Downwell AI Object Detection Dataset and Pre-Trained Model by CS230 Project

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Explore Dataset

Here are a few use cases for this project:

Game Development & Analysis: Developers could use the Downwell AI to analyze a gameplay, identifying and tracking all the classes throughout the game and examining players' responses, movement, and interaction with various game elements.
Automated Gameplay Commentary: The Downwell AI model could be used in a live game streaming or broadcasting setting to provide real-time commentary or analysis about the ongoing game events, player movements, and other various interactions by identifying the components in the game.
Player Training & Assistance: The Downwell AI could be leveraged to create an interactive guide or gaming assistant. It can observe the gameplay, identify the game elements, and suggest the next promising move or highlight potential threats based on the model's understanding of the game dynamics from previous playthroughs.
Behavior Analysis & Enhancement: The model could be employed for understanding player behavior and preferences by analyzing their interaction with different game elements. The gathered insight could inform game design decisions, improve engagement mechanisms, and enhance overall player experience.
Debugging & Quality Assurance: In a game development scenario, the Downwell AI can be incredibly useful for automated testing and quality assurance. It can be run through the game's various stages to identify any inconsistency, glitches, or abnormalities by recognizing each game component and its expected behavior.

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{
                            downwell-ai_dataset,
                            title = { Downwell AI Dataset },
                            type = { Open Source Dataset },
                            author = { CS230 Project },
                            howpublished = { \url{ https://universe.roboflow.com/cs230-project/downwell-ai } },
                            url = { https://universe.roboflow.com/cs230-project/downwell-ai },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { dec },
                            note = { visited on 2024-04-28 },
                            }