1 try Object Detection Dataset and Pre-Trained Model by Sk Andrey

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Explore Dataset

Here are a few use cases for this project:

Gaming Strategy Analysis: Utilize the "1 try" computer vision model to analyze player strategies in Pokémon games. By recognizing different elements like players, ingame actions, bets, table positions, game limits, card choices, button activities, and pot sizes, the model can provide insight into gameplay tactics, help players understand their competitor's strategy, and boost their game performance.
Gameplay Broadcasting: Streamers and gaming content creators can use this model to create active overlays during live streams or video content, helping their viewers by clearly demonstrating the ongoing game elements and activities in an engaging and interactive way.
Game Development: Game developers can use it to test game interfaces, user experiences, and game functionality during the development stage. By automated identification of game elements, developers can ensure that everything is working as expected and bugs are identified early.
Online Tournament or Gaming Event Surveillance: In online tournament situations, the model could be used to monitor game events to prevent fraud and ensure fair play. It would do so by identifying any unusual performance or signs of cheating via sophisticated card play, betting patterns, and button activities.
E-learning Platform Integration: An e-learning platform can integrate this model to create interactive learning experiences for users who aim to learn and improve their Pokémon gaming strategies. The model can help pinpoint key indicators for success within the games based on gameplay elements, providing users with hands-on, visually enhanced learning.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

YOLOv8

This project has a YOLOv8 model checkpoint available for inference with Roboflow Deploy. YOLOv8 is a new state-of-the-art real-time object detection model.

Cite This Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{
                            1-try_dataset,
                            title = { 1 try Dataset },
                            type = { Open Source Dataset },
                            author = { Sk Andrey },
                            howpublished = { \url{ https://universe.roboflow.com/sk-andrey-hl90o/1-try } },
                            url = { https://universe.roboflow.com/sk-andrey-hl90o/1-try },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jul },
                            note = { visited on 2024-06-18 },
                            }