mirror of https://github.com/davisking/dlib.git
Changed the object_detector interface slightly. In particular, it now handles
the adjust_threshold argument slightly differently in that it does not add it to the output detection score anymore.
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@ -293,10 +293,10 @@ namespace dlib
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if (w.size() != 0)
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{
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std::vector<std::pair<double, rectangle> > dets;
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const double thresh = w(scanner.get_num_dimensions()) + adjust_threshold;
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const double thresh = w(scanner.get_num_dimensions());
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scanner.load(img);
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scanner.detect(w, dets, thresh);
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scanner.detect(w, dets, thresh + adjust_threshold);
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for (unsigned long i = 0; i < dets.size(); ++i)
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{
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@ -153,15 +153,19 @@ namespace dlib
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- #dets.size() == the number of detected objects.
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- #dets[i].first gives the "detection confidence", of the i-th
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detection. This is the detection value output by the scanner
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minus the threshold, therefore this is a value > 0.
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minus the threshold.
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- #dets[i].second == the bounding box for the i-th detection.
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- #get_scanner() will have been loaded with img. Therefore, you can call
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#get_scanner().get_feature_vector() to obtain the feature vectors or
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#get_scanner().get_full_object_detection() to get the
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full_object_detections for the resulting object detection boxes.
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- The detection threshold is adjusted by having adjust_threshold added
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to it. Therefore, an adjust_threshold value > 0 makes detecting
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objects harder while a negative one makes it easier.
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- The detection threshold is adjusted by having adjust_threshold added to
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it. Therefore, an adjust_threshold value > 0 makes detecting objects
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harder while a negative one makes it easier. Moreover, the following
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will be true for all valid i:
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- #dets[i].first >= adjust_threshold
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This means that, for example, you can obtain all possible detections as
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outputs by setting adjust_threshold equal to negative infinity.
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!*/
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template <
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