V1.0.0 Object Detection Dataset and Pre-Trained Model by eliana

Images

2498 images

Explore Dataset

Here are a few use cases for this project:

Ocean Cleanup and Conservation: V1.0.0 can identify trash items underwater, such as plastic bottles, fishing nets, and plastic bags. This could help in planning and executing ocean cleanup missions, tracking plastic pollution, and monitoring the impact of these waste materials on aquatic ecosystems, like coral reefs.
Waste Sorting and Recycling: The model can be implemented in waste sorting facilities to automatically identify different types of trash, such as bottles, bags, and plates, and sort them accordingly. This will improve recycling efficiency and reduce the contamination of recyclable materials.
Beach Cleanup and Monitoring: V1.0.0 can be used by environmental organizations or local authorities to assess the amount of plastic waste on beaches. By identifying and quantifying specific trash items, targeted cleanup efforts can be organized, and public awareness campaigns can be launched to reduce littering.
Consumer Behavior Analysis: Businesses, municipalities, and researchers can use the V1.0.0 model to understand patterns in garbage accumulation in public spaces or commercial establishments. This data can be used to evaluate the effectiveness of policies or campaigns aimed at minimizing waste, encouraging reusable alternatives, or reducing single-use plastic consumption.
Education and Awareness: V1.0.0 can be integrated into educational tools and applications to teach students and the general public about the impact of plastic waste on the environment. Interactive presentations or games using real images of trash items can help users better understand the problem, its consequences, and ways to prevent pollution.

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{
                            v1.0.0_dataset,
                            title = { V1.0.0 Dataset },
                            type = { Open Source Dataset },
                            author = { eliana },
                            howpublished = { \url{ https://universe.roboflow.com/eliana-cyhk3/v1.0.0 } },
                            url = { https://universe.roboflow.com/eliana-cyhk3/v1.0.0 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { dec },
                            note = { visited on 2024-05-06 },
                            }