Has anyone created a recall precision curve for traincascade? I am thinking of doing this at the detection stage:
Looking at the [docs](http://docs.opencv.org/modules/objdetect/doc/cascade_classification.html#cascadeclassifier-detectmultiscale), opencv provides this method:
> Python: cv2.CascadeClassifier.detectMultiScale(image,rejectLevels, levelWeights[,scaleFactor[, minNeighbors[, flags[,minSize[, maxSize[,outputRejectLevels]]]]]]) → objects
My questions are:
- What 'objects' are being returned by this method?
- Assuming rejectLevels refers to the confidence level for each detection window, why do I need to pass it in as a parameter?
- What do I need to pass in for rejectLevels and levelWeights?
- What is outputRejectLevels? Is it related to how certain the cascade should be to accept a detection?
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