haar-classifier

问题 I am trying to train a Haar Cascade to detect hands. I have a vec file of size 1000. I have 40 positive images and 600 negative images. I have tried both dropping my positive images and negative images. When I run the following command I receive the following error: opencv_traincascade -data classifier -data classifier -vec samples.vec -bg negatives.txt -numstages 20 -minHitRate 0.999 -maxFalseAlarmRate 0.5 -numPos 1000\ -numNeg 600 -w 80 -h 40 -mode ALL -precalcValBufSize 1024\

问题 This is the first time I use openCV library. I want to use it to detect the eyes. I have used the FdActivity code available in this tutorial: http://romanhosek.cz/android-eye-detection-updated-for-opencv-2-4-6/ The tutorial uses OpenCV 2.4.6, but I have downloaded version 3.1 in my project. Due to the version differences I have changed the lines that uses putText, rectangle, and circle to be imported from imgproc instead of Core. This is all what I've changed. I have added haarcascade_lefteye

问题 I trained my pc with opencv_traincascade all one day long to detect 2€ coins using more than 6000 positive images similar to the following: Now, I have just tried to run a simple OpenCV program to see the results and to check the file cascade.xml . The final result is very disappointing: There are many points on the coin but there are also many other points on the background. Could it be a problem with my positive images used for training? Or maybe, am I using the detectMultiScale() with

问题 Using a C# implementation of Open CV which in turn is directly based on the OpenCV Java source here. http://docs.opencv.org/java/ The specific line where I call the HAAR classifier is cascade.detectMultiScale(grayMat, faces, 1.2, 3, 2, new Size(60, 60), new Size(150, 150)); The problem is I only want to track one face at a time, even if several are detected. ie if there are 2 faces detected, my tracking rectangles keep jumping randomly between the 2 faces. How can I ONLY detect 1 face at a

问题 I trained the cascade classifier to detect letters, this is the code I'm using. When I start the program, it opens my web cam but doesn't show the image (frames) and the detection but just a single blank window. I noticed this line causes the problem: faces_cascade.detectMultiScale(frame_gray, faces, 1.1, 2, 0 | CASCADE_SCALE_IMAGE, Size(30, 30)); This is the xml file. What should I do to make it show the captured frames and start detecting? Thank you. 回答1: I finally got it, I had to train my

问题 I want to create my own haarcascade for license plates. I have found a GUI called Cascade-Trainer-GUI that does this. I'm using Windows 10. You can download gui from here: http://amin-ahmadi.com/cascade-trainer-gui/ I have two folders with positive and negative images. There are about 650 positive images and 570 negative images. When I run the program, it finishes in a couple of seconds, but I do not get cascade.xml file. I get .txt file, and in the end of that txt file it says : OpenCV Error

问题 I am working on a project in my school to detect how many students are in the classroom. Like in this picture. I have been trying to use Haar Cascade in opencv for face detection to detect people, but the result is very bad. Like this: I took thousands of pictures in classroom, and cropped the picture with people manually. There are about 4000 positive samples and 12000 negative samples. I was wondering what did I do wrong? When I crop the image, should I only crop only head like this? Or

问题 Please help to get more knowledge on the my first-time haar training results. So I want to train Haar classifier to recognize simple pen, following Dileep Kumar’s article. Using my cellphone I made 14 pen pictures. These pictures size is big about: 263x2814 Then I collected negative pictures, some of them downloaded from web, with size 640x480 , and some of them made using my phone camera, with size: 1920x1080,5313x2388 Some of these negative images are really big. I have total 158 negative

问题 Closed. This question is off-topic. It is not currently accepting answers. Want to improve this question? Update the question so it's on-topic for Stack Overflow. Closed 4 years ago . I need a collection of sample images to train a Haar-based classifier for face detection. I read that a ratio of 2 negative examples for each positive example is acceptable. I searched around the web and found many databases containing positive examples to train my classifier (that is, images that contain faces)

问题 I am using Haar cascade in an emotion detection system. Every video input I am giving to the model has only one face in it (It is a requirement). When I run Haar cascade model to detect faces, it has some false positives. Since I have only one face in the video, I want to take the most positive area detected and ignore all other detection. Is there a way to do that? 回答1: when you are calling detectMultiScale function, set the minNeighbours value to a high value to avoid false positives. Also,