marcoromagnoli's profile - activity

Hi Maria:

Thank You so much for Your long and exhaustive reply. I did read it carefully as it deserve a proper attention and concentration. Still I have my doubts, not in the formula itself as that is very clear to me now, but in the methodology . First the fact that –numPos has to be different from the number of sample in the .vec file is not explained in any official documentation like opencv_user.pdf chapter four , and anybody who read, get the message they are the same (we need to update the documentation).

Second, more important, the formula as You say, is not giving any systematic and final way to calculate (given an already existing .vec file from a good dataset of positive), the –numPos value, because we cannot know in advance the value of S in the formula. What we can know is our setting of minHitrate, so if we set minHitRate equal to 0.9999999… it seems we never will get any error as in this way the falseNegativeCount pieces will always be less than one. Another possibility is the already mention one of setting numPos=(0,9 x num_in_vec) or (0,8 x num_in_vec), but that it look to me also a kind of trick without guaranty of success. The big problem here, as You know is the extremely LONG computational time for every stages , and to have the process crashed after few stages means to waste hours of work, and not to have any guaranty that new setting will lead to the “desideratum” final stage, without crashing another time.

What I did, is to utilize OpenCV 2.2 (I downgraded!) where you can set numPos=num_in_vec without problem and get your xml classifiers (somehow). 2.2 version (as an example) at every stages it consumes few and few positive, discharging the FalseNegativeCount pieces that You mention.

But now I ask Your Kind suggestion about what is better to do, after creating a good dataset of lets say 2000 positive, and getting the .vec file what should we do in order not-to-crash the process? Should we set numPos=0.9xNum_in_vec, or minHitRate=0.999999, or use version 2.2 or any better suggestion?

One final suggestion is about a different matter, as I’m working on this for my final Thesis for my master, I’d like to study in deep how is working the code of traincascade with the 3 different features: Haar, LBP and HOG, so I’ll appreciate any starting suggestions and tips from You on start studing the cpp code.

Best regard.

Marco Romagnoli

Hi All: Here: http://code.opencv.org/issues/1834 Maria Dimashova She is giving the formula : vec-file has to contain >= (numPose + (numStages-1) * (1 - minHitRate) * numPose) + S, where S is a count of samples from vec-file . First I would like to know where to find this formula, in which document . Second She is writing :Bug "It was fixed in r8913", What daes it mean r8913? Is it Opencv actual version 2.4.3 ? Thank You.

Hi Ekalic: ThankYou for Your answer. Now I have a different problem with traincascade, because the program is exiting with error: OpenCV Error: Bad argument (Can not get new positive sample. The most possible reason is insufficient count of samples in given vec-file. Here: http://code.opencv.org/issues/1834 Maria Dimashova She is giving the formula : vec-file has to contain >= (numPose + (numStages-1) * (1 - minHitRate) * numPose) + S, where S is a count of samples from vec-file . First I would like to know where to find this formula, in which document . Second She is writing :Bug "It was fixed in r8913", What daes it mean r8913? Is it Opencv actual version 2.4.3 ? Thank You.

Hi All: Here: http://code.opencv.org/issues/1834 Maria Dimashova She is giving the formula : vec-file has to contain >= (numPose + (numStages-1) * (1 - minHitRate) * numPose) + S, where S is a count of samples from vec-file . First I would like to know where to find this formula, in which document . Second She is writing :Bug "It was fixed in r8913", What daes it mean r8913? Is it Opencv actual version 2.4.3 ? Thank You.

Hi,

I'm training a classifier with opencv_traincascade.exe for a VideoSurveillance AirCam positioned in a fix place outside one office. I created about 1000 positive samples. Reading many tutorials I find out that the number of negatives should be more than the positive, BUT I doubt it in this case as the camera is fixed in a still place and the background is always the same. So my concerns is to create a dataset of negative images that is only about one hundred images, cropping different details of the same, and never changing background. Is it correct? Can anybody give me any hits. A suggestion will be welcome, and helpful. Thanks.