Haar Training

Athena on January 12th, 2012

In a meeting with my advisers, it was said by one of their colleagues that the AIA 211 images might be more detailed in the features to detect. Since originally I decided to use AIA 193, because visually it was easier for me to see and identify the solar cavities, I decided to try the […]

Continue reading about Running Classifier on Composite Validation Set

Athena on December 9th, 2011

In testing the classifiers produced, I ran it initially against the training set that was used to create the classifier, as seen in the previous post. So now we are going to start running tests on new image sets, to see how it truly performs on images it has never “seen” before. The below hit […]

Continue reading about Running Classifier on Validation Set

Athena on November 23rd, 2011

When creating samples from the marked images the default options are listed below. You notice that the default for the maxzangle is less than the defaults for the x and y angle values. So why is that? What do these parameters mean?   The Haar Classifier was initially developed for facial detections, but has been […]

Continue reading about CreateSamples ::: [ Maxxangle, Maxyangle, Maxzangle ]

Athena on September 16th, 2011

Below are examples of the haar-like feature sets that are used in training. It displays what features are used based on the “mode” option used as well as the string representation that will be used in each of the AdaBoostCARTHaarClassifier.txt files created for each stage on the classifier. haar_x2 haar_y2 haar_x3 haar_y3 haar_x2_y2 haar_x4 haar_y4 […]

Continue reading about Haar-like Features

Athena on September 10th, 2011

In running through tests against all the haarcascades I create, I noticed that the number of Misses in Quadrant III seemed surprisingly high, even when the cavity was a very distinct one.   Here is an example of the original image that was used to train the cascades. Here is an output file from the […]

Continue reading about Missed Hits in Quadrant III

Athena on August 14th, 2011

Once you have a *.xml file that you created from training the classifier then you can test the performance of that classifier cascade against your prositive test or you could create a validation test set to test performance against. OpenCV comes with a built in performance utility C:\OpenCV2.2\bin>opencv_performance.exe -data “C:\My Documents\HaarClassifier\haarcascade\haarcascade.xml” -info “C:\My Documents\Positive Test […]

Continue reading about Performance Testing your Classifier

Athena on August 13th, 2011

Once your training is done there will be a number of directories created in your haarcascade location you specified when your training first began. The directories will be labelled from 0…N where N is the total number of stages the trainer completed. In each directory there will be one AdaBoostCARTHaarClassisifer.txt file and each of the […]

Continue reading about AdaBoostCARTHaarClassifier Text Files

Athena on August 13th, 2011

When going through the training stages you might find that your training has come to a halt where its progress isn’t getting any further and or it has exited out improperly. If this happens you can still turn the stages it did successfully complete into a Classifier Cascade XML. OpenCV comes with a built in […]

Continue reading about Converting an intermediate cascade set

Athena on August 13th, 2011

Once you have a *.vec file that you created from your positive images you are ready to train your classifier. OpenCV comes with a built in training utility opencv_haartraining.exe -data “C:\My Documents\HaarClassifier\haarcascade” -vec “C:\My Documents\Positive Test Set\positives.vec” -bg “C:\My Documents\Negative Test Set\negatives.txt” -npos 1134 -nneg 625 -nstages 20 Explanation of the code above: opencv_haartraining.exe is […]

Continue reading about Training a Haar Classifier