Developed a system for analyzing poker hands from video using OCR and OpenCV. The solution reads game data from frames, extracts key parameters of the situation, processes them through internal decision-making logic, and generates recommendations for further action.
The project implements recognition of interface elements, processing of video streams, data normalization, event-driven analysis logic, and output of hints based on predefined rules. The project represents a working MVP of a specialized tool for analyzing game situations.
The project implements recognition of interface elements, processing of video streams, data normalization, event-driven analysis logic, and output of hints based on predefined rules. The project represents a working MVP of a specialized tool for analyzing game situations.