trash mega Object Detection Dataset and Pre-Trained Model by Studio Boson

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Explore Dataset

Here are a few use cases for this project:

Waste Management Systems: The "trash mega" model can be used in smart garbage disposal systems to sort the different trash items as per their materials (like glass, plastic, paper, etc.) and classify them for effective recycling.
Smart Cities Maintenance: City municipal departments can implement this model into CCTV systems to detect littering in public areas in real-time, aiding cleanliness efforts and potentially identifying perpetrators.
Beach and Ocean Cleanup: Deployed on drones or other robotic systems, the model can help identify trash on beaches or floating in the sea, aiding cleanup operations and protecting marine life.
Environmental Research: Researchers can use it to analyze the extent of pollution in different areas and study the most commonly discarded waste materials, helping to formulate policies for better waste management.
Educational Tools: It could be integrated into mobile applications as a tool to educate people on proper waste disposal, showing in real-time what class the trash belongs to and where it needs to be disposed.

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{
                            trash-mega_dataset,
                            title = { trash mega Dataset },
                            type = { Open Source Dataset },
                            author = { Studio Boson },
                            howpublished = { \url{ https://universe.roboflow.com/studio-boson/trash-mega } },
                            url = { https://universe.roboflow.com/studio-boson/trash-mega },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { aug },
                            note = { visited on 2024-05-03 },
                            }