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Counting objects in images is one of the fundamental tasks in computer vision. The task of counting objects is relatively easy for us, people, but it can be challenging for a computer vision algorithm. Deep learning (DL) methods provide the state-of-the-art performance in digital image processing. They require collecting a lot of annotated data, which is usually time consuming and prone to labelling errors. Alternative approaches leverage point-like annotations of objects positions, which are much cheaper to collect.