Tuesday, February 28, 2017
Retraining Classifier Results
This week I worked on retraining the haar cascade. After being able to create 1000 positive samples I used 500 negative samples as input for our narrow helix classifier. The first attempt of training only passed through 1 stage then terminated with the following error "Train dataset for temp stage can not be filled. Branch training terminated."
I learned that this occurred because the paths within my negative descriptor were incorrect, I quickly fixed this and retrained. On the second attempt stages 0 and 1 were loaded and I was able to enter into stage 2, but once again I encountered another issue "Required leaf false alarm rate achieved. Branch training terminated."
The third attempt I made to train the classifier was much more successful than the previous. I ended up starting from scratch without loading the last xml containing the results of prior stages and reached the third stage. I then tried testing the classifier with my detect script, but I was unable to detect any narrow helixes in my sample image.
Even though I wasn't able to detect helixes within my test images, we've made meaningful progress in training the classifier. Prior to now training didn't proceed past the 1st stage. With some minor adjustments we should be able to accurately detect segments of the ear.