Training Options Used –
-npos 1898
-nneg 625
-nstages 20
-mode ALL
The number of positive images used to train this classifier was 1898, the number of negative images used was 625 and specified that the number of stages the trainer should try to complete is 20. Used the mode ALL switch, which not only includes the basic haar like features but an extended set of features, here is a link to the feature sets Haar-like features. During the training phase of this cascade it finished in stage 20, which created 139 total weak classifiers. In this stage it reached the desired minimum false alarm rate, or else the false alarm rate will be too high for real world use. This positive set had a few more images, most of the additions were from images that contained a cavity in Quadrant 3, and the image was rotated and saved as new image so that its cavity now resides in Quadrant 1.
NEG: 148 9.77509e-005
Used a modified version of the OpenCV haartrainer.
-data "F:\Thesis Research\AutomatedCMEDetector\HaarClassifier\haarcascade18" -vec "F:\Thesis Research\AutomatedCMEDetector\Test Sets\Positive Solar Cavities\positivesoutput.vec" -bg "F:\Thesis Research\AutomatedCMEDetector\Test Sets\Negative Solar Cavities\negatives.txt" -npos 1134 -nneg 625 -nstages 20 -mode ALL
Hit rate ≈ 56.7%
Tags: testing outcomes, trials