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I think you can solve your problem using Parameter learningrate
* learningRate The value between 0 and 1 that indicates how fast the background model is learnt. Negative parameter value makes the algorithm to use some automatically chosen learning rate. 0 means that the background model is not updated at all, 1 means that the background model is completely reinitialized from the last frame. *
when learningrate =0 background is initialise at first call and never update when you use apply method
