This OpenCV tutorial is a very simple code example of GPU Cuda optical flow in OpenCV written in c++. The configuration of the project, code, and explanation are included for farneback Optical Flow method. Farneback algorithm is a dense method that is used to process all the pixels in the given image. The dense methods are slower but more accurate as all the pixels of the image are processed. In the following example, I am displaying just a few pixes based on a grid. I am not displaying all the pixes. In the opposite to dense method the sparse method like Lucas Kanade using just a selected subset of pixels. They are faster. Both methods have specific applications. Lucas-Kanade is widely used in tracking. The farneback can be used for the analysis of more complex movement in image scene and furder segmentation based on these changes. As dense methods are slightly slower, the GPU and Cuda implementation can lead to great performance improvements to calculate optical flow for all pixels o
13 stage opencv LBP cascade for people detection to download
My Opencv LBP 13 stage cascade for people detection. It is only 13 stages learned on 300 of positive people images. It is not trained enough. Training time is only under 1 hour. I have also a more trained version also on 300 people. They are just under testing. This is just what i want to release to public. Enjoy The cascade. It is not that bad. You need to only set the higher minNeighbors parameter. As I sayd it is not trained a lot.
Opencv cascade for people detection conditions of use
Also, Do not worry about the condition of use. Use only on your own risk. That's it. The dataset to train this cascade is only mine. I also colect positive and negative data. I just want to say, that there is also no conditions based on the datasets. There is no others conditions of use.Cascade classifier LBP great but real value is in Datasets
This cascade is just example achieved in 2 hours. One hour of training and the previous one for try to find right configuration and testing. There is much more time in preparing the dataset for testing and also for learning. I like to train cascade on more training images and also for more situations. All is matter of time. Nothing else. Only time, Sure there is nothing valuable than time.
LBP cascade training ( traincascade ) parameters
The utility is just traincascade.exe distributed with Opencv 3.1 version. Parameters are just like this.
-data v -vec vec.vec -bg bg.dat -numPos 300 -numNeg 300 -numStages 13 -numThreads 4
-stageType BOOST -featureType LBP -w 32 -h 64 -minHitRate 0.995 -maxFalseAlarmRate 0.42
-maxDepth 1 -maxWeakCount 100
There is one performance advice. If you have a cloud computer just focus on memory. To speed up
the learning process just increase precalcValBufSize and precalcIdxBufSize. One year ago i have set up Azure server for learning and 64 GB of ram is better than more cores. I would like to write something later about that. It was great to have this kind of computer and 30 000 well prepared positive examples for learning.
How to use LBP cascade in OPENCV
This code helps you to use the cascade. Complete code you can find in the previous article for Car detection in opencv
vector human;
cvtColor(img, img, CV_BGR2GRAY);
equalizeHist(img, img);
detectorBody.detectMultiScale(img, human,1.1,50,0|1,Size(5, 10),Size(300,480 ));
if (human.size() > 0) {
for (int gg = 0; gg < human.size(); gg++) {
rectangle(img, human[gg].tl(), human[gg].br(), Scalar(0, 0, 255), 2, 8, 0);
}
}
OPENCV LBP Cascade parameters
<?xml version="1.0"?>
<!--
This is just basic 13# stage haar cascade pedestrian detector develop by
V.K. from https://funvision.blogspot.com
-->
<opencv_storage>
<cascade>
<stageType>BOOST</stageType>
<featureType>LBP</featureType>
<height>64</height>
<width>32</width>
<stageParams>
<boostType>GAB</boostType>
<minHitRate>9.9500000476837158e-01</minHitRate>
<maxFalseAlarm>4.1999998688697815e-01</maxFalseAlarm>
<weightTrimRate>9.4999999999999996e-01</weightTrimRate>
<maxDepth>1</maxDepth>
<maxWeakCount>100</maxWeakCount></stageParams>
<featureParams>
<maxCatCount>256</maxCatCount>
<featSize>1</featSize></featureParams>
<stageNum>13</stageNum>
<stages>
OPENCV LBP Cascade download HERE
If you want to train some cascade. Just download my dataset for cars. It is also for free
See also my car dataset
What are them do.
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