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Is there a reason why we run ROI detection for training and keep those with large overlap, instead of just using the ground truth bounding boxes with transitional + scaling (random) augmentation?
Is there a reason why we run ROI detection for training and keep those with large overlap, instead of just using the ground truth bounding boxes with transitional + scaling (random) augmentation?