Abstract
In inventories, the context of object counting and speed of response becomes essential. The process is more straightforward when there are only a few items, but its complexity lies when there are many close or overlapping items. In addition, the pressure to meet tight inventory deadlines adds another challenge. This work aimed to develop a program that automates the accurate counting of similar objects in digital images, regardless of their quantity or arrangement. For this purpose, an algorithm has been implemented in Python. The main results show efficiency in analyzing images with similar objects, a significant step towards separating and accurately counting adjacent objects in various scientific fields. This solution promises to simplify and speed up the counting process in digital images, with potential beneficial applications in multiple scientific disciplines.
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