Classifier with a lot of false positive

asked 2017-01-19 08:01:34 -0500

Hello, I'm depressed ... It's been a week since my training classifier turns and it's the drama ... I try to create a classifier to detect magpies ...

opencv_traincascade -data classifier -vec positives.vec -bg negatives.txt -numPos 1000 -numNeg 600 -numStages 10 -w 48 -h 48

I had a lot of trouble for the samples because the magpie is black and white, when creating samples there is a part of the magpie that disappears.

I was finally able to create samples using the script annotations, and then my samples.

I have 2000 positive images and 600 negatives. After a week of training, I test on an image and it works but I have detections more.

I have to mount the "minNeighbors" parameter thoroughly to make them disappear. Do you have any ideas to improve my classify?

Thanks.

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Comments

1

do you really have 2000 positive images ? or did you generate synthetic ones from a single image in create_samples (bad idea) ?

berak gravatar imageberak ( 2017-01-19 08:13:03 -0500 )edit
1

i use a lot of images (~200) with the annotation script who gives me the positions of the object (F... Magpies), and after, i put them in samples with create_samples who give me 1000 positives images

kabdriver gravatar imagekabdriver ( 2017-01-19 10:35:38 -0500 )edit

oooh, ok, i really did not expect that ..

berak gravatar imageberak ( 2017-01-19 10:45:44 -0500 )edit

Like he said, bad choice, read OpenCV 3 Blueprints, chapter 5 to know why :)

StevenPuttemans gravatar imageStevenPuttemans ( 2017-01-19 10:49:44 -0500 )edit
1

again, "birds-in-the-wild" are terribly hard.

maybe you can restrict it to a "profile" view, beak on the left ? (and flip the image later, to detect the "opposite" pose)

berak gravatar imageberak ( 2017-01-19 10:54:59 -0500 )edit