OpenCV Tutorial: Training your own detector | packtpub.com
Why Stack Overflow recommends it
Stack Overflow users link it as a worked example of training a custom OpenCV cascade detector, both in answers pointing people to opencv_traincascade and in questions where the training stalls or misdetects.
Recommended by 1 people across 1 different months, 2013 to 2017.
What it is
A short Packt tutorial from the 'OpenCV Computer Vision Application Programming' video course on training your own cascade classifier in OpenCV. It walks through collecting positive and background images, generating the description files and .vec file, and running the cascade training.
What people said
Recommends Darshan · 2013-11 · Stack Overflow · on “Object Detection project with OpenCV”
you would probably need to do these following steps. Find out and zero in on a feature detection and extraction algorithm you want to use(SIFT,SURF,ORB, there are few more). Detect and extract features. you should be storing descriptors extracted from a descriptor extractor in your xml files. add those descriptors to a trainer such as bowtrainer to create a dictionary. Train your classifier You can find lot of examples here [LINK] and you can watch this [this video] video if you want to realize something similar in your project.
Cites Troup · 2014-08 · Stack Overflow · on “OpenCV - LBP Traincascade can’t pass Precalculation in Stage 0, but HAAR works fine?”
I run opencv_traincascade, and I never reach the precalculation time for stage 0. Edit: My problem seems to be specific to LBP training. I changed featureType to HAAR and the classifier below finished training in a matter of minutes Edit: Precalculation time is in seconds, so at stage 0 you should see it reach precalculation within 10 seconds, but I've seen it as high as 40 seconds. Precalculation time may increase steadily from stage to stage, and then suddenly increase dramatically to half an hour in the later stages (and perhaps even longer than that if you are working with thousands of samples, but I haven't got that far yet) (I will continue to update this post filling in things I've co
Cites Fixus · 2014-12 · Stack Overflow · on “how to reduce wrong recognition using cascade classifier”
Hello I'm tring to recognize a car using cascade classifier, android and opencv library. My problem is that my phone is marking almoust everything as a car. I've created my code based on: [this video] and face detection sample. My app behave very strange cause marking looks like random. I even don't know if marking car is correct or maybe it is just some random behaviour. At the moment it is even marking my keyboard as a car. I'm not sure what can I improve. I don't see any progress between training it up to 5 or 14 stages I've trained my file up to 14 stages my code looks like this: @Override public Mat onCameraFrame(Mat aInputFrame) { // return FrameAnalyzer.analyzeFrame(aInputFrame); // Create
Cites sop · 2015-03 · Stack Overflow · on “SVM image target size issue”
First, your approach is not good. SVM is trying to say if the image is the same (in some size, as you said), so not if your image is containing an object in some region. So you need detect the object in the image and then classify it with the SVM. In your second image your iPod is too small, and there is too much information around it. You'll need a detector ( traincascade [this video] ). Or you can train a BOW (see this [LINK] for better understanding), and this will be able to say if your image contains the object or not. Or try to use the feature detector, descriptor extractor and matching for finding the same object (as here [LINK] ).
Cites jkarimi · 2015-09 · Stack Overflow · on “OpenCV: training a cascade classifier”
I am trying to train a cascade classifier using OpenCV, a tutorial [this video] & UIUC Image Database for Car Detection [LINK] . However, the training 'hangs' at stage 0 and never generates any files; in the tutorial, results are seen in a matter of minutes. I am running OpenCV 2.4.8, which I have installed using conda, on a 2015 MBP running Yosemite (10.10.5) Steps: Downloaded the dataset & saved the positive images in a pos folder and the negative images in a neg folder generated a txt file for the positive images find pos -iname "*.pgm" > cars.txt sed -i '' 's/.pgm/.pgm 1 0 0 100 40/g' cars.txt generated a txt file for the negative images find neg -iname "*.pgm" > bg.txt generated a vec file f
Cites BenJ · 2016-01 · Stack Overflow · on “Passive and automatic face recognition”
You could look at using opencv to train an object detector to look for the badge: [LINK] [this video] If each of the badges have some unique identifier for the students, you could then analyse the identifier to take attendance. Identifying the badge / face would be the "easy" part. Identifying the student would be the hard part! Identifying people from photos is tricky, and I would estimate that Facebook has spent millions on this problem. Here are a couple of links that may be useful [LINK] OpenCV identify person with face detection [LINK]
Cites CharlieWhite · 2017-06 · Stack Overflow · on “haar-cascade nothing come up with xml file”
Only 5KB for my cascade file. I have followed this one if you want to see it : link [this video] . I have spent a lot of time to read the documentation too. :)