: https://stackoverflow.com/questions/14539498/change-type-of-mat-object-from-cv-32f-to-cv-8u/14539652
aFrame.convertTo(iFrameChannelSizeOne, CV_8U, 255.0 / (max - min), -255.0*min / (max - min));
}
else
{
iFrameChannelSizeOne = aFrame;
}
// Make sure our frame has a single channel
// Make an extra copy if needed
const int channelCount = iFrameChannelSizeOne.channels();
if (channelCount == 3)
{
// Convert to grayscale
// TODO: What's our input format, BRG or RGB?
// That won't make our point extraction work but at least it won't crash
cv::cvtColor(iFrameChannelSizeOne, iFrameGray, cv::COLOR_BGR2GRAY);
// TODO: Instead convert to HSV and use a key color together with cv::inRange to sport the color we want.
// Key color should be defined in settings.
}
else if (channelCount == 1)
{
// No further convertion needed
iFrameGray = iFrameChannelSizeOne;
}
else
{
eval_once(qDebug() << "tracker/easy: camera frame depth not supported" << aFrame.channels());
return;
}
// Contours detection
std::vector<std::vector<cv::Point> > contours;
cv::findContours(iFrameGray, contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE);
// Workout which countours are valid points
for (size_t i = 0; i < contours.size(); i++)
{
if (aPreview)
{
cv::drawContours(*aPreview, contours, (int)i, CV_RGB(255, 0, 0), 2);
}
cv::Rect bBox;
bBox = cv::boundingRect(contours[i]);
// Make sure bounding box matches our criteria
if (bBox.width >= s.min_point_size
&& bBox.height >= s.min_point_size
&& bBox.width <= s.max_point_size
&& bBox.height <= s.max_point_size)
{
vec2 center;
center[0] = bBox.x + bBox.width / 2;
center[1] = bBox.y + bBox.height / 2;
aPoints.push_back(vec2(center));
if (aPreview)
{
cv::rectangle(*aPreview, bBox, CV_RGB(0, 255, 0), 2);
}
}
}
// Keep only the three points which are highest, i.e. with lowest Y coordinates
// That's most usefull to discard noise from features below your cap/head.
// Typically noise comming from zippers and metal parts on your clothing.
// With a cap tracker it also successfully discards noise from glasses.
// However it may not work as good with a clip user wearing glasses.
while (aPoints.size() > 3) // Until we have no more than three points
{
int maxY = 0;
size_t index = -1;
// Search for the point with highest Y coordinate
for (size_t i = 0; i < aPoints.size(); i++)
{
if (aPoints[i][1] > maxY)
{
maxY = aPoints[i][1];
index = i;
}
}
// Discard it
aPoints.erase(aPoints.begin() + index);
}
}
}
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