Garbage Object Detection Dataset and Pre-Trained Model by dsoelma

Images

524 images

Explore Dataset

Here are a few use cases for this project:

Waste Management and Recycling: The model can be used to enhance waste sorting and recycling processes by classifying the amount and type of waste in a container. By identifying the level of fullness, waste management companies can optimize their collection schedules and routes.
Smart City Innovation: Cities can incorporate the model into their smart city initiatives to monitor and manage public waste disposal areas. The AI can determine when garbage cans are reaching capacity and schedule timely pickups, ultimately maintaining urban cleanliness.
Environmental Monitoring: It can be a crucial tool for environmental researchers to study patterns of waste disposal and detect incidences of improper waste disposal like instances of KGO (bulk waste) outside the container or creation of unauthorized landfills.
Civic Tech Apps: Developers can make use of this model in designing applications to motivate citizen participation towards maintaining cleanliness in their neighborhoods. Users could report overflowing bins or improper waste disposal, with the model validating the situation from user-provided images for efficient municipal response.
Indoor Waste Management: In a controlled environment such as offices or shopping malls, the model can be integrated into the security system to alert cleaning services when bins are reaching their full capacity, ensuring a clean and healthy environment.

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{
                            garbage-clixe_dataset,
                            title = { Garbage Dataset },
                            type = { Open Source Dataset },
                            author = { dsoelma },
                            howpublished = { \url{ https://universe.roboflow.com/dsoelma/garbage-clixe } },
                            url = { https://universe.roboflow.com/dsoelma/garbage-clixe },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jul },
                            note = { visited on 2024-06-02 },
                            }