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Automatická vizuální podpora pro Q-řazení
Kán, Dávid ; Hradiš, Michal (referee) ; Vaško, Marek (advisor)
This bachelor thesis deals with the integration of Q-sorting and computer vision methods for object detection. The goal of the work is to create a program that, with the help of~visual support, will facilitate the process and at the same time prevent errors in Q-sorting. Furthermore, the work deals with the creation of~a suitable data set for training the model and for experiments, which takes into account the way the cards are laid out and the~environment. The implemented program takes the form of a console application and is written using the Python programming language. The program uses YOLOv8 to detect objects and uses Pero OCR to retrieve text from cards. Using the created test set, experiments were performed on the trained model and the program was tested.

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1 Kan, Dmitriy
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