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I’m training an object detection model on yolov8 but my training data is a little biased because it doesn’t represent the real life distribution. (I want to count objects of one class but different shape in a video and need them to be detected with near equal probability. ) How can I make sure to generalise the model enough so that the bias doesn’t have too much of an effect? I know it will come with more false positives, but that’s not a problem.
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