My Valorant Object Detection Dataset and Pre-Trained Model by NotSam

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Here are a few use cases for this project:

Strategic Gameplay Assistance: The "My Valorant" model could be utilized to provide real-time strategic insights for competitive players by identifying friends, enemies, smoke areas, and bomb positions, thus enhancing gameplay decision-making.
Highlight Compilation: The model could be used in creating highlight reels or clips from gameplay. By identifying key elements such as enemy encounters, friend actions, and critical moments involving the bomb or smoke, it can automatically curate the most exciting parts of a game.
Real-time Coaching: The model could serve as a coaching tool, providing new or less experienced players with guidance during gameplay. It could highlight potential threats, suggest when to use smokes, and alert players about the bomb's location.
Accessibility Aid: The model could be adapted to assist players with visual impairments by providing auditory cues about the locations of friends, enemies, smokes, and the spike, improving the accessibility of the game.
Game Analysis: eSports analysts and commentators could use this model to break down and understand key moments of gameplay for post-match analysis, contributing to strategic discussions about game outcomes.

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.

YOLOv5

This project has a YOLOv5 model checkpoint available for inference with Roboflow Deploy. YOLOv5 is a proven and tested, production ready, 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{
                            my-valorant_dataset,
                            title = { My Valorant Dataset },
                            type = { Open Source Dataset },
                            author = { NotSam },
                            howpublished = { \url{ https://universe.roboflow.com/notsam-jqwtl/my-valorant } },
                            url = { https://universe.roboflow.com/notsam-jqwtl/my-valorant },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { sep },
                            note = { visited on 2024-05-02 },
                            }