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Hi everyone!! I have a few basic questions regarding the object detection available on OpenCV.

First: I is said all over the internet that a good positive folder is a huge step of the traincascade process: good images may lead to good results. My question is: is there an optimal resolution this positive images should have?

Second: About the negative folder, most times people say "random images not containing the object you want to recognize". Well, should i put images of other trained objects? Or should i put ridiculous images like forests and stuff? I'm a little lost regarding the contents of this folder..

Third: When i create the vector, what importance has the size you pick? The bigger w and h parameters, the better? I doesn't really matter? I always put 32, but truth is i've tried with -w 50 -h 50 and it gave out a better result.

Fourth: About groupRectangles(..) : what should the second and third arguments be? I guess if i use this function to try to reduce some redundant rectangles, i will DISABLE the possibility of identifying two of the same object on the same picture, right?

I'd really appreciate any help at all. Thanks in advance :)

Hi everyone!! I have a few basic questions regarding the object detection available on OpenCV.

I have a few basic questions regarding the object detection available on OpenCV.

1. I is said all over the internet that a good positive folder is a huge step of the traincascade process: good images may lead to good results. My question is: is there an optimal resolution this positive images should have?

2. About the negative folder, most times people say "random images not containing the object you want to recognize". Well, should i put images of other trained objects? Or should i put ridiculous images like forests and stuff? I'm a little lost regarding the contents of this folder..

3. When i create the vector, what importance has the size you pick? The bigger w and h parameters, the better? I doesn't really matter? I always put 32, but truth is i've tried with -w 50 -h 50 and it gave out a better result.

4. About groupRectangles(..) : what should the second and third arguments be? I guess if i use this function to try to reduce some redundant rectangles, i will DISABLE the possibility of identifying two of the same object on the same picture, right?

I have a few basic questions regarding the object detection available on OpenCV.

1. I is said all over the internet that a good positive folder is a huge step of the traincascade process: good images may lead to good results. My question is: is there an optimal resolution this positive images should have?

2. About the negative folder, most times people say "random images not containing the object you want to recognize". Well, should i put images of other trained objects? Or should i put ridiculous images like forests and stuff? I'm a little lost regarding the contents of this folder..

3. When i create the vector, what importance has the size you pick? The bigger w and h parameters, the better? I doesn't really matter? I always put 32, but truth is i've tried with -w 50 -h 50 and it gave out a better result.

4. About groupRectangles(..) : what should the second and third arguments be? I guess if i use this function to try to reduce some redundant rectangles, i will DISABLE the possibility of identifying two of the same object on the same picture, right?