void mainloop(){
acquireData(&gd);
gdnorm = gd - grelax;
//printData(gdnorm);
detectGesture(gdnorm, gdiff, &gstartstate);
doTheThing();
}
void testApp::processSample(int x, int y, int z){
const int samplesToAverage = 4;
static int count = 0;
static int totalX, totalY, totalZ = 0;
totalX += x;
totalY += y;
totalZ += z;
count++;
if (count == samplesToAverage) {
sampleData[sampleCount][0] = quantizeAccelData(totalX / samplesToAverage);
sampleData[sampleCount][1] = quantizeAccelData(totalY / samplesToAverage);
sampleData[sampleCount][2] = quantizeAccelData(totalZ / samplesToAverage);
sampleCount++;
totalX = totalY = totalZ = 0;
count = 0;
}
if(sampleCount > (sampleDataLength - 1)){
endCapture();
int gesture = detectGesture();
cout << "Gesture: " << gesture << endl;
}
}
// subscribers retreive hand position on depth map for left and right hands of currently tracked user
void gestureTracker::l_hand_cb(const std_msgs::Int32MultiArray::ConstPtr& array)
{
l_hand_pos_prev = l_hand_pos;
std::vector<int>::const_iterator it = array->data.begin();
this->l_hand_pos.x = *it;
it++;
this->l_hand_pos.y = *it;
//cerr << " L: pos " << l_hand_pos.x << " " << l_hand_pos.y << endl;
if(abs(l_hand_pos_prev.x - l_hand_pos.x) > 10.0 || abs(l_hand_pos_prev.y - l_hand_pos.y) > 10.0)
return;
int w = 20;
int h = 20;
if(this->has_depth_data)
{
//while(this->in_use)
// waitKey(1);
this->in_use = true;
//Mat depth;
//depth = this->depth_img.clone();
//this->depth_img.copyTo(depth);
Size max = this->depth_img.size();
int max_x = max.width;
int max_y = max.height;
int tl_x = clamp(l_hand_pos.x-w/2, 1, (max_x-w)-1);
int tl_y = clamp(l_hand_pos.y-h/2, 1, (max_y-h)-1);
/*
cerr << " L: " << max_x << " " << max_y << endl;
cerr << " L: " << l_hand_pos.x << " " << l_hand_pos.y << endl;
cerr << " L: clamp in " << l_hand_pos.x-w/2 << " " << l_hand_pos.y-h/2 << endl;
cerr << " L: clamp in " << l_hand_pos.x-(w/2) << " " << l_hand_pos.y-(h/2) << endl;
cerr << " L: " << tl_x << " " << tl_y << " " << w << " " << h <<endl;
cerr << " L: first roi" << endl;
*/
Rect roi = Rect(tl_x, tl_y, w, h);
Scalar avg = cv::mean(this->depth_img(roi));
//cerr << " L: first roi success" << endl;
double scale_w = (avg[0]/(double)12750);
double scale_h = (avg[0]/(double)12750);
if(scale_w <= 0 || scale_h <= 0)
return;
int scaled_w = 1/scale_w * 110 + 60;
int scaled_h = 1/scale_h * 110 + 60;
//cerr << " L: " << avg[0] << " " << scaled_w << " " << scale_h << endl;
scaled_h = clamp(scaled_h, scaled_h, 200);
scaled_w = clamp(scaled_w, scaled_w, 200);
l_roi_size_filter.add(scaled_w);
scaled_w = l_roi_size_filter.average();
scaled_h = scaled_w;
int tl_x_new = clamp(l_hand_pos.x-scaled_w/2, 0, (max_x-scaled_w));
int tl_y_new = clamp(l_hand_pos.y-scaled_h/2, 0, (max_y-scaled_h));
/*
cerr << " L: " << tl_x_new << " " << tl_y_new << " " << scaled_w << " " << scaled_h << endl;
cerr << " L: scaling roi" << endl;
*/
Rect roi_scaled = Rect(tl_x_new, tl_y_new, scaled_w, scaled_h);
this->depth_img(roi_scaled).copyTo(l_hand_roi);
this->in_use = false;
//imshow("left", l_hand_roi);
//waitKey(60);
detectGesture(l_hand_roi, "left");
}
}
