Omkar2118/datasets huggingface dataset:
Ticket to Ride Games

Description:

<a href="https://gts.ai/dataset-download/ticket-to-ride-games/" target="_blank">👉 Download the dataset here</a>

Ticket to Ride Games is a popular strategic board game where players compete to connect various cities on a map by placing their train pieces along specific routes. The objective is to complete the longest and most valuable routes while blocking opponents' paths. The game involves strategic planning, as each player's moves impact the overall board configuration and the availability of routes. This dataset is designed for enthusiasts, researchers, and Al developers interested in analyzing board game strategies, computer vision tasks, and data-driven game mechanics. It provides a comprehensive look at how different players approach the game, offering insights into decision-making processes, route optimization, and game dynamics.

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Content:

The dataset contains high-resolution images capturing various board configurations during the game, showcasing the players' city connections. The images are taken from four different angles to provide a complete view of the board's layout. Additionally, the dataset includes a well-structure CSV file that labels each player's city connections, detailing which cities have been successfully link by train routes. This labeling allows for in-depth analysis and pattern recognition, making it an ideal resource for those interest in game theory, Al training, or visual recognition models.

Key Features:

Images: Over [insert number] high-quality images of board configurations during gameplay, capturing different stages and strategies employe by players.

Angles: Each configuration is photograph from four distinct angles, ensuring comprehensive visual data for analysis.

CSV Labeling: The accompanying CSV file provides detail labeling of players' city connections, specifying which routes have been claim by each player. This structured data enables various analytical approaches, including statistical analysis, machine learning, and Al model training.

Versatile Applications: The dataset can be use for computer vision tasks, such as object detection and image segmentation, as well as for developing Al models to simulate or predict player strategies in board games.

Research Potential: Ideal for academic research, game development, and Al training, this dataset offers a rich source of data for exploring the complexities of board game strategies and player behaviors.

This dataset is sourced from Kaggle.