dogedash Object Detection Dataset and Pre-Trained Model by ea

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Explore Dataset

Here are a few use cases for this project:

Gaming Assistance: "dogedash" can be integrated into video games, particularly platformer or action games, to provide real-time object identification and assistance to players. It can help users understand game elements, identify threats or opportunities, and suggest strategies or actions tailored to the current in-game situation.
Automated Game Testing: Developers can use "dogedash" to automate the testing of object interactions, functionality, and performance within their games. By identifying and tracking object classes like coin, enemy, and missile, the model can help detect any anomalies or bugs and ensure that the game is running correctly.
Streamer and Content Creator Tool: "dogedash" can be incorporated into software used by game streamers and content creators. By providing real-time object identification, it can create overlays, visual cues, or informative pop-ups for viewers, enhancing their experience and understanding of the game being played.
Accessible Gaming: "dogedash" can be harnessed to create adaptive controller interfaces for gamers with physical or cognitive impairments. By identifying and tracking key in-game objects like doge, spiky_enemy, and fire, the model can help map alternative control schemes, user-specific timings, and other adjustments tailored to the gamer's individual needs.
Game Design Analysis: "dogedash" can be employed as a research tool for game designers and academics studying game mechanics, level design, and player interaction. By analyzing a range of games and identifying object classes, the model can provide insights into how these elements impact player engagement, difficulty, and overall experience.

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.

Cite This Project

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

@misc{
                            dogedash_dataset,
                            title = { dogedash Dataset },
                            type = { Open Source Dataset },
                            author = { ea },
                            howpublished = { \url{ https://universe.roboflow.com/ea-7s2vt/dogedash } },
                            url = { https://universe.roboflow.com/ea-7s2vt/dogedash },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jan },
                            note = { visited on 2024-06-15 },
                            }