lo thap Object Detection Dataset and Pre-Trained Model by labelimages

Images

4962 images

Explore Dataset

Here are a few use cases for this project:

Waste Management and Recycling: The Lo Thap model could be utilized in the waste management industry to help with sorting different materials such as, ban (tire), contrung (eggshell), kimloai (metal), toc (hair), thuytinh (glass), be (turtle), and matnhom (aluminium). This would help to streamline the recycling process and improve waste management efficacy. The model can identify and categorize these items whether they're in a single or a mixed-waste context.
Quality Control in Manufacturing: The Lo Thap computer vision model could be utilized in a factory setting to identify and monitor the materials used in the manufacturing process. For instance, if a product is supposed to be made of a particular material such as kimloai or thuytinh, the computer vision model could help ensure the right materials are being used.
Crime Scene Investigation: The model can be used in forensic science where it can help in identifying various materials found on a crime scene. For instance, small fragments of glass (thuytinh) or metal (kimloai) or hair (toc) that need to be analyzed.
Environmental Monitoring: The model could be utilized for environmental studies, including beach cleanups or litter mapping. It could identify and quantify the presence of different materials like glass (thuytinh), metal (kimloai), tire (ban) which can often be found in these environments.
Education: The model could be used as an educational tool in schools to educate students about different materials and their properties. The model can identify and describe these materials via an interactive application where students can upload an image of an object and the model will identify the materials it's made of.

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{ lo-thap_dataset,
    title = { lo thap Dataset },
    type = { Open Source Dataset },
    author = { labelimages },
    howpublished = { \url{ https://universe.roboflow.com/labelimages/lo-thap } },
    url = { https://universe.roboflow.com/labelimages/lo-thap },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2022 },
    month = { dec },
    note = { visited on 2023-12-09 },
}