Resolve detection objects pick by prob threshold.
Before this it will only pick the last object with prob > thresh wich is absolutely wrong Now it picks all the objects with prob > thesh. fixes #94
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+24
-23
@@ -113,34 +113,35 @@ void Yolo3Detection::postprocess(const int bi, const bool mAP){
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int x1 = (b.x+b.w/2.);
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int y0 = (b.y-b.h/2.);
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int y1 = (b.y+b.h/2.);
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int obj_class = -1;
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float prob = 0;
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for(int c=0; c<classes; c++) {
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if(dets[j].prob[c] >= confThreshold) {
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obj_class = c;
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prob = dets[j].prob[c];
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int obj_class = c;
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float prob = dets[j].prob[c];
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// convert to image coords
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x0 = x_ratio*x0;
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x1 = x_ratio*x1;
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y0 = y_ratio*y0;
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y1 = y_ratio*y1;
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tk::dnn::box res;
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res.cl = obj_class;
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res.prob = prob;
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res.x = x0;
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res.y = y0;
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res.w = x1 - x0;
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res.h = y1 - y0;
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// FIXME: this shuld be useless
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// if(mAP)
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// for(int c=0; c<classes; c++)
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// res.probs.push_back(dets[j].prob[c]);
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detected.push_back(res);
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}
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}
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if(obj_class >= 0) {
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// convert to image coords
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x0 = x_ratio*x0;
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x1 = x_ratio*x1;
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y0 = y_ratio*y0;
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y1 = y_ratio*y1;
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tk::dnn::box res;
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res.cl = obj_class;
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res.prob = prob;
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res.x = x0;
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res.y = y0;
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res.w = x1 - x0;
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res.h = y1 - y0;
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if(mAP)
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for(int c=0; c<classes; c++)
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res.probs.push_back(dets[j].prob[c]);
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detected.push_back(res);
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}
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}
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batchDetected.push_back(detected);
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}
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