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Been tinkering with OpenCV in python. The face detection demo is impressive.
Are there any free collection of Haar classifiers aside from the face, eyes and full body ones?
Sure, there are a few common ones which show up in most people's projects, although opencv should come with these:
cv haar cascades
eye cascades
You can make your own cascades, but be warned, it's a pretty cumbersome process. The best tutorial I found was this one.
HTH
Alejandro F. Reimondo has a few cascades on his site: http://alereimondo.no-ip.org/OpenCV/34
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I need a dataset for my future project based on image processing, hand recognition. I need a minimum of 5 hand position and orientation and a minumim of 200 images per set.
I want to know if there are websites where I can find a great variety of datasets.
I recommend you to search here: http://homepages.inf.ed.ac.uk/rbf/CVonline/Imagedbase.htm#gesture.
I needed this for a project too and I found a lot of variations here. It also depends on what kind of gestures you are looking for, but I think you will find here what you need.
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I'm new to YOLO and trying to make car counting application using YOLO. The cars is from video file. Is there any reference? Thank you
There are multiple places from which I suggest you try to learn:
1) The CNN course from coursera https://www.coursera.org/learn/convolutional-neural-networks
This course has a good explanation on yolo(There assignment is on car detection as well which can easily be extended to car counting) and the rest of the course is quite nice as well
2)https://towardsdatascience.com/yolo-you-only-look-once-real-time-object-detection-explained-492dc9230006
The article focus on a few implementation details and talks about the papers yolo and yolov2 , and helped me clear a out a few issues i had when i was trying to implement yolo
3)The original paper (although this may be too advanced ): https://arxiv.org/pdf/1506.02640v5.pdf
4)A keras implmentation : https://github.com/experiencor/keras-yolo2
A simple git clone if you wish to simply have the code , although i do not recommend this as it has very little actual learning and is simply a download and use option
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I was curious if anyone knew of something like this flowchart but for Computer Vision tasks? Specifically for OpenCV would be most ideal.
Or any references with best practices, and common patterns for Computer Vision problems?
That's a monumental task. The best I could find is from this article and it's a little bit old:
Maybe it's a good time to commit to FlexCV on Kickstarter.com, a GUI for OpenCV that allows you to create complex algorithms in a matter of minutes by connecting graphical elements together. It's an alternative for Adaptive Vision, but purely based on OpenCV features.
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I am looking for open source Face/ Image Detection, Recognition, Video Face Mining libraries similar to the ones that were at one time available from Pittsburg Pattern Recognition. I am also interested in libraries that detect various states of facial expressions that would work on captured still images.libra I looked at OpenCV but I was not able to find a cohesive library. Also, I would be interested in getting in touch with any group that would do contract development or license available libraries. Much thanks in advance.
OpenCV has support for Face Detection and even gesture recognition, such as smile recognition, like this: auto-smiley.
openFrameworks is a good library which wraps OpenCV and makes life considerably easier, very sophisticated image processing can be done with the two.
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I have found OpenCV code that uses CvGaussBGStatModelParams structure, cvCreateGaussianBGModel, and other related functions. However, I haven't been able to find any explanations for how they work and how they are to be used and what they mean.
Any help would be appreciated.
These functions are undocumented (at least as far as the manual goes). However, if you look around in the source, you will find them in src/cvaux/cvbgfg_gaussmix.cpp. In there:
This is based on the "An Improved
Adaptive Background Mixture Model for
Real-time Tracking with Shadow
Detection" by P. KaewTraKulPong and R.
Bowden
http://personal.ee.surrey.ac.uk/Personal/R.Bowden/publications/avbs01/avbs01.pdf
The windowing method is used, but not
the shadow detection. I make some of
my own modifications which make more
sense. There are some errors in some
of their equations.
That link is probably a good start for you.