OpenCV has AdaBoost algorithm function.
And gpu version also is provided.
For using detection, we prepare the trained xml file.
Although we can train some target using adaboost algorithm in opencv functions, there are several trained xml files in the opencv folder. (mostly in opencv/sources/data/haarcascades )
I will use "haarcascade_frontalface_alt.xml" file for face detection example.
gpu and cpu both versions use xml file.
more detail refer to this source code.
The source code is included 2 version of cpu and gpu.
result is ..
gpu is faster than cpu version (but exactly they may not be same condition..)
blue boxes are result of cpu.
red boxes are results of gpu.
The results are not important because it can be different by parameters values.
<code start>
<code end>
Github
https://github.com/MareArts/AdaBoost-Face-Detection-test-using-OpenCV
#Tags
cvtColor, CascadeClassifier, CascadeClassifier_GPU, detectMultiScale,
9/24/2014
OpenCV face detection using adaboost example source code and cpu vs gpu detection speed compare (CascadeClassifier, CascadeClassifier_GPU, detectMultiScale)
Labels:
AdaBoost,
CascadeClassifier,
CascadeClassifier_GPU,
cvtColor,
detectMultiScale,
face detection,
OpenCV
Subscribe to:
Post Comments (Atom)
-
The MNIST dataset is a dataset of handwritten digits, comprising 60 000 training examples and 10 000 test examples. The dataset can be downl...
-
Logistic Classifier The logistic classifier is similar to equation of the plane. W is weight vector, X is input vector and y is output...
-
In past, I wrote an articel about YUV 444, 422, 411 introduction and yuv <-> rgb converting example code. refer to this page -> ht...
-
Image size of origin is 320*240. Processing time is 30.96 second took. The result of stitching The resul...
-
* Introduction - The solution shows panorama image from multi images. The panorama images is processing by real-time stitching algorithm...
-
Download for free https://www.spectacleapp.com/ I like it. ๐๐ป♂️
-
error: . VanillaPipeline.get_train_loss_dict: 12.6875 Traceback (most recent call last): File "/home/mare/anaconda3...
-
My Environment : MS VS 2008 & MFC(Dialog Based) Joy Stick : Logitech Extreme 3D pro (XBox Type) Cteated Date : 2012. 03 [source code]...
-
fig 1. Left: set 4 points (Left Top, Right Top, Right Bottom, Left Bottom), right:warped image to (0,0) (300,0), (300,300), (0,300) Fi...
-
RTSP(Real Time Streaming Protocol) is video streaming, it usually sent from network camera. VideoCapture function in opencv also can get r...
gpu::CascadeClassifier_GPU ada_gpu; having error in this line and
ReplyDeleteDo you use same opencv version 249?
DeleteThis comment has been removed by the author.
Deleteopencv 2.4.11 visual studio 2013 and cuda 7.5 toolkit
ReplyDeleteI think there are about 3 cause.
Delete1. the parameter changed of the function in 2.4.11
2. lib, dll, header file including missing.
3. code error(user fault)
Check try gain?
Thank you.
getting an error related to no gpu support even after successful cmake
DeleteCheck your dll is 32bit or 64bit?
Deleteand I uploaded source code on github
https://github.com/MareArts/AdaBoost-Face-Detection-test-using-OpenCV
The code is run well. I have tested just now.
Thank you.
thank you so much but i would like to know you opencv settings with visual studio and gpu
DeleteDownload opencv and set path in Visual Studio.
Deleterefer to here -> http://study.marearts.com/2013/08/visual-studio-2012-opencv-246-setting.html
But you want to use GPU, then build library self.
Set build option using cmake, and build in VS then dll is made.
refer to here
http://study.marearts.com/search/label/Opencv%20Build
but simple method is to use vs plug in. gpu use also possible
who made opecv plug to use simple in vs
refer to here
http://study.marearts.com/search/label/ceemple
I have problem to compile, I copy the "haarcascade_frontalface_alt.xml" file in a specific location?
ReplyDeletexml file located in project folder or bin folder.
DeleteThank you.
how do we optimize gpu functions? In my case gpu took more time in detection of faces than cpu.
ReplyDeletesee the opencv reference here -> http://docs.opencv.org/2.4/modules/objdetect/doc/cascade_classification.html#cascadeclassifier-detectmultiscale
DeleteI think that gpu will be faster, lager image and searching face more closely..
And should gpu performance good? we need expensive graphic card!!
Thank you.