SVM + HOG learning and detection methods using HogDescriptor
Dear Erol çıtak
This posting is for cleanning up the SVM + HOG learning and detection methods to help you.
Step 1. Prepare Data.
Prepare Positive and Negative images
Same size and gray scale
And make xml file for a more convenient data management.
Refer to this page for this step
Step 2. Training by SVM
Load positive.xml and Negative.xml and train by SVM
Refer to this page for this step 2
Step 3. Test by SVM
After training, test other images.
Refer to this page for this step 3
Step 4. for using MultiScaleDetection()
For using Hog.MultiScaleDetection() and other functions.
We have to change the value that result of svm training.
Refer to this page for Step 4. (There is a method for converting the end of source code)http://study.marearts.com/2014/11/opencv-svm-learning-method-and-xml.html
refer to this source code for using method..
//Load trained SVM xml data FileStorage svmDX_Xml("XXXXX.xml", FileStorage::READ); Mat xMat; svmDX_Xml["SecondSVMd"] >> xMat; vector< float> VX; //copy mat to vector VX.assign((float*)xMat.datastart, (float*)xMat.dataend); //HogDescriptor HOGDescriptor d( Size(64,64), Size(16,16), Size(8,8), Size(8,8), 9); //must be same with training setting. d.setSVMDetector(VX); ... d.detect(...) or d.detectMultiScale(...)..