Solidwaste Detection Instance Segmentation Dataset and Pre-Trained Model by VAPE

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Explore Dataset

Here are a few use cases for this project:

Recycling Industry: This model could be used to automate waste sortation at recycling facilities. This could lead to more efficient recycling, reducing the amount of wrongly sorted waste and increasing the volume of correctly identified materials for reuse.
Public Waste Management: Municipalities could use this technology to monitor public waste bins, helping guide collection routing based on the types of waste identified and bin capacity levels.
Eco-friendly Initiatives: NGOs or governmental agencies involved in pollution control could use this model to identify areas with high concentration of specific waste types. This could be useful in planning clean-up initiatives or for environmental impact studies.
Industrial Process Control: Companies producing glass, metal, and plastic products could use this model to monitor their production waste. This can help them identify the waste type immediately and plan for reusing or recycling, ensuring cost-effective and eco-friendly industrial practices
Education and Awareness: Schools or community outreach programs could use this computer vision model as an educational tool to showcase how different types of solid waste can be identified in real-time, raising awareness about the importance of proper waste separation and recycling.

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.

YOLOv8

This project has a YOLOv8 model checkpoint available for inference with Roboflow Deploy. YOLOv8 is a new 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{
                            solidwaste-detection_dataset,
                            title = { Solidwaste Detection Dataset },
                            type = { Open Source Dataset },
                            author = { VAPE },
                            howpublished = { \url{ https://universe.roboflow.com/vape-0gytc/solidwaste-detection } },
                            url = { https://universe.roboflow.com/vape-0gytc/solidwaste-detection },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { apr },
                            note = { visited on 2024-04-25 },
                            }