# Revision history [back]

### Performance evaluation for detection

I'm trying to evaluate some cascades I have trained with trainingcascade.cpp. So I would like to know if using the intersection of two rectangles (the reference rect and the detected rect) is a good metric. The criteria would be something:

if det.area() < (0.9*ref.area())
hit++
else
miss++


It is good enough to evaluate? I have looked the code in opencv_performance, but did not understood well the metric used here. It is a code for rect intersection or another thing?

Thanks!

### Performance evaluation for detection

I'm trying to evaluate some cascades I have trained with trainingcascade.cpp. So I would like to know if using the intersection of two rectangles (the reference rect and the detected rect) is a good metric. The criteria would be something:

if det.area() intersect.area() < (0.9*ref.area())
hit++
else
miss++


It is good enough to evaluate? I have looked the code in opencv_performance, but did not understood well the metric used here. It is a code for rect intersection or another thing?

Thanks!

### Performance evaluation for detection

I'm trying to evaluate some cascades I have trained with trainingcascade.cpp. So I would like to know if using the intersection of two rectangles (the reference rect and the detected rect) is a good metric. The criteria would be something:

if intersect.area() < > (0.9*ref.area())
hit++
else
miss++


It is good enough to evaluate? I have looked the code in opencv_performance, but did not understood well the metric used here. It is a code for rect intersection or another thing?

Thanks!